Introduction
Groovy…
-
is an agile and dynamic language for the Java Virtual Machine
-
builds upon the strengths of Java but has additional power features inspired by languages like Python, Ruby and Smalltalk
-
makes modern programming features available to Java developers with almost-zero learning curve
-
provides the ability to statically type check and statically compile your code for robustness and performance
-
supports Domain-Specific Languages and other compact syntax so your code becomes easy to read and maintain
-
makes writing shell and build scripts easy with its powerful processing primitives, OO abilities and an Ant DSL
-
increases developer productivity by reducing scaffolding code when developing web, GUI, database or console applications
-
simplifies testing by supporting unit testing and mocking out-of-the-box
-
seamlessly integrates with all existing Java classes and libraries
-
compiles straight to Java bytecode so you can use it anywhere you can use Java
1. Groovy Language Specification
1.1. Syntax
This chapter covers the syntax of the Groovy programming language. The grammar of the language derives from the Java grammar, but enhances it with specific constructs for Groovy, and allows certain simplifications.
1.1.1. Comments
Single line comment
Single line comments start with //
and can be found at any position in the line.
The characters following //
, till the end of the line, are considered part of the comment.
// a standalone single line comment
println "hello" // a comment till the end of the line
Multiline comment
A multiline comment starts with /*
and can be found at any position in the line.
The characters following /*
will be considered part of the comment, including new line characters,
up to the first */
closing the comment.
Multiline comments can thus be put at the end of a statement, or even inside a statement.
/* a standalone multiline comment
spanning two lines */
println "hello" /* a multiline comment starting
at the end of a statement */
println 1 /* one */ + 2 /* two */
GroovyDoc comment
Similarly to multiline comments, GroovyDoc comments are multiline, but start with /**
and end with */
.
Lines following the first GroovyDoc comment line can optionally start with a star *
.
Those comments are associated with:
-
type definitions (classes, interfaces, enums, annotations),
-
fields and properties definitions
-
methods definitions
Although the compiler will not complain about GroovyDoc comments not being associated with the above language elements, you should prepend those constructs with the comment right before it.
/**
* A Class description
*/
class Person {
/** the name of the person */
String name
/**
* Creates a greeting method for a certain person.
*
* @param otherPerson the person to greet
* @return ag reeting message
*/
String greet(String otherPerson) {
"Hello ${otherPerson}"
}
}
GroovyDoc follows the same conventions as Java’s own JavaDoc. So you’ll be able to use the same tags as with JavaDoc.
Shebang line
Beside the single line comment, there is a special line comment, often called the shebang line understood by UNIX systems
which allows scripts to be run directly from the command-line, provided you have installed the Groovy distribution
and the groovy
command is available on the PATH
.
#!/usr/bin/env groovy
println "Hello from the shebang line"
The # character must be the first character of the file. Any indentation would yield a compilation error.
|
1.1.2. Keywords
The following list represents all the keywords of the Groovy language:
as |
assert |
break |
case |
catch |
class |
const |
continue |
def |
default |
do |
else |
enum |
extends |
false |
finally |
for |
goto |
if |
implements |
import |
in |
instanceof |
interface |
new |
null |
package |
return |
super |
switch |
this |
throw |
throws |
trait |
true |
try |
while |
1.1.3. Identifiers
Normal identifiers
Identifiers start with a letter, a dollar or an underscore. They cannot start with a number.
A letter can be in the following ranges:
-
a to z (lowercase ascii letter)
-
A to Z (uppercase ascii letter)
-
\u00C0 to \u00D6
-
\u00D8 to \u00F6
-
\u00F8 to \u00FF
-
\u0100 to \uFFFE
Then following characters can contain letters and numbers.
Here are a few examples of valid identifiers (here, variable names):
def name
def item3
def with_underscore
def $dollarStart
But the following ones are invalid identifiers:
def 3tier
def a+b
def a#b
All keywords are also valid identifiers when following a dot:
foo.as
foo.assert
foo.break
foo.case
foo.catch
Quoted identifiers
Quoted identifiers appear after the dot of a dotted expression.
For instance, the name
part of the person.name
expression can be quoted with person."name"
or person.'name’
.
This is particularly interesting when certain identifiers contain illegal characters that are forbidden by the Java Language Specification,
but which are allowed by Groovy when quoted. For example, characters like a dash, a space, an exclamation mark, etc.
def map = [:]
map."an identifier with a space and double quotes" = "ALLOWED"
map.'with-dash-signs-and-single-quotes' = "ALLOWED"
assert map."an identifier with a space and double quotes" == "ALLOWED"
assert map.'with-dash-signs-and-single-quotes' == "ALLOWED"
As we shall see in the following section on strings, Groovy provides different string literals. All kind of strings are actually allowed after the dot:
map.'single quote'
map."double quote"
map.'''triple single quote'''
map."""triple double quote"""
map./slashy string/
map.$/dollar slashy string/$
There’s a difference between plain character strings and Groovy’s GStrings (interpolated strings), as in that the latter case, the interpolated values are inserted in the final string for evaluating the whole identifier:
def firstname = "Homer"
map."Simson-${firstname}" = "Homer Simson"
assert map.'Simson-Homer' == "Homer Simson"
1.1.4. Strings
Text literals are represented in the form of chain of characters called strings.
Groovy lets you instantiate java.lang.String
objects, as well as GStrings (groovy.lang.GString
)
which are also called interpolated strings in other programming languages.
Single quoted string
Single quoted strings are a series of characters surrounded by single quotes:
'a single quoted string'
Single quoted strings are plain java.lang.String and don’t support interpolation.
|
String concatenation
All the Groovy strings can be concatenated with the +
operator:
assert 'ab' == 'a' + 'b'
Triple single quoted string
Triple single quoted strings are a series of characters surrounded by triplets of single quotes:
'''a triple single quoted string'''
Triple single quoted strings are plain java.lang.String and don’t support interpolation.
|
Triple single quoted strings are multiline. You can span the content of the string across line boundaries without the need to split the string in several pieces, without contatenation or newline escape characters:
def aMultilineString = '''line one
line two
line three'''
If your code is indented, for example in the body of the method of a class, your string will contain the whitespace of the indentation.
The Groovy Development Kit contains methods for stripping out the indentation with the String#stripIndent()
method,
and with the String#stripMargin()
method that takes a delimiter character to identify the text to remove from the beginning of a string.
When creating a string as follows:
def startingAndEndingWithANewline = '''
line one
line two
line three
'''
You will notice that the resulting string contains a newline character as first character. It is possible to strip that character by escaping the newline with a backslash:
def strippedFirstNewline = '''\
line one
line two
line three
'''
assert !strippedFirstNewline.startsWith('\n')
Escaping special characters
You can escape single quotes with the the backslash character to avoid terminating the string literal:
'an escaped single quote: \' needs a backslash'
And you can escape the escape character itself with a double backslash:
'an escaped escape character: \\ needs a double backslash'
Some special characters also use the backslash as escape character:
Escape sequence | Character |
---|---|
\t |
tabulation |
\b |
backspace |
\n |
newline |
\r |
carriage return |
\f |
formfeed |
\\ |
backslash |
\' |
single quote (for single quoted and triple single quoted strings) |
\" |
double quote (for double quoted and triple double quoted strings) |
Double quoted string
Double quoted strings are a series of characters surrounded by double quotes:
"a double quoted string"
Double quoted strings are plain java.lang.String if there’s no interpolated expression,
but are groovy.lang.GString instances if interpolation is present.
|
To escape a double quote, you can use the backslash character: "A double quote: \"" .
|
String interpolation
Any Groovy expression can be interpolated in all string literals, apart from single and triple single quoted strings.
Interpolation is the act of replacing a placeholder in the string with its value upon evaluation of the string.
The placeholder expressions are surrounded by ${}
or prefixed with $
for dotted expressions.
The expression value inside the placeholder is evaluated to its string representation when the GString is passed to a method taking a String as argument by calling toString()
on that expression.
Here, we have a string with a placeholder referencing a local variable:
def name = 'Guillaume' // a plain string
def greeting = "Hello ${name}"
assert greeting.toString() == 'Hello Guillaume'
But any Groovy expression is valid, as we can see in this example with an arithmetic expression:
def sum = "The sum of 2 and 3 equals ${2 + 3}"
assert sum.toString() == 'The sum of 2 and 3 equals 5'
Not only expressions are actually allowed in between the ${} placeholder. Statements are also allowed, but a statement’s value is just null .
So if several statements are inserted in that placeholder, the last one should somehow return a meaningful value to be inserted.
For instance, "The sum of 1 and 2 is equal to ${def a = 1; def b = 2; a + b}" is supported and works as expected but a good practice is usually to stick to simple expressions inside GString placeholders.
|
In addition to ${}
placeholders, we can also use a lone $
sign prefixing a dotted expression:
def person = [name: 'Guillaume', age: 36]
assert "$person.name is $person.age years old" == 'Guillaume is 36 years old'
But only dotted expressions of the form a.b
, a.b.c
, etc, are valid, but expressions that would contain parentheses like method calls, curly braces for closures, or arithmetic operators would be invalid.
Given the following variable definition of a number:
def number = 3.14
The following statement will throw a groovy.lang.MissingPropertyException
because Groovy believes you’re trying to access the toString
property of that number, which doesn’t exist:
shouldFail(MissingPropertyException) {
println "$number.toString()"
}
You can think of "$number.toString()" as being interpreted by the parser as "${number.toString}()" .
|
If you need to escape the $
or ${}
placeholders in a GString so they appear as is without interpolation,
you just need to use a \
backslash character to escape the dollar sign:
assert '${name}' == "\${name}"
Special case of interpolating closure expressions
So far, we’ve seen we could interpolate arbitrary expressions inside the ${}
placeholder, but there is a special case and notation for closure expressions. When the placeholder contains an arrow, ${→}
, the expression is actually a closure expression — you can think of it as a closure with a dollar prepended in front of it:
def sParameterLessClosure = "1 + 2 == ${-> 3}" (1)
assert sParameterLessClosure == '1 + 2 == 3'
def sOneParamClosure = "1 + 2 == ${ w -> w << 3}" (2)
assert sOneParamClosure == '1 + 2 == 3'
1 | The closure is a parameterless closure which doesn’t take arguments. |
2 | Here, the closure takes a single java.io.StringWriter argument, to which you can append content with the << leftShift operator.
In either case, both placeholders are embedded closures. |
In appearance, it looks like a more verbose way of defining expressions to be interpolated, but closure have an interesting advantage over mere expressions: lazy evaluation.
Let’s consider the following sample:
def number = 1 (1)
def eagerGString = "value == ${number}"
def lazyGString = "value == ${ -> number }"
assert eagerGString == "value == 1" (2)
assert lazyGString == "value == 1" (3)
number = 2 (4)
assert eagerGString == "value == 1" (5)
assert lazyGString == "value == 2" (6)
1 | We define a number variable containing 1 that we then interpolate within two GStrings,
as an expression in eagerGString and as a closure in lazyGString . |
2 | We expect the resulting string to contain the same string value of 1 for eagerGString . |
3 | Similarily for lazyGString |
4 | Then we change the value of the variable to a new number |
5 | With a plain interpolated expression, the value was actually bound at the time of creation of the GString. |
6 | But with a closure expression, the closure is called upon each coercion of the GString into String, resulting in an updated string containing the new number value. |
An embedded closure expression taking more than one parameter will generate an exception at runtime. Only closures with zero or one paramaters are allowed. |
Inteoperability with Java
When a method (whether implemented in Java or Groovy) expects a java.lang.String
,
but we pass a groovy.lang.GString
instance,
the toString()
method of the GString is automatically and transparently called.
String takeString(String message) { (4)
assert message instanceof String (5)
return message
}
def message = "The message is ${'hello'}" (1)
assert message instanceof GString (2)
def result = takeString(message) (3)
assert result instanceof String
assert result == 'The message is hello'
1 | We create a GString variable |
2 | We double check it’s an instance of the GString |
3 | We then pass that GString to a method taking a String as parameter |
4 | The signature of the takeString() method explicitly says its sole parameter is a String |
5 | We also verify that the parameter is indeed a String and not a GString. |
GString and String hashCodes
Although interpolated strings can be used in lieu of plain Java strings, they differ with strings in a particular way: their hashCodes are different. Plain Java strings are immutable, whereas the resulting String representation of a GString can vary, depending on its interpolated values. Even for the same resulting string, GStrings and Strings don’t have the same hashCode.
assert "one: ${1}".hashCode() != "one: 1".hashCode()
GString and Strings having different hashCode values, using GString as Map keys should be avoided, especially if we try to retrieve an associated value with a String instead of a GString.
def key = "a"
def m = ["${key}": "letter ${key}"] (1)
assert m["a"] == null (2)
1 | The map is created with an initial pair whose key is a GString |
2 | When we try to fetch the value with a String key, we will not find it, as Strings and GString have different hashCode values |
Triple double quoted string
Triple double quoted strings behave like double quoted strings, with the addition that they are multiline, like the triple single quoted strings.
def name = 'Groovy'
def template = """
Dear Mr ${name},
You're the winner of the lottery!
Yours sincerly,
Dave
"""
assert template.toString().contains('Groovy')
Neither double quotes nor single quotes need be escaped in triple double quoted strings. |
Slashy string
Beyond the usual quoted strings, Groovy offers slashy strings, which use /
as delimiters.
Slashy strings are particularly useful for defining regular expressions and patterns,
as there is no need to escape backslashes.
Example of a slashy string:
def fooPattern = /.*foo.*/
assert fooPattern == '.*foo.*'
Only forward slashes need to be escaped with a backslash:
def escapeSlash = /The character \/ is a forward slash/
assert escapeSlash == 'The character / is a forward slash'
Slashy strings are multiline:
def multilineSlashy = /one
two
three/
assert multilineSlashy.contains('\n')
Slashy strings can also be interpolated (ie. a GString):
def color = 'blue'
def interpolatedSlashy = /a ${color} car/
assert interpolatedSlashy == 'a blue car'
There are a few gotchas to be aware of.
An empty slashy string cannot be represented with a double forward slash, as it’s understood by the Groovy parser as a line comment. That’s why the following assert would actually not compile as it would look like a non-terminated statement:
assert '' == //
Dollar slashy string
Dollar slashy strings are multiline GStrings delimited with an opening $/
and and a closing /$
.
The escaping character is the dollar sign, and it can escape another dollar, or a forward slash.
But both dollar and forward slashes don’t need to be escaped, except to escape the dollar of a string subsequence that would start like a GString placeholder sequence, or if you need to escape a sequence that would start like a closing dollar slashy string delimiter.
Here’s an example:
def name = "Guillaume"
def date = "April, 1st"
def dollarSlashy = $/
Hello $name,
today we're ${date}.
$ dollar sign
$$ escaped dollar sign
\ backslash
/ forward slash
$/ escaped forward slash
$/$ escaped dollar slashy string delimiter
/$
assert [
'Guillaume',
'April, 1st',
'$ dollar sign',
'$ escaped dollar sign',
'\\ backslash',
'/ forward slash',
'$/ escaped forward slash',
'/$ escaped dollar slashy string delimiter'
].each { dollarSlashy.contains(it) }
String summary table
String name |
String syntax |
Interpolated |
Multiline |
Escape character |
Single quoted |
|
|
||
Triple single quoted |
|
|
||
Double quoted |
|
|
||
Triple double quoted |
|
|
||
Slashy |
|
|
||
Dollar slashy |
|
|
Characters
Unlike Java, Groovy doesn’t have an explicit character literal. However, you can be explicit about making a Groovy string an actual character, by three different means:
char c1 = 'A' (1)
assert c1 instanceof Character
def c2 = 'B' as char (2)
assert c2 instanceof Character
def c3 = (char)'C' (3)
assert c3 instanceof Character
1 | by being explicit when declaring a variable holding the character by specifying the char type |
2 | by using type coercion with the as operator |
3 | by using a cast to char operation |
The first option 1 is interesting when the character is held in a variable, while the other two (2 and 3) are more interesting when a char value must be passed as argument of a method call. |
1.1.5. Numbers
Groovy supports different kinds of integral literals and decimal literals, backed by the usual Number
types of Java.
Integral literals
The integral literal types are the same as in Java:
-
byte
-
char
-
short
-
int
-
long
-
java.lang.BigInteger
You can create integral numbers of those types with the following declarations:
// primitive types
byte b = 1
char c = 2
short s = 3
int i = 4
long l = 5
// infinite precision
BigInteger bi = 6
If you use optional typing by using the def
keyword, the type of the integral number will vary:
it’ll adapt to the capacity of the type that can hold that number.
For positive numbers:
def a = 1
assert a instanceof Integer
// Integer.MAX_VALUE
def b = 2147483647
assert b instanceof Integer
// Integer.MAX_VALUE + 1
def c = 2147483648
assert c instanceof Long
// Long.MAX_VALUE
def d = 9223372036854775807
assert d instanceof Long
// Long.MAX_VALUE + 1
def e = 9223372036854775808
assert e instanceof BigInteger
As well as for negative numbers:
def na = -1
assert na instanceof Integer
// Integer.MIN_VALUE
def nb = -2147483648
assert nb instanceof Integer
// Integer.MIN_VALUE - 1
def nc = -2147483649
assert nc instanceof Long
// Long.MIN_VALUE
def nd = -9223372036854775808
assert nd instanceof Long
// Long.MIN_VALUE - 1
def ne = -9223372036854775809
assert ne instanceof BigInteger
Alternative non-base 10 representations
In Java 6 and before, as well as in Groovy, numbers could be represented in decimal, octal and hexadecimal bases, and with Java 7 and Groovy 2, you can use a binary notation with the 0b
prefix:
int xInt = 0b10101111
assert xInt == 175
short xShort = 0b11001001
assert xShort == 201 as short
byte xByte = 0b11
assert xByte == 3 as byte
long xLong = 0b101101101101
assert xLong == 2925l
BigInteger xBigInteger = 0b111100100001
assert xBigInteger == 3873g
int xNegativeInt = -0b10101111
assert xNegativeInt == -175
Octal numbers are specified in the typical format of 0
followed by octal digits.
int xInt = 077
assert xInt == 63
short xShort = 011
assert xShort == 9 as short
byte xByte = 032
assert xByte == 26 as byte
long xLong = 0246
assert xLong == 166l
BigInteger xBigInteger = 01111
assert xBigInteger == 585g
int xNegativeInt = -077
assert xNegativeInt == -63
Hexadecimal numbers are specified in the typical format of 0x
followed by hex digits.
int xInt = 0x77
assert xInt == 119
short xShort = 0xaa
assert xShort == 170 as short
byte xByte = 0x3a
assert xByte == 58 as byte
long xLong = 0xffff
assert xLong == 65535l
BigInteger xBigInteger = 0xaaaa
assert xBigInteger == 43690g
Double xDouble = new Double('0x1.0p0')
assert xDouble == 1.0d
int xNegativeInt = -0x77
assert xNegativeInt == -119
Decimal literals
The decimal literal types are the same as in Java:
-
float
-
double
-
java.lang.BigDecimal
You can create decimal numbers of those types with the following declarations:
// primitive types
float f = 1.234
double d = 2.345
// infinite precision
BigDecimal bd = 3.456
Decimals can use exponents, with the e
or E
exponent letter, followed by an optional sign,
and a integral number representing the exponent:
assert 1e3 == 1_000.0
assert 2E4 == 20_000.0
assert 3e+1 == 30.0
assert 4E-2 == 0.04
assert 5e-1 == 0.5
Conveniently for exact decimal number calculations, Groovy choses java.lang.BigDecimal
as its decimal number type.
In addition, both float
and double
are supported, but require an explicit type declaration, type coercion or suffix.
Even if BigDecimal
is the default for decimal numbers, such literals are accepted in methods or closures taking float
or double
as parameter types.
Decimal numbers can’t be represented using a binary, octal or hexadecimal representation. |
Underscore in literals
When writing long literal numbers, it’s harder on the eye to figure out how some numbers are grouped together, for example with groups of thousands, of words, etc. By allowing you to place underscore in number literals, it’s easier to spot those groups:
long creditCardNumber = 1234_5678_9012_3456L
long socialSecurityNumbers = 999_99_9999L
double monetaryAmount = 12_345_132.12
long hexBytes = 0xFF_EC_DE_5E
long hexWords = 0xFFEC_DE5E
long maxLong = 0x7fff_ffff_ffff_ffffL
long alsoMaxLong = 9_223_372_036_854_775_807L
long bytes = 0b11010010_01101001_10010100_10010010
Number type suffixes
We can force a number (including binary, octals and hexadecimals) to have a specific type by giving a suffix (see table bellow), either uppercase or lowercase.
Type | Suffix |
---|---|
BigInteger |
|
Long |
|
Integer |
|
BigDecimal |
|
Double |
|
Float |
|
Examples:
assert 42I == new Integer('42')
assert 42i == new Integer('42') // lowercase i more readable
assert 123L == new Long("123") // uppercase L more readable
assert 2147483648 == new Long('2147483648') // Long type used, value too large for an Integer
assert 456G == new BigInteger('456')
assert 456g == new BigInteger('456')
assert 123.45 == new BigDecimal('123.45') // default BigDecimal type used
assert 1.200065D == new Double('1.200065')
assert 1.234F == new Float('1.234')
assert 1.23E23D == new Double('1.23E23')
assert 0b1111L.class == Long // binary
assert 0xFFi.class == Integer // hexadecimal
assert 034G.class == BigInteger // octal
Math operations
Although operators are covered later on, it’s important to discuss the behavior of math operations and what their resulting types are.
Division and power binary operations aside (covered below),
-
binary operations between
byte
,char
,short
andint
result inint
-
binary operations involving
long
withbyte
,char
,short
andint
result inlong
-
binary operations involving
BigInteger
and any other integral type result inBigInteger
-
binary operations between
float
,double
andBigDecimal
result indouble
-
binary operations between two
BigDecimal
result inBigDecimal
The following table summarizes those rules:
byte | char | short | int | long | BigInteger | float | double | BigDecimal | |
---|---|---|---|---|---|---|---|---|---|
byte |
int |
int |
int |
int |
long |
BigInteger |
double |
double |
double |
char |
int |
int |
int |
long |
BigInteger |
double |
double |
double |
|
short |
int |
int |
long |
BigInteger |
double |
double |
double |
||
int |
int |
long |
BigInteger |
double |
double |
double |
|||
long |
long |
BigInteger |
double |
double |
double |
||||
BigInteger |
BigInteger |
double |
double |
double |
|||||
float |
double |
double |
double |
||||||
double |
double |
double |
|||||||
BigDecimal |
BigDecimal |
Thanks Groovy’s operator overloading, the usual arithmetic operators work as well with BigInteger and BigDecimal ,
unlike in Java where you have to use explict methods for operating on those numbers.
|
The case of the division operator
The division operators /
(and /=
for division and assignment) produce a double
result
if either operand is a float
or double
, and a BigDecimal
result otherwise
(when both operands are any combination of an integral type short
, char
, byte
, int
, long
,
BigInteger
or BigDecimal
).
BigDecimal
division is performed with the divide()
method if the division is exact
(ie. yielding a result that can be represented within the bounds of the same precision and scale),
or using a MathContext
with a precision
of the maximum of the two operands’ precision plus an extra precision of 10,
and a scale
of the maximum of 10 and the maximum of the operands’ scale.
For integer division like in Java, you should use the intdiv() method,
as Groovy doesn’t provide a dedicated integer division operator symbol.
|
The case of the power operator
The power operation is represented by the **
operator, with two parameters: the base and the exponent.
The result of the power operation depends on its operands, and the result of the operation
(in particular if the result can be represented as an integral value).
The following rules are used by Groovy’s power operation to determine the resulting type:
-
If the exponent is a decimal value
-
if the result can be represented as an
Integer
, then return anInteger
-
else if the result can be represented as a
Long
, then return aLong
-
otherwise return a
Double
-
-
If the exponent is an integral value
-
if the exponent is strictly negative, then return an
Integer
,Long
orDouble
if the result value fits in that type -
if the exponent is positive or zero
-
if the base is a
BigDecimal
, then return aBigDecimal
result value -
if the base is a
BigInteger
, then return aBigInteger
result value -
if the base is an
Integer
, then return anInteger
if the result value fits in it, otherwise aBigInteger
-
if the base is a
Long
, then return aLong
if the result value fits in it, otherwise aBigInteger
-
-
We can illustrate those rules with a few examples:
// base and exponent are ints and the result can be represented by an Integer
assert 2 ** 3 instanceof Integer // 8
assert 10 ** 9 instanceof Integer // 1_000_000_000
// the base is a long, so fit the result in a Long
// (although it could have fit in an Integer)
assert 5L ** 2 instanceof Long // 25
// the result can't be represented as an Integer or Long, so return a BigInteger
assert 100 ** 10 instanceof BigInteger // 10e20
assert 1234 ** 123 instanceof BigInteger // 170515806212727042875...
// the base is a BigDecimal and the exponent a negative int
// but the result can be represented as an Integer
assert 0.5 ** -2 instanceof Integer // 4
// the base is an int, and the exponent a negative float
// but again, the result can be represented as an Integer
assert 1 ** -0.3f instanceof Integer // 1
// the base is an int, and the exponent a negative int
// but the result will be calculated as a Double
// (both base and exponent are actually converted to doubles)
assert 10 ** -1 instanceof Double // 0.1
// the base is a BigDecimal, and the exponent is an int, so return a BigDecimal
assert 1.2 ** 10 instanceof BigDecimal // 6.1917364224
// the base is a float or double, and the exponent is an int
// but the result can only be represented as a Double value
assert 3.4f ** 5 instanceof Double // 454.35430372146965
assert 5.6d ** 2 instanceof Double // 31.359999999999996
// the exponent is a decimal value
// and the result can only be represented as a Double value
assert 7.8 ** 1.9 instanceof Double // 49.542708423868476
assert 2 ** 0.1f instanceof Double // 1.0717734636432956
1.1.6. Booleans
Boolean is a special data type that is used to represent truth values: true
and false
.
Use this data type for simple flags that track true/false conditions.
Boolean values can be stored in variables, assigned into fields, just like any other data type:
def myBooleanVariable = true
boolean untypedBooleanVar = false
booleanField = true
true
and false
are the only two primitive boolean values.
But more complex boolean expressions can be represented using logical operators.
In addition, Groovy has special rules (often referred to as Groovy Truth) for coercing non-boolean objects to a boolean value.
1.1.7. Lists
Groovy uses a comma-separated list of values, surrounded by square brackets, to denote lists.
Groovy lists are plain JDK java.util.List
, as Groovy doesn’t define its own collection classes.
The concrete list implementation used when defining list literals are java.util.ArrayList
by default,
unless you decide to specify otherwise, as we shall see later on.
def numbers = [1, 2, 3] (1)
assert numbers instanceof List (2)
assert numbers.size() == 3 (3)
1 | We define a list numbers delimited by commas and surrounded by square brackets, and we assign that list into a variable |
2 | The list is an instance of Java’s java.util.List interface |
3 | The size of the list can be queried with the size() method, and shows our list contains 3 elements |
In the above example, we used a homogeneous list, but you can also create lists containing values of heterogeneous types:
def heterogeneous = [1, "a", true] (1)
1 | Our list here contains a number, a string and a boolean value |
We mentioned that by default, list literals are actually instances of java.util.ArrayList
,
but it is possible to use a different backing type for our lists,
thanks to using type coercion with the as
operator, or with explicit type declaration for your variables:
def arrayList = [1, 2, 3]
assert arrayList instanceof java.util.ArrayList
def linkedList = [2, 3, 4] as LinkedList (1)
assert linkedList instanceof java.util.LinkedList
LinkedList otherLinked = [3, 4, 5] (2)
assert otherLinked instanceof java.util.LinkedList
1 | We use coercion with the as operator to explicitly request a java.util.LinkedList implementation |
2 | We can say that the variable holding the list literal is of type java.util.LinkedList |
You can access elements of the list with the []
subscript operator (both for reading and setting values)
with positive indices or negative indices to access elements from the end of the list, as well as with ranges,
and use the <<
leftShift operator to append elements to a list:
def letters = ['a', 'b', 'c', 'd']
assert letters[0] == 'a' (1)
assert letters[1] == 'b'
assert letters[-1] == 'd' (2)
assert letters[-2] == 'c'
letters[2] = 'C' (3)
assert letters[2] == 'C'
letters << 'e' (4)
assert letters[ 4] == 'e'
assert letters[-1] == 'e'
assert letters[1, 3] == ['b', 'd'] (5)
assert letters[2..4] == ['C', 'd', 'e'] (6)
1 | Access the first element of the list (zeroth-based counting) |
2 | Access the last element of the list with a negative index: -1 is the first element from the end of the list |
3 | Use an assignment to set a new value for the third element of the list |
4 | Use the << leftShift operator to append an element at the end of the list |
5 | Access two elements at once, returning a new list containing those two elements |
6 | Use a range to access a range of values from the list, from a start to an end element position |
As lists can be heterogeneous in nature, lists can also contain other lists to create multi-dimensional lists:
def multi = [[0, 1], [2, 3]] (1)
assert multi[1][0] == 2 (2)
1 | Define a list of list of numbers |
2 | Access the second element of the top-most list, and the first element of the inner list |
1.1.8. Arrays
Groovy reuses the list notation for arrays, but to make such literals arrays, you need to explicitely define the type of the array through coercion or type declaration.
String[] arrStr = ['Ananas', 'Banana', 'Kiwi'] (1)
assert arrStr instanceof String[] (2)
assert !(arrStr instanceof List) (3)
def numArr = [1, 2, 3] as int[] (4)
assert numArr instanceof int[] (5)
assert numArr.size() == 3
1 | Define an array of strings using explicit variable type declaration |
2 | Assert that we created an array of strings |
3 | Create an array of ints with the as operator |
4 | Assert that we created an array of primitive ints |
You can also create multi-dimensional arrays:
def matrix3 = new Integer[3][3] (1)
assert matrix3.size() == 3
Integer[][] matrix2 (2)
matrix2 = [[1, 2], [3, 4]]
assert matrix2 instanceof Integer[][]
1 | You can define the bounds of a new array |
2 | Or declare an array without specifying its bounds |
Access to elements of an array follows the same notation as for lists:
String[] names = ['Cédric', 'Guillaume', 'Jochen', 'Paul']
assert names[0] == 'Cédric' (1)
names[2] = 'Blackdrag' (2)
assert names[2] == 'Blackdrag'
1 | Retrieve the first element of the array |
2 | Set the value of the third element of the array to a new value |
Java’s array initializer notation is not supported by Groovy, as the curly braces can be misinterpreted with the notation of Groovy closures. |
1.1.9. Maps
Sometimes called dictionaries or associative arrays in other languages, Groovy features maps. Maps associate keys to values, separating keys and values with colons, and each key/value pairs with commas, and the whole keys and values surrounded by square brackets.
def colors = [red: '#FF0000', green: '#00FF00', blue: '#0000FF'] (1)
assert colors['red'] == '#FF0000' (2)
assert colors.green == '#00FF00' (3)
colors['pink'] = '#FF00FF' (4)
colors.yellow = '#FFFF00' (5)
assert colors.pink == '#FF00FF'
assert colors['yellow'] == '#FFFF00'
assert colors instanceof java.util.LinkedHashMap
1 | We define a map of string color names, associated with their hexadecimal-coded html colors |
2 | We use the subscript notation to check the content associated with the red key |
3 | We can also use the property notation to assert the color green’s hexadecimal representation |
4 | Similarily, we can use the subscript notation to add a new key/value pair |
5 | Or the property notation, to add the yellow color |
When using names for the keys, we actually define string keys in the map. |
Groovy creates maps that are actually instances of java.util.LinkedHashMap .
|
If you try to access a key which is not present in the map:
assert colors.unknown == null
You will retrieve a null
result.
In the examples above, we used string keys, but you can also use values of other types as keys:
def numbers = [1: 'one', 2: 'two']
assert numbers[1] == 'one'
Here, we used numbers as keys, as numbers can unambiguously be recognized as numbers, so Groovy will not create a string key like in our previous examples. But consider the case you want to pass a variable in lieu of the key, to have the value of that variable become the key:
def key = 'name'
def person = [key: 'Guillaume'] (1)
assert !person.containsKey('name') (2)
assert person.containsKey('key') (3)
1 | The key associated with the 'Guillaume’ name will actually be the "key" string, not the value associated with the key variable |
2 | The map doesn’t contain the 'name’ key |
3 | Instead, the map contains a 'key’ key |
You can also pass quoted strings as well as keys: ["name": "Guillaume"] .
This is mandatory if your key string isn’t a valid identifier,
for example if you wanted to create a string key containing a hash like in: ["street-name": "Main street"] .
|
When you need to pass variable values as keys in your map definitions, you must surround the variable or expression with parentheses:
person = [(key): 'Guillaume'] (1)
assert person.containsKey('name') (2)
assert !person.containsKey('key') (3)
1 | This time, we surround the key variable with parentheses, to instruct the parser we are passing a variable rather than defining a string key |
2 | The map does contain the name key |
3 | But the map doesn’t contain the key key as before |
1.2. Operators
This chapter covers the operators of the Groovy programming language.
1.2.1. Arithmetic operators
Groovy supports the usual familiar arithmetic operators you find in mathematics and in other programming languages like Java. All the Java arithmetic operators are supported. Let’s go through them in the following examples.
Normal arithmetic operators
The following binary arithmetic operators are available in Groovy:
Operator | Purpose | Remarks |
---|---|---|
|
addition |
|
|
subtraction |
|
|
multiplication |
|
|
division |
Use |
|
modulo |
|
|
power |
See the section about the power operation for more information on the return type of the operation. |
Here are a few examples of usage of those operators:
assert 1 + 2 == 3
assert 4 - 3 == 1
assert 3 * 5 == 15
assert 3 / 2 == 1.5
assert 10 % 3 == 1
assert 2 ** 3 == 8
Unary operators
The +
and -
operators are also available as unary operators:
assert +3 == 3
assert -4 == 0 - 4
assert -(-1) == 1 (1)
1 | Note the usage of parentheses to surround an expression to apply the unary minus to that surrounded expression. |
In terms of unary arithmetics operators, the ++
(increment) and --
(decrement) operators are available,
both in prefix and postfix notation:
def a = 2
def b = a++ * 3 (1)
assert a == 3 && b == 6
def c = 3
def d = c-- * 2 (2)
assert c == 2 && d == 6
def e = 1
def f = ++e + 3 (3)
assert e == 2 && f == 5
def g = 4
def h = --g + 1 (4)
assert g == 3 && h == 4
1 | The postfix increment will increment a after the expression has been evaluated and assigned into b |
2 | The postfix decrement will decrement c after the expression has been evaluated and assigned into d |
3 | The prefix increment will increment e before the expression is evaluated and assigned into f |
4 | The prefix decrement will decrement g before the expression is evaluated and assigned into h |
Assignment arithmetic operators
From the binary arithmetic operators we have seen above, certain of them are also available in an assignment form:
-
+=
-
-=
-
*=
-
/=
-
%=
Let’s see them in action:
def a = 4
a += 3
assert a == 7
def b = 5
b -= 3
assert b == 2
def c = 5
c *= 3
assert c == 15
def d = 10
d /= 2
assert d == 5
def e = 10
e %= 3
assert e == 1
1.2.2. Relational operators
Relational operators allow comparisons between objects, to know if two objects are the same or different, or if one is greater than, less than, or equal to the other.
The following operators are available:
Operator | Purpose |
---|---|
|
equal |
|
different |
|
less than |
|
less than or equal |
|
greater than |
|
greater than or equal |
Here are some examples of simple number comparisons using these operators:
assert 1 + 2 == 3
assert 3 != 4
assert -2 < 3
assert 2 <= 2
assert 3 <= 4
assert 5 > 1
assert 5 >= -2
1.2.3. Logical operators
Groovy offers three logical operators for boolean expressions:
-
&&
: logical "and" -
||
: logical "or" -
!
: logical "not"
Let’s illustrate them with the following examples:
assert !false (1)
assert true && true (2)
assert true || false (3)
1 | "not" false is true |
2 | true "and" true is true |
3 | true "or" false is true |
Precedence
The logical "not" has a higher priority than the logical "and".
assert (!false && false) == false (1)
1 | Here, the assertion is true (as the expression in parentheses is false), because "not" has a higher precedence than "and", so it only applies to the first "false" term; otherwise, it would have applied to the result of the "and", turned it into true, and the assertion would have failed |
The logical "and" has a higher priority than the logical "or".
assert true || true && false (1)
1 | Here, the assertion is true, because "and" has a higher precedence than "or", therefore the "or" is executed last and returns true, having one true argument; otherwise, the "and" would have executed last and returned false, having one false argument, and the assertion would have failed |
Short-circuiting
The logical ||
operator supports short-circuiting: if the left operand is true, it knows that the result will be true in any case, so it won’t evaluate the right operand.
The right operand will be evaluated only if the left operand is false.
Likewise for the logical &&
operator: if the left operand is false, it knows that the result will be false in any case, so it won’t evaluate the right operand.
The right operand will be evaluated only if the left operand is true.
boolean checkIfCalled() { (1)
called = true
}
called = false
true || checkIfCalled()
assert !called (2)
called = false
false || checkIfCalled()
assert called (3)
called = false
false && checkIfCalled()
assert !called (4)
called = false
true && checkIfCalled()
assert called (5)
1 | We create a function that sets the called flag to true whenever it’s called |
2 | In the first case, after resetting the called flag, we confirm that if the left operand to || is true, the function is not called, as || short-circuits the evaluation of the right operand |
3 | In the second case, the left operand is false and so the function is called, as indicated by the fact our flag is now true |
4 | Likewise for && , we confirm that the function is not called with a false left operand |
5 | But the function is called with a true left operand |
1.2.4. Bitwise operators
Groovy offers 4 bitwise operators:
-
&
: bitwise "and" -
|
: bitwise "or" -
^
: bitwise "xor" (exclusive "or") -
~
: bitwise negation
Bitwise operators can be applied on a byte
or an int
and return an int
:
int a = 0b00101010
assert a==42
int b = 0b00001000
assert b==8
assert (a & a) == a (1)
assert (a & b) == b (2)
assert (a | a) == a (3)
assert (a | b) == a (4)
int mask = 0b11111111 (5)
assert ((a ^ a) & mask) == 0b00000000 (6)
assert ((a ^ b) & mask) == 0b00100010 (7)
assert ((~a) & mask) == 0b11010101 (8)
1 | bitwise and |
2 | bitwise and returns common bits |
3 | bitwise or |
4 | bitwise or returns all 1 bits |
5 | setting a mask to check only the last 8 bits |
6 | bitwise exclusive or on self returns 0 |
7 | bitwise exclusive or |
8 | bitwise negation |
It’s worth noting that the internal representation of primitive types follow the Java Language Specification. In particular, primitive types are signed, meaning that for a bitwise negation, it is always good to use a mask to retrieve only the necessary bits.
In Groovy, bitwise operators have the particularity of being overloadable, meaning that you can define the behavior of those operators for any kind of object.
1.2.5. Conditional operators
Not operator
The "not" operator is represented with an exclamation mark (!
) and inverts the result of the underlying boolean expression. In
particular, it is possible to combine the not
operator with the Groovy truth:
assert (!true) == false (1)
assert (!'foo') == false (2)
assert (!'') == true (3)
1 | the negation of true is false |
2 | foo is a non empty string, evaluating to true , so negation returns false |
3 | '' is an empty string, evaluating to false , so negation returns true |
Ternary operator
The ternary operator is a shortcut expression that is equivalent to an if/else branch assigning some value to a variable.
Instead of:
if (string!=null && string.length()>0) {
result = 'Found'
} else {
result = 'Not found'
}
You can write:
result = (string!=null && string.length()>0) ? 'Found' : 'Not found'
The ternary operator is also compatible with the Groovy truth, so you can make it even simpler:
result = string ? 'Found' : 'Not found'
Elvis operator
The "Elvis operator" is a shortening of the ternary operator. One instance of where this is handy is for returning
a sensible default value if an expression resolves to false
or null
. A simple example might look like this:
displayName = user.name ? user.name : 'Anonymous' (1)
displayName = user.name ?: 'Anonymous' (2)
1 | with the ternary operator, you have to repeat the value you want to assign |
2 | with the Elvis operator, the value which is tested is used if it is not false or null |
Usage of the Elvis operator reduces the verbosity of your code and reduces the risks of errors in case of refactorings, by removing the need to duplicate the expression which is tested in both the condition and the positive return value.
1.2.6. Object operators
Safe navigation operator
The Safe Navigation operator is used to avoid a NullPointerException
. Typically when you have a reference to an object
you might need to verify that it is not null
before accessing methods or properties of the object. To avoid this, the safe
navigation operator will simply return null
instead of throwing an exception, like so:
def person = Person.find { it.id == 123 } (1)
def name = person?.name (2)
assert name == null (3)
1 | find will return a null instance |
2 | use of the null-safe operator prevents from a NullPointerException |
3 | result is null |
Direct field access operator
Normally in Groovy, when you write code like this:
class User {
public final String name (1)
User(String name) { this.name = name}
String getName() { "Name: $name" } (2)
}
def user = new User('Bob')
assert user.name == 'Name: Bob' (3)
1 | public field name |
2 | a getter for name that returns a custom string |
3 | calls the getter |
The user.name
call triggers a call to the property of the same name, that is to say, here, to the getter for name
. If
you want to retrieve the field instead of calling the getter, you can use the direct field access operator:
assert user.@name == 'Bob' (1)
1 | use of .@ forces usage of the field instead of the getter |
Method pointer operator
The method pointer operator (.&
) call be used to store a reference to a method in a variable, in order to call it
later:
def str = 'example of method reference' (1)
def fun = str.&toUpperCase (2)
def upper = fun() (3)
assert upper == str.toUpperCase() (4)
1 | the str variable contains a String |
2 | we store a reference to the toUpperCase method on the str instance inside a variable named fun |
3 | fun can be called like a regular method |
4 | we can check that the result is the same as if we had called it directly on str |
There are multiple advantages in using method pointers. First of all, the type of such a method pointer is
a groovy.lang.Closure
, so it can be used in any place a closure would be used. In particular, it is suitable to
convert an existing method for the needs of the strategy pattern:
def transform(List elements, Closure action) { (1)
def result = []
elements.each {
result << action(it)
}
result
}
String describe(Person p) { (2)
"$p.name is $p.age"
}
def action = this.&describe (3)
def list = [
new Person(name: 'Bob', age: 42),
new Person(name: 'Julia', age: 35)] (4)
assert transform(list, action) == ['Bob is 42', 'Julia is 35'] (5)
1 | the transform method takes each element of the list and calls the action closure on them, returning a new list |
2 | we define a function that takes a Person a returns a String |
3 | we create a method pointer on that function |
4 | we create the list of elements we want to collect the descriptors |
5 | the method pointer can be used where a Closure was expected |
Method pointers are bound by the receiver and a method name. Arguments are resolved at runtime, meaning that if you have multiple methods with the same name, the syntax is not different, only resolution of the appropriate method to be called will be done at runtime:
def doSomething(String str) { str.toUpperCase() } (1)
def doSomething(Integer x) { 2*x } (2)
def reference = this.&doSomething (3)
assert reference('foo') == 'FOO' (4)
assert reference(123) == 246 (5)
1 | define an overloaded doSomething method accepting a String as an argument |
2 | define an overloaded doSomething method accepting an Integer as an argument |
3 | create a single method pointer on doSomething , without specifying argument types |
4 | using the method pointer with a String calls the String version of doSomething |
5 | using the method pointer with an Integer calls the Integer version of doSomething |
1.2.7. Regular expression operators
Pattern operator
The pattern operator (~
) provides a simple way to create a java.util.regex.Pattern
instance:
def p = ~/foo/
assert p instanceof Pattern
while in general, you find the pattern operator with an expression in a slashy-string, it can be used with any kind of
String
in Groovy:
p = ~'foo' (1)
p = ~"foo" (2)
p = ~$/dollar/slashy $ string/$ (3)
p = ~"${pattern}" (4)
1 | using single quote strings |
2 | using double quotes strings |
3 | the dollar-slashy string lets you use slashes and the dollar sign without having to escape them |
4 | you can also use a GString! |
Find operator
Alternatively to building a pattern, you can directly use the find operator =~
to build a java.util.regex.Matcher
instance:
def text = "some text to match"
def m = text =~ /match/ (1)
assert m instanceof Matcher (2)
if (!m) { (3)
throw new RuntimeException("Oops, text not found!")
}
1 | =~ creates a matcher against the text variable, using the pattern on the right hand side |
2 | the return type of =~ is a Matcher |
3 | equivalent to calling if (!m.find()) |
Since a Matcher
coerces to a boolean
by calling its find
method, the =~
operator is consistent with the simple
use of Perl’s =~
operator, when it appears as a predicate (in if
, while
, etc.).
Match operator
The match operator (==~
) is a slight variation of the find operator, that does not return a Matcher
but a boolean
and requires a strict match of the input string:
m = text ==~ /match/ (1)
assert m instanceof Boolean (2)
if (m) { (3)
throw new RuntimeException("Should not reach that point!")
}
1 | ==~ matches the subject with the regular expression, but match must be strict |
2 | the return type of ==~ is therefore a boolean |
3 | equivalent to calling if (text ==~ /match/) |
1.2.8. Other operators
Spread operator
The Spread Operator (*.
) is used to invoke an action on all items of an aggregate object. It is equivalent to calling the action on each item
and collecting the result into a list:
class Car {
String make
String model
}
def cars = [
new Car(make: 'Peugeot', model: '508'),
new Car(make: 'Renault', model: 'Clio')] (1)
def makes = cars*.make (2)
assert makes == ['Peugeot', 'Renault'] (3)
1 | build a list of Car items. The list is an aggregate of objects. |
2 | call the spread operator on the list, accessing the make property of each item |
3 | returns a list of strings corresponding to the collection of make items |
The spread operator is null-safe, meaning that if an element of the collection is null, it will return null instead of throwing a NullPointerException
:
cars = [
new Car(make: 'Peugeot', model: '508'),
null, (1)
new Car(make: 'Renault', model: 'Clio')]
assert cars*.make == ['Peugeot', null, 'Renault'] (2)
assert null*.make == null (3)
1 | build a list for which of of the elements is null |
2 | using the spread operator will not throw a NullPointerException |
3 | the receiver might also be null, in which case the return value is null |
The spread operator can be used on any class which implements the Iterable
interface:
class Component {
Long id
String name
}
class CompositeObject implements Iterable<Component> {
def components = [
new Component(id: 1, name: 'Foo'),
new Component(id: 2, name: 'Bar')]
@Override
Iterator<Component> iterator() {
components.iterator()
}
}
def composite = new CompositeObject()
assert composite*.id == [1,2]
assert composite*.name == ['Foo','Bar']
Spreading method arguments
There may be situations when the arguments of a method call can be found in a list that you need to adapt to the method arguments. In such situations, you can use the spread operator to call the method. For example, imagine you have the following method signature:
int function(int x, int y, int z) {
x*y+z
}
then if you have the following list:
def args = [4,5,6]
you can call the method without having to define intermediate variables:
assert function(*args) == 26
It is even possible to mix normal arguments with spread ones:
args = [4]
assert function(*args,5,6) == 26
Spread list elements
When used inside a list literal, the spread operator acts as if the spread element contents were inlined into the list:
def items = [4,5] (1)
def list = [1,2,3,*items,6] (2)
assert list == [1,2,3,4,5,6] (3)
1 | items is a list |
2 | we want to insert the contents of the items list directly into list without having to call addAll |
3 | the contents of items has been inlined into list |
Spread map elements
The spread map operator works in a similar manner as the spread list operator, but for maps. It allows you to inline the contents of a map into another map literal, like in the following example:
def m1 = [c:3, d:4] (1)
def map = [a:1, b:2, *:m1] (2)
assert map == [a:1, b:2, c:3, d:4] (3)
1 | m1 is the map that we want to inline |
2 | we use the *:m1 notation to spread the contents of m1 into map |
3 | map contains all the elements of m1 |
The position of the spread map operator is relevant, like illustrated in the following example:
def m1 = [c:3, d:4] (1)
def map = [a:1, b:2, *:m1, d: 8] (2)
assert map == [a:1, b:2, c:3, d:8] (3)
1 | m1 is the map that we want to inline |
2 | we use the *:m1 notation to spread the contents of m1 into map , but redefine the key d after spreading |
3 | map contains all the expected keys, but d was redefined |
Range operator
Groovy supports the concept of ranges and provides a notation (..
) to create ranges of objects:
def range = 0..5 (1)
assert (0..5).collect() == [0, 1, 2, 3, 4, 5] (2)
assert (0..<5).collect() == [0, 1, 2, 3, 4] (3)
assert (0..5) instanceof List (4)
assert (0..5).size() == 6 (5)
1 | a simple range of integers, stored into a local variable |
2 | an IntRange , with inclusive bounds |
3 | an IntRange , with exclusive upper bound |
4 | a groovy.lang.Range implements the List interface |
5 | meaning that you can call the size method on it |
Ranges implementation is lightweight, meaning that only the lower and upper bounds are stored. You can create a range
from any Comparable
object. For example, you can create a range of characters this way:
assert ('a'..'d').collect() == ['a','b','c','d']
Spaceship operator
The spaceship operator (<=>
) delegates to the compareTo
method:
assert (1 <=> 1) == 0
assert (1 <=> 2) == -1
assert (2 <=> 1) == 1
assert ('a' <=> 'z') == -1
Subscript operator
The subscript operator is a short hand notation for getAt
or putAt
, depending on whether you find it on
the left hand side or the right hand side of an assignment:
def list = [0,1,2,3,4]
assert list[2] == 2 (1)
list[2] = 4 (2)
assert list[0..2] == [0,1,4] (3)
list[0..2] = [6,6,6] (4)
assert list == [6,6,6,3,4] (5)
1 | [2] can be used instead of getAt(2) |
2 | if on left hand side of an assignment, will call putAt |
3 | getAt also supports ranges |
4 | so does putAt |
5 | the list is mutated |
The subscript operator, in combination with a custom implementation of getAt
/putAt
is a convenient way for destructuring
objects:
class User {
Long id
String name
def getAt(int i) { (1)
switch (i) {
case 0: return id
case 1: return name
}
throw new IllegalArgumentException("No such element $i")
}
void putAt(int i, def value) { (2)
switch (i) {
case 0: id = value; return
case 1: name = value; return
}
throw new IllegalArgumentException("No such element $i")
}
}
def user = new User(id: 1, name: 'Alex') (3)
assert user[0] == 1 (4)
assert user[1] == 'Alex' (5)
user[1] = 'Bob' (6)
assert user.name == 'Bob' (7)
1 | the User class defines a custom getAt implementation |
2 | the User class defines a custom putAt implementation |
3 | create a sample user |
4 | using the subscript operator with index 0 allows retrieving the user id |
5 | using the subscript operator with index 1 allows retrieving the user name |
6 | we can use the subscript operator to write to a property thanks to the delegation to putAt |
7 | and check that it’s really the property name which was changed |
Membership operator
The membership operator (in
) is equivalent to calling the isCase
method. In the context of a List
, it is equivalent
to calling contains
, like in the following example:
def list = ['Grace','Rob','Emmy']
assert ('Emmy' in list) (1)
1 | equivalent to calling list.contains('Emmy') or list.isCase('Emmy') |
Identity operator
In Groovy, using ==
to test equality is different from using the same operator in Java. In Groovy, it is calling equals
.
If you want to compare reference equality, you should use is
like in the following example:
def list1 = ['Groovy 1.8','Groovy 2.0','Groovy 2.3'] (1)
def list2 = ['Groovy 1.8','Groovy 2.0','Groovy 2.3'] (2)
assert list1 == list2 (3)
assert !list1.is(list2) (4)
1 | Create a list of strings |
2 | Create another list of strings containing the same elements |
3 | using == , we test object equality |
4 | but using is , we can check that references are distinct |
Coercion operator
The coercion operator (as
) is a variant of casting. Coercion converts object from one type to another without them
being compatible for assignement. Let’s take an example:
Integer x = 123
String s = (String) x (1)
1 | Integer is not assignable to a String , so it will produce a ClassCastException at runtime |
This can be fixed by using coercion instead:
Integer x = 123
String s = x as String (1)
1 | Integer is not assignable to a String , but use of as will coerce it to a String |
When an object is coerced into another, unless the target type is the same as the source type, coercion will return a
new object. The rules of coercion differ depending on the source and target types, and coercion may fail if no conversion
rules are found. Custom conversion rules may be implemented thanks to the asType
method:
class Identifiable {
String name
}
class User {
Long id
String name
def asType(Class target) { (1)
if (target==Identifiable) {
return new Identifiable(name: name)
}
throw new ClassCastException("User cannot be coerced into $target")
}
}
def u = new User(name: 'Xavier') (2)
def p = u as Identifiable (3)
assert p instanceof Identifiable (4)
assert !(p instanceof User) (5)
1 | the User class defines a custom conversion rule from User to Identifiable |
2 | we create an instance of User |
3 | we coerce the User instance into an Identifiable |
4 | the target is an instance of Identifiable |
5 | the target is not an instance of User anymore |
Diamond operator
The diamond operator (<>
) is a syntactic sugar only operator added to support compatibility with the operator of the
same name in Java 7. It is used to indicate that generic types should be inferred from the declaration:
List<String> strings = new LinkedList<>()
In dynamic Groovy, this is totally unused. In statically type checked Groovy, it is also optional since the Groovy type checker performs type inference whether this operator is present or not.
Call operator
The call operator ()
is used to call a method named call
implicitly. For any object which defines a call
method,
you can omit the .call
part and use the call operator instead:
class MyCallable {
int call(int x) { (1)
2*x
}
}
def mc = new MyCallable()
assert mc.call(2) == 4 (2)
assert mc(2) == 4 (3)
1 | MyCallable defines a method named call . Note that it doesn’t need to implement java.util.concurrent.Callable |
2 | we can call the method using the classic method call syntax |
3 | or we can omit .call thanks to the call operator |
1.2.9. Operator precedence
The table below lists all groovy operators in order of precedence.
Level | Operator(s) | Name(s) |
---|---|---|
1 |
|
scope escape |
|
new, explicit parentheses |
|
|
method call, closure, list/map |
|
|
dot, safe dereferencing, spread-dot |
|
|
bitwise negate, not, typecast |
|
2 |
|
power |
3 |
|
pre/post increment/decrement, unary plus, unary minus |
4 |
|
multiply, div, modulo |
5 |
|
binary plus, binary minus |
6 |
|
left/right (unsigned) shift, inclusive/exclusive range |
7 |
|
less/greater than/or equal, instanceof, type coercion |
8 |
|
equal, not equal, compare to |
9 |
|
binary and |
10 |
|
binary xor |
11 |
|
binary or |
12 |
|
logical and |
13 |
|
logical or |
14 |
|
ternary conditional |
15 |
|
various assignments |
1.2.10. Operator overloading
Groovy allows you to overload the various operators so that they can be used with your own classes. Consider this simple class:
class Bucket {
int size
Bucket(int size) { this.size = size }
Bucket plus(Bucket other) { (1)
return new Bucket(this.size + other.size)
}
}
1 | Bucket implements a special method called plus() |
Just by implementing the plus()
method, the Bucket
class can now be used with the +
operator like so:
def b1 = new Bucket(4)
def b2 = new Bucket(11)
assert (b1 + b2).size == 15 (1)
1 | The two Bucket objects can be added together with the + operator |
All (non-comparator) Groovy operators have a corresponding method that you can implement in your own classes. The only requirements are that your method is public, has the correct name, and has the correct number of arguments. The argument types depend on what types you want to support on the right hand side of the operator. For example, you could support the statement
assert (b1 + 11).size == 15
by implementing the plus()
method with this signature:
Bucket plus(int capacity) {
return new Bucket(this.size + capacity)
}
Here is a complete list of the operators and their corresponding methods:
Operator | Method | Operator | Method |
---|---|---|---|
|
a.plus(b) |
|
a.getAt(b) |
|
a.minus(b) |
|
a.putAt(b, c) |
|
a.multiply(b) |
|
a.leftShift(b) |
|
a.div(b) |
|
a.rightShift(b) |
|
a.mod(b) |
|
a.next() |
|
a.power(b) |
|
a.previous() |
|
a.or(b) |
|
a.positive() |
|
a.and(b) |
|
a.negative() |
|
a.xor(b) |
|
a.bitwiseNegative() |
1.3. Program structure (Anto Aravinth)
This chapter covers the program structure of the Groovy programming language.
1.3.1. Package names
Package names play exactly the same role as in Java. They allows us to separate the code base without any conflicts. Groovy classes must specify their package before the class definition, else the default package is assumed.
Defining a package is very similar to Java:
// defining a package named com.yoursite
package com.yoursite
To refer to some class Foo
in the com.yoursite.com
package you will need to use the fully qualified name com.yoursite.com.Foo
, or else you can use an import
statement as we’ll see below.
1.3.2. Imports
In order to refer to any class you need a qualified reference to its package. Groovy follows Java’s notion of allowing import
statement to resolve class references.
For example, Groovy provides several builder classes, such as MarkupBuilder
. MarkupBuilder
is inside the package groovy.xml
so in order to use this class, you need to import
it as shown:
// importing the class MarkupBuilder
import groovy.xml.MarkupBuilder
// using the imported class to create an object
def xml = new MarkupBuilder()
assert xml != null
Default imports
Default imports are the imports that Groovy language provides by default. For example look at the following code:
new Date()
The same code in Java needs an import statement to Date
class like this: import java.util.Date
. Groovy by default imports these classes for you. There are six packages that groovy imports for you, they are:
import java.lang.*
import java.util.*
import java.io.*
import java.net.*
import groovy.lang.*
import groovy.util.*
import java.math.BigInteger
import java.math.BigDecimal
Simple import
A simple import is an import statement where you fully define the class name along with the package. For example the import statement import groovy.xml.MarkupBuilder
in the code below is a simple import which directly refers to the a class inside a package.
// importing the class MarkupBuilder
import groovy.xml.MarkupBuilder
// using the imported class to create an object
def xml = new MarkupBuilder()
assert xml != null
Star import
Groovy, like Java, provides a special way to import all classes from a package using *
, a so called Star import. MarkupBuilder
is a class which is in package groovy.xml
, alongside another class called StreamingMarkupBuilder
. In case you need to use both classes, you can do:
import groovy.xml.MarkupBuilder
import groovy.xml.StreamingMarkupBuilder
def markupBuilder = new MarkupBuilder()
assert markupBuilder != null
assert new StreamingMarkupBuilder() != null
That’s perfectly valid code. But with a *
import, we can achieve the same effect with just one line, where *
imports all the classes under package groovy.xml
:
import groovy.xml.*
def markupBuilder = new MarkupBuilder()
assert markupBuilder != null
assert new StreamingMarkupBuilder() != null
One problem with *
imports is that they can clutter your local namespace. But with the kinds of aliasing provided by Groovy, this can be solved easily.
Static import
Groovy’s static import capability allows you to reference imported classes as if they were static methods in your own class. This is similar to Java’s static import capability but works with Java 1.4 and above and is a little more dynamic than Java in that it allows you to define methods with the same name as an imported method as long as you have different types. If you have the same types, the imported class takes precedence. Here is a sample of its usage:
import static Boolean.FALSE
assert !FALSE //use directly, without Boolean prefix!
As you can see, now we can able to refer to the static variable FALSE
in our code base cleanly.
Static import aliasing
Static imports with the as
keyword provide an elegant solution to namespace problems. Suppose you want to get a Calendar
instance, using its getInstance()
method. It’s a static method, so we can use a static import. But instead of calling getInstance()
every time, which can be misleading when separated from its class name, we can import it with an alias, to increase code readability:
import static Calendar.getInstance as now
assert now().class == Calendar.getInstance().class
Now, that’s clean!
Static star import
A static star import is very similar to the regular star import. It will import all the static methods from the given class.
For example, lets say we need to calculate sines and cosines for our application.
The class java.lang.Math
has static methods named sin
and cos
which fit our need. With the help of a static star import, we can do:
import static java.lang.Math.*
assert sin(0) == 0.0
assert cos(0) == 1.0
As you can see, we were able to access the methods sin
and cos
directly, without the Math.
prefix.
Import aliasing
With type aliasing, we can refer to a fully qualified class name using a name of our choice. This can be done with the as
keyword, as before.
Consider the following class, provided by some third-party library code:
package thirdpartylib
public class MultiplyTwo {
def static multiply(def value) {
return value * 3 //intentionally wrong.
}
}
Suppose we have some existing code using the library:
def result = new MultiplyTwo().multiply(2)
Now suppose that, after using this library throughout your codebase, we discover that it doesn’t give correct results. How can we fix it in one place, outside of the original class, without changing all the code that’s using it? Groovy has an elegant solution to this problem.
With a simple import aliasing, we can fix the bug like this:
import thirdpartylib.MultiplyTwo as OrigMultiplyTwo
class MultiplyTwo extends OrigMultiplyTwo {
def multiply(def value) {
return value * 2 // fixed here
}
}
// nothing to change below here
def multiplylib = new MultiplyTwo()
// assert passes as well
assert 4 == new MultiplyTwo().multiply(2)
Thats it! Notice how Groovy allowed us to use the as
keyword to rename our imported class and solve this common problem.
Type aliasing is also useful to solve name collision problems which can occur with *
imports.
1.4. Object orientation
This chapter covers the object orientation of the Groovy programming language.
1.4.2. Traits
Traits are a a structural construct of the language which allow:
-
composition of behaviors
-
runtime implementation of interfaces
-
behavior overriding
-
compatibility with static type checking/compilation
They can be seen as interfaces carrying both default implementations and state. A trait is defined using the
trait
keyword:
trait FlyingAbility { (1)
String fly() { "I'm flying!" } (2)
}
1 | declaration of a trait |
2 | declaration of a method inside a trait |
Then it can be used like a normal interface using the implements
keyword:
class Bird implements FlyingAbility {} (1)
def b = new Bird() (2)
assert b.fly() == "I'm flying!" (3)
1 | Adds the trait FlyingAbility to the Bird class capabilities |
2 | instantiate a new Bird |
3 | the Bird class automatically gets the behavior of the FlyingAbility trait |
Traits allow a wide range of capabilities, from simple composition to testing, which are described thoroughly in this section.
Methods
Public methods
Declaring a method in a trait can be done like any regular method in a class:
trait FlyingAbility { (1)
String fly() { "I'm flying!" } (2)
}
1 | declaration of a trait |
2 | declaration of a method inside a trait |
Abstract methods
In addition, traits may declare abstract methods too, which therefore need to be implemented in the class implementing the trait:
trait Greetable {
abstract String name() (1)
String greeting() { "Hello, ${name()}!" } (2)
}
1 | implementing class will have to declare the name method |
2 | can be mixed with a concrete method |
Then the trait can be used like this:
class Person implements Greetable { (1)
String name() { 'Bob' } (2)
}
def p = new Person()
assert p.greeting() == 'Hello, Bob!' (3)
1 | implement the trait Greetable |
2 | since name was abstract, it is required to implement it |
3 | then greeting can be called |
Private methods
Traits may also define private methods. Those methods will not appear in the trait contract interface:
trait Greeter {
private String greetingMessage() { (1)
'Hello from a private method!'
}
String greet() {
def m = greetingMessage() (2)
println m
m
}
}
class GreetingMachine implements Greeter {} (3)
def g = new GreetingMachine()
assert g.greet() == "Hello from a private method!" (4)
try {
assert g.greetingMessage() (5)
} catch (MissingMethodException e) {
println "greetingMessage is private in trait"
}
1 | define a private method greetingMessage in the trait |
2 | the public greet message calls greetingMessage by default |
3 | create a class implementing the trait |
4 | greet can be called |
5 | but not greetingMessage |
Traits only support public and private methods. Neither protected nor package private scopes are
supported.
|
The meaning of this
this
represents the implementing instance. Think of a trait as a superclass. This means that when you write:
trait Introspector {
def whoAmI() { this }
}
class Foo implements Introspector {}
def foo = new Foo()
then calling:
foo.whoAmI()
will return the same instance:
assert foo.whoAmI().is(foo)
Interfaces
Traits may implement interfaces, in which case the interfaces are declared using the implements
keyword:
interface Named { (1)
String name()
}
trait Greetable implements Named { (2)
String greeting() { "Hello, ${name()}!" }
}
class Person implements Greetable { (3)
String name() { 'Bob' } (4)
}
def p = new Person()
assert p.greeting() == 'Hello, Bob!' (5)
assert p instanceof Named (6)
assert p instanceof Greetable (7)
1 | declaration of a normal interface |
2 | add Named to the list of implemented interfaces |
3 | declare a class that implements the Greetable trait |
4 | implement the missing greet method |
5 | the greeting implementation comes from the trait |
6 | make sure Person implements the Named interface |
7 | make sure Person implements the Greetable trait |
Properties
A trait may define properties, like in the following example:
trait Named {
String name (1)
}
class Person implements Named {} (2)
def p = new Person(name: 'Bob') (3)
assert p.name == 'Bob' (4)
assert p.getName() == 'Bob' (5)
1 | declare a property name inside a trait |
2 | declare a class which implements the trait |
3 | the property is automatically made visible |
4 | it can be accessed using the regular property accessor |
5 | or using the regular getter syntax |
Fields
Private fields
Since traits allow the use of private methods, it can also be interesting to use private fields to store state. Traits will let you do that:
trait Counter {
private int count = 0 (1)
int count() { count += 1; count } (2)
}
class Foo implements Counter {} (3)
def f = new Foo()
assert f.count() == 1 (4)
assert f.count() == 2
1 | declare a private field count inside a trait |
2 | declare a public method count that increments the counter and returns it |
3 | declare a class that implements the Counter trait |
4 | the count method can use the private field to keep state |
This is a major difference with Java 8 virtual extension methods. While virtual extension methods do not carry state, traits can. Moreover, traits in Groovy are supported starting with Java 6, because their implementation does not rely on virtual extension methods. This means that even if a trait can be seen from a Java class as a regular interface, that interface will not have default methods, only abstract ones. |
Public fields
Public fields work the same way as private fields, but in order to avoid the diamond problem, field names are remapped in the implementing class:
trait Named {
public String name (1)
}
class Person implements Named {} (2)
def p = new Person() (3)
p.Named__name = 'Bob' (4)
1 | declare a public field inside the trait |
2 | declare a class implementing the trait |
3 | create an instance of that class |
4 | the public field is available, but renamed |
The name of the field depends on the fully qualified name of the trait. All dots (.
) in package are replaced with an underscore (_
), and the final name includes a double underscore.
So if the type of the field is String
, the name of the package is my.package
, the name of the trait is Foo
and the name of the field is bar
,
in the implementing class, the public field will appear as:
String my_package_Foo__bar
While traits support public fields, it is not recommended to use them and considered as a bad practice. |
Composition of behaviors
Traits can be used to implement multiple inheritance in a controlled way, avoiding the diamond issue. For example, we can have the following traits:
trait FlyingAbility { (1)
String fly() { "I'm flying!" } (2)
}
trait SpeakingAbility {
String speak() { "I'm speaking!" }
}
And a class implementing both traits:
class Duck implements FlyingAbility, SpeakingAbility {} (1)
def d = new Duck() (2)
assert d.fly() == "I'm flying!" (3)
assert d.speak() == "I'm speaking!" (4)
1 | the Duck class implements both FlyingAbility and SpeakingAbility |
2 | creates a new instance of Duck |
3 | we can call the method fly from FlyingAbility |
4 | but also the method speak from SpeakingAbility |
Traits encourage the reuse of capabilities among objects, and the creation of new classes by the composition of existing behavior.
Overriding default methods
Traits provide default implementations for methods, but it is possible to override them in the implementing class. For example, we can slightly change the example above, by having a duck which quacks:
class Duck implements FlyingAbility, SpeakingAbility {
String quack() { "Quack!" } (1)
String speak() { quack() } (2)
}
def d = new Duck()
assert d.fly() == "I'm flying!" (3)
assert d.quack() == "Quack!" (4)
assert d.speak() == "Quack!" (5)
1 | define a method specific to Duck , named quack |
2 | override the default implementation of speak so that we use quack instead |
3 | the duck is still flying, from the default implementation |
4 | quack comes from the Duck class |
5 | speak no longer uses the default implementation from SpeakingAbility |
Extending traits
Simple inheritance
Traits may extend another trait, in which case you must use the extends
keyword:
trait Named {
String name (1)
}
trait Polite extends Named { (2)
String introduce() { "Hello, I am $name" } (3)
}
class Person implements Polite {}
def p = new Person(name: 'Alice') (4)
assert p.introduce() == 'Hello, I am Alice' (5)
1 | the Named trait defines a single name property |
2 | the Polite trait extends the Named trait |
3 | Polite adds a new method which has access to the name property of the super-trait |
4 | the name property is visible from the Person class implementing Polite |
5 | as is the introduce method |
Multiple inheritance
Alternatively, a trait may extend multiple traits. In that case, all super traits must be declared in the implements
clause:
trait WithId { (1)
Long id
}
trait WithName { (2)
String name
}
trait Identified implements WithId, WithName {} (3)
1 | WithId trait defines the id property |
2 | WithName trait defines the name property |
3 | Identified is a trait which inherits both WithId and WithName |
Duck typing and traits
Dynamic code
Traits can call any dynamic code, like a normal Groovy class. This means that you can, in the body of a method, call methods which are supposed to exist in an implementing class, without having to explicitly declare them in an interface. This means that traits are fully compatible with duck typing:
trait SpeakingDuck {
String speak() { quack() } (1)
}
class Duck implements SpeakingDuck {
String methodMissing(String name, args) {
"${name.capitalize()}!" (2)
}
}
def d = new Duck()
assert d.speak() == 'Quack!' (3)
1 | the SpeakingDuck expects the quack method to be defined |
2 | the Duck class does implement the method using methodMissing |
3 | calling the speak method triggers a call to quack which is handled by methodMissing |
Dynamic methods in a trait
It is also possible for a trait to implement MOP methods like methodMissing
or propertyMissing
, in which case implementing classes
will inherit the behavior from the trait, like in this example:
trait DynamicObject { (1)
private Map props = [:]
def methodMissing(String name, args) {
name.toUpperCase()
}
def propertyMissing(String prop) {
props[prop]
}
void setProperty(String prop, Object value) {
props[prop] = value
}
}
class Dynamic implements DynamicObject {
String existingProperty = 'ok' (2)
String existingMethod() { 'ok' } (3)
}
def d = new Dynamic()
assert d.existingProperty == 'ok' (4)
assert d.foo == null (5)
d.foo = 'bar' (6)
assert d.foo == 'bar' (7)
assert d.existingMethod() == 'ok' (8)
assert d.someMethod() == 'SOMEMETHOD' (9)
1 | create a trait implementing several MOP methods |
2 | the Dynamic class defines a property |
3 | the Dynamic class defines a method |
4 | calling an existing property will call the method from Dynamic |
5 | calling an non-existing property will call the method from the trait |
6 | will call setProperty defined on the trait |
7 | will call getProperty defined on the trait |
8 | calling an existing method on Dynamic |
9 | but calling a non existing method thanks to the trait methodMissing |
Multiple inheritance conflicts
Default conflict resolution
It is possible for a class to implement multiple traits. If some trait defines a method with the same signature as a method in another trait, we have a conflict:
trait A {
String exec() { 'A' } (1)
}
trait B {
String exec() { 'B' } (2)
}
class C implements A,B {} (3)
1 | trait A defines a method named exec returning a String |
2 | trait B defines the very same method |
3 | class C implements both traits |
In this case, the default behavior is that methods from the last declared trait wins. Here, B
is declared after A
so the method from B
will be picked up:
def c = new C()
assert c.exec() == 'B'
User conflict resolution
In case this behavior is not the one you want, you can explicitly choose which method to call using the Trait.super.foo
syntax.
In the example above, we can force to choose the method from trait A, by writing this:
class C implements A,B {
String exec() { A.super.exec() } (1)
}
def c = new C()
assert c.exec() == 'A' (2)
1 | explicit call of exec from the trait A |
2 | calls the version from A instead of using the default resolution, which would be the one from B |
Runtime implementation of traits
Implementing a trait at runtime
Groovy also supports implementing traits dynamically at runtime. It allows you to "decorate" an existing object using a trait. As an example, let’s start with this trait and the following class:
trait Extra {
String extra() { "I'm an extra method" } (1)
}
class Something { (2)
String doSomething() { 'Something' } (3)
}
1 | the Extra trait defines an extra method |
2 | the Something class does not implement the Extra trait |
3 | Something only defines a method doSomething |
Then if we do:
def s = new Something()
s.extra()
the call to extra would fail because Something
is not implementing Extra
. It is possible to do it at runtime with
the following syntax:
def s = new Something() as Extra (1)
s.extra() (2)
s.doSomething() (3)
1 | use of the as keyword to coerce an object to a trait at runtime |
2 | then extra can be called on the object |
3 | and doSomething is still callable |
When coercing an object to a trait, the result of the operation is not the same instance. It is guaranteed that the coerced object will implement both the trait and the interfaces that the original object implements, but the result will not be an instance of the original class. |
Implementing multiple traits at once
Should you need to implement several traits at once, you can use the withTraits
method instead of the as
keyword:
trait A { void methodFromA() {} }
trait B { void methodFromB() {} }
class C {}
def c = new C()
c.methodFromA() (1)
c.methodFromB() (2)
def d = c.withTraits A, B (3)
d.methodFromA() (4)
d.methodFromB() (5)
1 | call to methodFromA will fail because C doesn’t implement A |
2 | call to methodFromB will fail because C doesn’t implement B |
3 | withTrait will wrap c into something which implements A and B |
4 | methodFromA will now pass because d implements A |
5 | methodFromB will now pass because d also implements B |
When coercing an object to multiple traits, the result of the operation is not the same instance. It is guaranteed that the coerced object will implement both the traits and the interfaces that the original object implements, but the result will not be an instance of the original class. |
Chaining behavior
Groovy supports the concept of stackable traits. The idea is to delegate from one trait to the other if the current trait is not capable of handling a message. To illustrate this, let’s imagine a message handler interface like this:
interface MessageHandler {
void on(String message, Map payload)
}
Then you can compose a message handler by applying small behaviors. For example, let’s define a default handler in the form of a trait:
trait DefaultHandler implements MessageHandler {
void on(String message, Map payload) {
println "Received $message with payload $payload"
}
}
Then any class can inherit the behavior of the default handler by implementing the trait:
class SimpleHandler implements DefaultHandler {}
Now what if you want to log all messages, in addition to the default handler? One option is to write this:
class SimpleHandlerWithLogging implements DefaultHandler {
void on(String message, Map payload) { (1)
println "Seeing $message with payload $payload" (2)
DefaultHandler.super.on(message, payload) (3)
}
}
1 | explicitly implement the on method |
2 | perform logging |
3 | continue by delegating to the DefaultHandler trait |
This works but this approach has drawbacks:
-
the logging logic is bound to a "concrete" handler
-
we have an explicit reference to
DefaultHandler
in theon
method, meaning that if we happen to change the trait that our class implements, code will be broken
As an alternative, we can write another trait which responsability is limited to logging:
trait LoggingHandler implements MessageHandler { (1)
void on(String message, Map payload) {
println "Seeing $message with payload $payload" (2)
super.on(message, payload) (3)
}
}
1 | the logging handler is itself a handler |
2 | prints the message it receives |
3 | then super makes it delegate the call to the next trait in the chain |
Then our class can be rewritten as this:
class HandlerWithLogger implements DefaultHandler, LoggingHandler {}
def loggingHandler = new HandlerWithLogger()
loggingHandler.on('test logging', [:])
which will print:
Seeing test logging with payload [:] Received test logging with payload [:]
As the priority rules imply that LoggerHandler
wins because it is declared last, then a call to on
will use
the implementation from LoggingHandler
. But the latter has a call to super
, which means the next trait in the
chain. Here, the next trait is DefaultHandler
so both will be called:
The interest of this approach becomes more evident if we add a third handler, which is responsible for handling messages
that start with say
:
trait SayHandler implements MessageHandler {
void on(String message, Map payload) {
if (message.startsWith("say")) { (1)
println "I say ${message - 'say'}!"
} else {
super.on(message, payload) (2)
}
}
}
1 | a handler specific precondition |
2 | if the precondition is not met, pass the message to the next handler in the chain |
Then our final handler looks like this:
class Handler implements DefaultHandler, SayHandler, LoggingHandler {}
def h = new Handler()
h.on('foo', [:])
h.on('sayHello', [:])
Which means:
-
messages will first go through the logging handler
-
the logging handler calls
super
which will delegate to the next handler, which is theSayHandler
-
if the message starts with
say
, then the hanlder consumes the message -
if not, the
say
handler delegates to the next handler in the chain
This approach is very powerful because it allows you to write handlers that do not know each other and yet let you combine them in the order you want. For example, if we execute the code, it will print:
Seeing foo with payload [:] Received foo with payload [:] Seeing sayHello with payload [:] I say Hello!
but if we move the logging handler to be the second one in the chain, the output is different:
class AlternateHandler implements DefaultHandler, LoggingHandler, SayHandler {}
h = new AlternateHandler()
h.on('foo', [:])
h.on('sayHello', [:])
prints:
Seeing foo with payload [:] Received foo with payload [:] I say Hello!
The reason is that now, since the SayHandler
consumes the message without calling super
, the logging handler is
not called anymore.
Semantics of super inside a trait
If a class implements multiple traits and a call to an unqualified super
is found, then:
-
if the class implements another trait, the call delegates to the next trait in the chain
-
if there isn’t any trait left in the chain,
super
refers to the super class of the implementing class (this)
For example, it is possible to decorate final classes thanks to this behavior:
trait Filtering { (1)
StringBuilder append(String str) { (2)
def subst = str.replace('o','') (3)
super.append(subst) (4)
}
String toString() { super.toString() } (5)
}
def sb = new StringBuilder().withTraits Filtering (6)
sb.append('Groovy')
assert sb.toString() == 'Grvy' (7)
1 | define a trait named Filtering , supposed to be applied on a StringBuilder at runtime |
2 | redefine the append method |
3 | remove all 'o’s from the string |
4 | then delegate to super |
5 | in case toString is called, delegate to super.toString |
6 | runtime implementation of the Filtering trait on a StringBuilder instance |
7 | the string which has been appended no longer contains the letter o |
In this example, when super.append
is encountered, there is no other trait implemented by the target object, so the
method which is called is the original append
method, that is to say the one from StringBuilder
. The same trick
is used for toString
, so that the string representation of the proxy object which is generated delegates to the
toString
of the StringBuilder
instance.
Advanced features
SAM type coercion
If a trait defines a single abstract method, it is candidate for SAM (Single Abstract Method) type coercion. For example, imagine the following trait:
trait Greeter {
String greet() { "Hello $name" } (1)
abstract String getName() (2)
}
1 | the greet method is not abstract and calls the abstract method getName |
2 | getName is an abstract method |
Since getName
is the single abstract method in the Greeter
trait, you can write:
Greeter greeter = { 'Alice' } (1)
1 | the closure "becomes" the implementation of the getName single abstract method |
or even:
void greet(Greeter g) { println g.greet() } (1)
greet { 'Alice' } (2)
1 | the greet method accepts the SAM type Greeter as parameter |
2 | we can call it directly with a closure |
Differences with Java 8 default methods
In Java 8, interfaces can have default implementations of methods. If a class implements an interface and does not provide an implementation for a default method, then the implementation from the interface is chosen. Traits behave the same but with a major difference: the implementation from the trait is always used if the class declares the trait in its interface list and that it doesn’t provide an implementation.
This feature can be used to compose behaviors in an very precise way, in case you want to override the behavior of an already implemented method.
To illustrate the concept, let’s start with this simple example:
import groovy.transform.CompileStatic
import org.codehaus.groovy.control.CompilerConfiguration
import org.codehaus.groovy.control.customizers.ASTTransformationCustomizer
import org.codehaus.groovy.control.customizers.ImportCustomizer
class SomeTest extends GroovyTestCase {
def config
def shell
void setup() {
config = new CompilerConfiguration()
shell = new GroovyShell(config)
}
void testSomething() {
assert shell.evaluate('1+1') == 2
}
void otherTest() { /* ... */ }
}
In this example, we create a simple test case which uses two properties (config and shell) and uses those in
multiple test methods. Now imagine that you want to test the same, but with another distinct compiler configuration.
One option is to create a subclass of SomeTest
:
class AnotherTest extends SomeTest {
void setup() {
config = new CompilerConfiguration()
config.addCompilationCustomizers( ... )
shell = new GroovyShell(config)
}
}
It works, but what if you have actually multiple test classes, and that you want to test the new configuration for all those test classes? Then you would have to create a distinct subclass for each test class:
class YetAnotherTest extends SomeTest {
void setup() {
config = new CompilerConfiguration()
config.addCompilationCustomizers( ... )
shell = new GroovyShell(config)
}
}
Then what you see is that the setup
method of both tests is the same. The idea, then, is to create a trait:
trait MyTestSupport {
void setup() {
config = new CompilerConfiguration()
config.addCompilationCustomizers( new ASTTransformationCustomizer(CompileStatic) )
shell = new GroovyShell(config)
}
}
Then use it in the subclasses:
class AnotherTest extends SomeTest implements MyTestSupport {}
class YetAnotherTest extends SomeTest2 implements MyTestSupport {}
...
It would allow us to dramatically reduce the boilerplate code, and reduces the risk of forgetting to change the setup
code in case we decide to change it. Even if setup
is already implemented in the super class, since the test class declares
the trait in its interface list, the behavior will be borrowed from the trait implementation!
This feature is in particular useful when you don’t have access to the super class source code. It can be used to mock methods or force a particular implementation of a method in a subclass. It lets you refactor your code to keep the overriden logic in a single trait and inherit a new behavior just by implementing it. The alternative, of course, is to override the method in every place you would have used the new code.
It’s worth noting that if you use runtime traits, the methods from the trait are always preferred to those of the proxied object: |
class Person {
String name (1)
}
trait Bob {
String getName() { 'Bob' } (2)
}
def p = new Person(name: 'Alice')
assert p.name == 'Alice' (3)
def p2 = p as Bob (4)
assert p2.name == 'Bob' (5)
1 | the Person class defines a name property which results in a getName method |
2 | Bob is a trait which defines getName as returning Bob |
3 | the default object will return Alice |
4 | p2 coerces p into Bob at runtime |
5 | getName returns Bob because getName is taken from the trait |
Again, don’t forget that dynamic trait coercion returns a distinct object which only implements the original interfaces, as well as the traits. |
Differences with mixins
There are several conceptual differences with mixins, as they are available in Groovy. Note that we are talking about runtime mixins, not the @Mixin annotation which is deprecated in favour of traits.
First of all, methods defined in a trait are visible in bytecode:
-
internally, the trait is represented as an interface (without default methods) and several helper classes
-
this means that an object implementing a trait effectively implements an interface
-
those methods are visible from Java
-
they are compatible with type checking and static compilation
Methods added through a mixin are, on the contrary, only visible at runtime:
class A { String methodFromA() { 'A' } } (1)
class B { String methodFromB() { 'B' } } (2)
A.metaClass.mixin B (3)
def o = new A()
assert o.methodFromA() == 'A' (4)
assert o.methodFromB() == 'B' (5)
assert o instanceof A (6)
assert !(o instanceof B) (7)
1 | class A defines methodFromA |
2 | class B defines methodFromB |
3 | mixin B into A |
4 | we can call methodFromA |
5 | we can also call methodFromB |
6 | the object is an instance of A |
7 | but it’s not an instanceof B |
The last point is actually a very important and illustrates a place where mixins have an advantage over traits: the instances are not modified, so if you mixin some class into another, there isn’t a third class generated, and methods which respond to A will continue responding to A even if mixed in.
Static methods, properties and fields
The following instructions are subject to caution. Static member support is work in progress and still experimental. The information below is valid for 2.3.11 only. |
It is possible to define static methods in a trait, but it comes with numerous limitations:
-
traits with static methods cannot be compiled statically or type checked. All static methods/properties/field are accessed dynamically (it’s a limitation from the JVM).
-
the trait is interpreted as a template for the implementing class, which means that each implementing class will get its own static methods/properties/methods. So a static member declared on a trait doesn’t belong to the
Trait
, but to it’s implementing class.
Let’s start with a simple example:
trait TestHelper {
public static boolean CALLED = false (1)
static void init() { (2)
CALLED = true (3)
}
}
class Foo implements TestHelper {}
Foo.init() (4)
assert Foo.TestHelper__CALLED (5)
1 | the static field is declared in the trait |
2 | a static method is also declared in the trait |
3 | the static field is updated within the trait |
4 | a static method init is made available to the implementing class |
5 | the static field is remapped to avoid the diamond issue |
As usual, it is not recommended to use public fields. Anyway, should you want this, you must understand that the following code would fail:
Foo.CALLED = true
because there is no static field CALLED defined on the trait itself. Likewise, if you have two distinct implementing classes, each one gets a distinct static field:
class Bar implements TestHelper {} (1)
class Baz implements TestHelper {} (2)
Bar.init() (3)
assert Bar.TestHelper__CALLED (4)
assert !Baz.TestHelper__CALLED (5)
1 | class Bar implements the trait |
2 | class Baz also implements the trait |
3 | init is only called on Bar |
4 | the static field CALLED on Bar is updated |
5 | but the static field CALLED on Baz is not, because it is distinct |
Inheritance of state gotchas
We have seen that traits are stateful. It is possible for a trait to define fields or properties, but when a class implements a trait, it gets those fields/properties on a per-trait basis. So consider the following example:
trait IntCouple {
int x = 1
int y = 2
int sum() { x+y }
}
The trait defines two properties, x
and y
, as well as a sum
method. Now let’s create a class which implements the trait:
class BaseElem implements IntCouple {
int f() { sum() }
}
def base = new BaseElem()
assert base.f() == 3
The result of calling f
is 3
, because f
delegates to sum
in the trait, which has state. But what if we write this instead?
class Elem implements IntCouple {
int x = 3 (1)
int y = 4 (2)
int f() { sum() } (3)
}
def elem = new Elem()
1 | Override property x |
2 | Override property y |
3 | Call sum from trait |
If you call elem.f()
, what is the expected output? Actually it is:
assert elem.f() == 3
The reason is that the sum
method accesses the fields of the trait. So it is using the x
and y
values defined
in the trait. If you want to use the values from the implementing class, then you need to derefencence fields by using
getters and setters, like in this last example:
trait IntCouple {
int x = 1
int y = 2
int sum() { getX()+getY() }
}
class Elem implements IntCouple {
int x = 3
int y = 4
int f() { sum() }
}
def elem = new Elem()
assert elem.f() == 7
Limitations
Compatibility with AST transformations
Traits are not officially compatible with AST transformations. Some of them, like @CompileStatic will be applied
on the trait itself (not on implementing classes), while others will apply on both the implementing class and the trait.
There is absolutely no guarantee that an AST transformation will run on a trait as it does on a regular class, so use it
at your own risk!
|
Prefix and postfix operations
Within traits, prefix and postfix operations are not allowed if they update a field of the trait:
trait Counting {
int x
void inc() {
x++ (1)
}
void dec() {
--x (2)
}
}
class Counter implements Counting {}
def c = new Counter()
c.inc()
1 | x is defined within the trait, postfix increment is not allowed |
2 | x is defined within the trait, prefix decrement is not allowed |
A workaround is to use the +=
operator instead.
:leveloffset: 0
1.4.3. Closures (TBD)
This chapter covers Groovy Closures. A closure in Groovy is an open, anonymous, block of code that can take arguments,
return a value and be assigned to a variable. A closure may reference variables declared in its surrounding scope. In
opposition to the formal definition of a closure, Closure
in the Groovy language can also contain free variables which
are defined outside of its surrounding scope. While breaking the formal concept of a closure, it offers a variety of
advantages which are descripted in this chapter.
Syntax
Defining a closure
A closure definition follows this syntax:
{ [closureParameters -> ] statements }
Where +[closureParameters->]+
is an optional comma-delimited list of
parameters, and statements are 0 or more Groovy statements. The parameters
look similar to a method parameter list, and these parameters may be
typed or untyped.
When a parameter list is specified, the +->+
character
is required and serves to seperate the arguments from the closure body.
The statements portion consists of 0, 1, or many Groovy statements.
Some examples of valid closure definitions:
{ item++ } (1)
{ -> item++ } (2)
{ println it } (3)
{ it -> println it } (4)
{ name -> println name } (5)
{ String x, int y -> (6)
println "hey ${x} the value is ${y}"
}
{ reader -> (7)
def line = reader.readLine()
line.trim()
}
1 | A closure referencing a variable named item |
2 | It is possible to explicitly separate closure parameters from code by adding an arrow (+->+ ) |
3 | A closure using an implicit parameter (it ) |
4 | An alternative version where it is this time an explicit parameter |
5 | In that case it is often better to use an explicit name for the parameter |
6 | A closure accepting two typed parameters |
7 | A closure can contain multiple statements |
Closures as an object
A closure is an instance of the groovy.lang.Closure
class, making it assignable to a variable or a field as any
other variable, despite being a block of code:
def listener = { e -> println "Clicked on $e.source" } (1)
assert listener instanceof Closure
Closure callback = { println 'Done!' } (2)
Closure<Boolean> isTextFile = {
File it -> it.name.endsWith('.txt') (3)
}
1 | You can assign a closure to a variable, and it is an instance of groovy.lang.Closure |
2 | If not using def , you can assign a closure to a variable of type groovy.lang.Closure |
3 | Optionally, you can specify the return type of the closure by using the generic type of groovy.lang.Closure |
Calling a closure
A closure, as an anonymous block of code, can be called like any other method. If you define a closure which takes no argument like this:
def code = { 123 }
Then the code inside the closure will only be executed when you call the closure, which can be done by using the variable as if it was a regular method:
assert code() == 123
Alternatively, you can be explicit and use the call
method:
assert code.call() == 123
The principle is the same if the closure accepts arguments:
def isOdd = { int i-> i%2 == 1 } (1)
assert isOdd(3) == true (2)
assert isOdd.call(2) == false (3)
def isEven = { it%2 == 0 } (4)
assert isEven(3) == false (5)
assert isEven.call(2) == true (6)
1 | define a closure which accepts an int as a parameter |
2 | it can be called directly |
3 | or using the call method |
4 | same goes for a closure with an implicit argument (it ) |
5 | which can be called directly using (arg) |
6 | or using call |
Unlike a method, a closure always returns a value when called. The next section discusses how to declare closure arguments, when to use them and what is the implicit "it" parameter.
Parameters
Normal parameters
Parameters of closures follow the same principle as parameters of regular methods:
-
an optional type
-
a name
-
an optional default value
Parameters are separated with commas:
def closureWithOneArg = { str -> str.toUpperCase() }
assert closureWithOneArg('groovy') == 'GROOVY'
def closureWithOneArgAndExplicitType = { String str -> str.toUpperCase() }
assert closureWithOneArgAndExplicitType('groovy') == 'GROOVY'
def closureWithTwoArgs = { a,b -> a+b }
assert closureWithTwoArgs(1,2) == 3
def closureWithTwoArgsAndExplicitTypes = { int a, int b -> a+b }
assert closureWithTwoArgsAndExplicitTypes(1,2) == 3
def closureWithTwoArgsAndOptionalTypes = { a, int b -> a+b }
assert closureWithTwoArgsAndOptionalTypes(1,2) == 3
def closureWithTwoArgAndDefaultValue = { int a, int b=2 -> a+b }
assert closureWithTwoArgAndDefaultValue(1) == 3
Implicit parameter
When a closure does not explicitly define a parameter list (using +->+
), a closure always defines an implicit
parameter, named it
. This means that this code:
def greeting = { "Hello, $it!" }
assert greeting('Patrick') == 'Hello, Patrick!'
is stricly equivalent to this one:
def greeting = { it -> "Hello, $it!" }
assert greeting('Patrick') == 'Hello, Patrick!'
If you want to declare a closure which accepts no argument and must be restricted to calls without arguments, then you must declare it with an explicit empty argument list:
def magicNumber = { -> 42 }
// this call will fail because the closure doesn't accept any argument
magicNumber(11)
Varargs
It is possible for a closure to declare variable arguments like any other method. Vargs methods are methods that can accept a variable number of arguments if the last parameter is of variable length (or an array) like in the next examples:
def concat1 = { String... args -> args.join('') } (1)
assert concat1('abc','def') == 'abcdef' (2)
def concat2 = { String[] args -> args.join('') } (3)
assert concat2('abc', 'def') == 'abcdef'
def multiConcat = { int n, String... args -> (4)
args.join('')*n
}
assert multiConcat(2, 'abc','def') == 'abcdefabcdef'
1 | A closure accepting a variable number of strings as first parameter |
2 | It may be called using any number of arguments without having to explicitly wrap them into an array |
3 | The same behavior is directly available if the args parameter is declared as an array |
4 | As long as the last parameter is an array of an explicit vargs type |
Delegation strategy
Groovy closures vs lambda expressions
Groovy defines closures as instances of the Closure class. It makes it very different from lambda expressions in Java 8. Delegation is a key concept in Groovy closures which has no equivalent in lambdas. The ability to change the delegate or change the delegation strategy of closures make it possible to design beautiful domain specific languages (DSLs) in Groovy.
Owner, delegate and this
To understand the concept of delegate, we must first explain the meaning of this
inside a closure. A closure actually
defines 3 distinct things:
-
this
corresponds to the enclosing class where the closure is defined -
owner
corresponds to the enclosing object where the closure is defined, which may be either a class or a closure -
delegate
corresponds to a third party object where methods calls or properties are resolved whenever the receiver of the message is not defined
In a closure, calling getThisObject
will return the enclosing class where the closure is defined. It is equivalent to
using an explicit this
:
class Enclosing {
void run() {
def whatIsThisObject = { getThisObject() } (1)
assert whatIsThisObject() == this (2)
def whatIsThis = { this } (3)
assert whatIsThis() == this (4)
}
}
class EnclosedInInnerClass {
class Inner {
Closure cl = { this } (5)
}
void run() {
def inner = new Inner()
assert inner.cl() == inner (6)
}
}
class NestedClosures {
void run() {
def nestedClosures = {
def cl = { this } (7)
cl()
}
assert nestedClosures() == this (8)
}
}
1 | a closure is defined inside the Enclosing class, and returns getThisObject |
2 | calling the closure will return the instance of Enclosing where the the closure is defined |
3 | in general, you will just want to use the shortcut this notation |
4 | and it returns exactly the same object |
5 | if the closure is defined in a inner class |
6 | this in the closure will return the inner class, not the top-level one |
7 | in case of nested closures, like here cl being defined inside the scope of nestedClosures |
8 | then this corresponds to the closest outer class, not the enclosing closure! |
It is of course possible to call methods from the enclosing class this way:
class Person {
String name
int age
String toString() { "$name is $age years old" }
String dump() {
def cl = {
String msg = this.toString() (1)
println msg
msg
}
cl()
}
}
def p = new Person(name:'Janice', age:74)
assert p.dump() == 'Janice is 74 years old'
1 | the closure calls toString on this , which will actually call the toString method on the enclosing object,
that is to say the Person instance |
The owner of a closure is very similar to the definition of this in a closure with a subtle difference: it will return the direct enclosing object, be it a closure or a class:
class Enclosing {
void run() {
def whatIsOwnerMethod = { getOwner() } (1)
assert whatIsOwnerMethod() == this (2)
def whatIsOwner = { owner } (3)
assert whatIsOwner() == this (4)
}
}
class EnclosedInInnerClass {
class Inner {
Closure cl = { owner } (5)
}
void run() {
def inner = new Inner()
assert inner.cl() == inner (6)
}
}
class NestedClosures {
void run() {
def nestedClosures = {
def cl = { owner } (7)
cl()
}
assert nestedClosures() == nestedClosures (8)
}
}
1 | a closure is defined inside the Enclosing class, and returns getOwner |
2 | calling the closure will return the instance of Enclosing where the the closure is defined |
3 | in general, you will just want to use the shortcut owner notation |
4 | and it returns exactly the same object |
5 | if the closure is defined in a inner class |
6 | owner in the closure will return the inner class, not the top-level one |
7 | but in case of nested closures, like here cl being defined inside the scope of nestedClosures |
8 | then owner corresponds to the enclosing closure, hence a different object from this ! |
The delegate of a closure can be accessed by using the delegate
property or calling the getDelegate
method. It is a
powerful concept for building domain specific languages in Groovy. While closure-this and closure-owner
refer to the lexical scope of a closure, the delegate is a user defined object that a closure will use. By default, the
delegate is set to owner
:
class Enclosing {
void run() {
def cl = { getDelegate() } (1)
def cl2 = { delegate } (2)
assert cl() == cl2() (3)
assert cl() == this (4)
def enclosed = {
{ -> delegate }.call() (5)
}
assert enclosed() == enclosed (6)
}
}
1 | you can get the delegate of a closure calling the getDelegate method |
2 | or using the delegate property |
3 | both return the same object |
4 | which is the enclosing class or closure |
5 | in particular in case of nested closures |
6 | delegate will correspond to the owner |
The delegate of a closure can be changed to any object. Let’s illustrate this by creating two classes which are not
subclasses of each other but both define a property called name
:
class Person {
String name
}
class Thing {
String name
}
def p = new Person(name: 'Norman')
def t = new Thing(name: 'Teapot')
Then let’s define a closure which fetches the name
property on the delegate:
def upperCasedName = { delegate.name.toUpperCase() }
Then by changing the delegate of the closure, you can see that the target object will change:
upperCasedName.delegate = p
assert upperCasedName() == 'NORMAN'
upperCasedName.delegate = t
assert upperCasedName() == 'TEAPOT'
At this point, the behavior is not different from having a `variable defined in the lexical scope of the closure:
def target = p
def upperCasedNameUsingVar = { target.name.toUpperCase() }
assert upperCasedNameUsingVar() == 'NORMAN'
However there is are major differences:
-
in the last example, target is a local variable referenced from within the closure
-
the delegate can be used transparently, that is to say without prefixing method calls with
delegate.
as explained in the next paragraph.
Whenever, in a closure, a property is accessed without explicitly setting a receiver object, then a delegation strategy is involved:
class Person {
String name
}
def p = new Person(name:'Igor')
def cl = { name.toUpperCase() } (1)
cl.delegate = p (2)
assert cl() == 'IGOR' (3)
1 | name is not referencing a variable in the lexical scope of the closure |
2 | we can change the delegate of the closure to be an instance of Person |
3 | and the method call will succeed |
The reason this code works is that the name
property will be resolved transparently on the delegate
object! This is
a very powerful way to resolve properties or method calls inside closures. There’s no need to set an explicit delegate.
receiver: the call will be made because the default delegation strategy of the closure makes it so. A closure actually
defines multiple resolution strategies that you can choose:
-
Closure.OWNER_FIRST
is the default strategy. If a property/method exists on the owner, then it will be called on the owner. If not, then the delegate is used. -
Closure.DELEGATE_FIRST
reverses the logic: the delegate is used first, then the owner -
Closure.OWNER_ONLY
will only resolve the property/method lookup on the owner: the delegate will be ignored. -
Closure.DELEGATE_ONLY
will only resolve the property/method lookup on the delegate: the owner will be ignored. -
Closure.TO_SELF
can be used by developers who need advanced meta-programming techniques and wish to implement a custom resolution strategy: the resolution will not be made on the owner or the delegate but only on the closure class itself. It makes only sense to use this if you implement your own subclass ofClosure
.
Let’s illustrate the default "owner first" strategy with this code:
class Person {
String name
def pretty = { "My name is $name" } (1)
String toString() {
pretty()
}
}
class Thing {
String name (2)
}
def p = new Person(name: 'Sarah')
def t = new Thing(name: 'Teapot')
assert p.toString() == 'My name is Sarah' (3)
p.pretty.delegate = t (4)
assert p.toString() == 'My name is Sarah' (5)
1 | for the illustration, we define a closure member which references "name" |
2 | both the Person and the Thing class define a name property |
3 | Using the default strategy, the name property is resolved on the owner first |
4 | so if we change the delegate to t which is an instance of Thing |
5 | there is no change in the result: name is first resolved on the owner of the closure |
However, it is possible to change the resolution strategy of the closure:
p.pretty.resolveStrategy = Closure.DELEGATE_FIRST
assert p.toString() == 'My name is Teapot'
By changing the resolveStrategy
, we are modifying the way Groovy will resolve the "implicit this" references: in this
case, name
will first be looked in the delegate, then if not found, on the owner. Since name
is defined in the
delegate, an instance of Thing
, then this value is used.
The differene between "delegate first" and "delegate only" or "owner first" and "owner only" can be illustrated if one of the delegate (resp. owner) does not have such a method or property:
class Person {
String name
int age
def fetchAge = { age }
}
class Thing {
String name
}
def p = new Person(name:'Jessica', age:42)
def t = new Thing(name:'Printer')
def cl = p.fetchAge
cl.delegate = p
assert cl() == 42
cl.delegate = t
assert cl() == 42
cl.resolveStrategy = Closure.DELEGATE_ONLY
cl.delegate = p
assert cl() == 42
cl.delegate = t
try {
cl()
assert false
} catch (MissingPropertyException ex) {
// "age" is not defined on the delegate
}
In this example, we define two classes which both have a name
property but only the Person
class declares an age
.
The Person
class also declares a closure which references age
. We can change the default resolution strategy from
"owner first" to "delegate only". Since the owner of the closure is the Person
class, then we can check that if the
delegate is an instance of Person
, calling the closure is successful, but if we call it with a delegate being an
instance of Thing
, it fails with a groovy.lang.MissingPropertyException
. Despite the closure being defined inside
the Person
class, the owner is not used.
A comprehensive explanation about how to use this feature to develop DSLs can be found in a dedicated section of the manual. |
1.4.4. Semantics
This chapter covers the semantics of the Groovy programming language.
Statements
Variable definition
Variables can be defined using either their type (like String
) or by using the keyword def
:
String x
def o
def
is a replacement for a type name. In variable definitions it is used to indicate that you don’t care about the type. In variable definitions it is mandatory to either provide a type name explicitly or to use "def" in replacement. This is needed to the make variable definitions detectable for the Groovy parser.
You can think of def
as an alias of Object
and you will understand it in an instant.
Variable definition types can be refined by using generics, like in List<String> names .
To learn more about the generics support, please read the generics section.
|
Variable assignment
You can assign values to variables for later use. Try the following:
x = 1
println x
x = new java.util.Date()
println x
x = -3.1499392
println x
x = false
println x
x = "Hi"
println x
Groovy supports multiple assignment, i.e. where multiple variables can be assigned at once, e.g.:
def (a, b, c) = [10, 20, 'foo']
assert a == 10 && b == 20 && c == 'foo'
You can provide types as part of the declaration if you wish:
def (int i, String j) = [10, 'foo']
assert i == 10 && j == 'foo'
As well as used when declaring variables it also applies to existing variables:
def nums = [1, 3, 5]
def a, b, c
(a, b, c) = nums
assert a == 1 && b == 3 && c == 5
The syntax works for arrays as well as lists, as well as methods that return either of these:
def (_, month, year) = "18th June 2009".split()
assert "In $month of $year" == 'In June of 2009'
If the left hand side has too many variables, excess ones are filled with null’s:
def (a, b, c) = [1, 2]
assert a == 1 && b == 2 && c == null
If the right hand side has too many variables, the extra ones are ignored:
def (a, b) = [1, 2, 3]
assert a == 1 && b == 2
In the section describing the various Groovy operators,
the case of the subscript operator has been covered,
explaining how you can override the getAt()
/putAt()
method.
With this technique, we can combine multiple assignments and the subscript operator methods to implement object destructuring.
Consider the following immutable Coordinates
class, containing a pair of longitude and latitude doubles,
and notice our implementation of the getAt()
method:
@Immutable
class Coordinates {
double latitude
double longitude
double getAt(int idx) {
if (idx == 0) latitude
else if (idx == 1) longitude
else throw new Exception("Wrong coordinate index, use 0 or 1")
}
}
Now let’s instantiate this class and destructure its longitude and latitude:
def coordinates = new Coordinates(latitude: 43.23, longitude: 3.67) (1)
def (la, lo) = coordinates (2)
assert la == 43.23 (3)
assert lo == 3.67
1 | we create an instance of the Coordinates class |
2 | then, we use a multiple assignment to get the individual longitude and latitude values |
3 | and we can finally assert their values. |
Control structures
Groovy supports the usual if - else syntax from Java
def x = false
def y = false
if ( !x ) {
x = true
}
assert x == true
if ( x ) {
x = false
} else {
y = true
}
assert x == y
Groovy also supports the normal Java "nested" if then else if syntax:
if ( ... ) {
...
} else if (...) {
...
} else {
...
}
The switch statement in Groovy is backwards compatible with Java code; so you can fall through cases sharing the same code for multiple matches.
One difference though is that the Groovy switch statement can handle any kind of switch value and different kinds of matching can be performed.
def x = 1.23
def result = ""
switch ( x ) {
case "foo":
result = "found foo"
// lets fall through
case "bar":
result += "bar"
case [4, 5, 6, 'inList']:
result = "list"
break
case 12..30:
result = "range"
break
case Integer:
result = "integer"
break
case Number:
result = "number"
break
case ~/fo*/: // toString() representation of x matches the pattern?
result = "foo regex"
break
case { it < 0 }: // or { x < 0 }
result = "negative"
break
default:
result = "default"
}
assert result == "number"
Switch supports the following kinds of comparisons:
-
Class case values matches if the switch value is an instance of the class
-
Regular expression case values match if the
toString()
representation of the switch value matches the regex -
Collection case values match if the switch value is contained in the collection. This also includes ranges (since they are Lists)
-
Closure case values match if the calling the closure returns a result which is true according to the Groovy truth
-
If none of the above are used then the case value matches if the case value equals the switch value
default must go at the end of the switch/case. While in Java the default can be placed anywhere in the switch/case, the default in Groovy is used more as an else than assigning a default case.
|
when using a closure case value, the default it parameter is actually the switch value (in our example, variable x )
|
Groovy supports the standard Java / C for loop:
String message = ''
for (int i = 0; i < 5; i++) {
message += 'Hi '
}
assert message == 'Hi Hi Hi Hi Hi '
The for loop in Groovy is much simpler and works with any kind of array, collection, Map, etc.
// iterate over a range
def x = 0
for ( i in 0..9 ) {
x += i
}
assert x == 45
// iterate over a list
x = 0
for ( i in [0, 1, 2, 3, 4] ) {
x += i
}
assert x == 10
// iterate over an array
def array = (0..4).toArray()
x = 0
for ( i in array ) {
x += i
}
assert x == 10
// iterate over a map
def map = ['abc':1, 'def':2, 'xyz':3]
x = 0
for ( e in map ) {
x += e.value
}
assert x == 6
// iterate over values in a map
x = 0
for ( v in map.values() ) {
x += v
}
assert x == 6
// iterate over the characters in a string
def text = "abc"
def list = []
for (c in text) {
list.add(c)
}
assert list == ["a", "b", "c"]
Groovy also supports the Java colon variation with colons: for (char c : text) {} ,
where the type of the variable is mandatory.
|
You can specify a complete try-catch-finally
, a try-catch
, or a try-finally
set of blocks.
Braces are required around each block’s body. |
try {
'moo'.toLong() // this will generate an exception
assert false // asserting that this point should never be reached
} catch ( e ) {
assert e in NumberFormatException
}
We can put code within a finally clause following a matching try clause, so that regardless of whether the code in the try clause throws an exception, the code in the finally clause will always execute:
def z
try {
def i = 7, j = 0
try {
def k = i / j
assert false //never reached due to Exception in previous line
} finally {
z = 'reached here' //always executed even if Exception thrown
}
} catch ( e ) {
assert e in ArithmeticException
assert z == 'reached here'
}
Promotion and coercion (TBD)
Closure to type coercion
A SAM type is a type which defines a single abstract method. This includes:
interface Predicate<T> {
boolean accept(T obj)
}
abstract class Greeter {
abstract String getName()
void greet() {
println "Hello, $name"
}
}
Any closure can be converted into a SAM type using the as
operator:
Predicate filter = { it.contains 'G' } as Predicate
assert filter.accept('Groovy') == true
Greeter greeter = { 'Groovy' } as Greeter
greeter.greet()
However, the as Type
expression is optional since Groovy 2.2.0. You can omit it and simply write:
Predicate filter = { it.contains 'G' }
assert filter.accept('Groovy') == true
Greeter greeter = { 'Groovy' }
greeter.greet()
which means you are also allowed to use method pointers, as shown in the following example:
boolean doFilter(String s) { s.contains('G') }
Predicate filter = this.&doFilter
assert filter.accept('Groovy') == true
Greeter greeter = GroovySystem.&getVersion
greeter.greet()
The second and probably more important use case for closure to SAM type coercion is calling a method which accepts a SAM type. Imagine the following method:
public <T> List<T> filter(List<T> source, Predicate<T> predicate) {
source.findAll { predicate.accept(it) }
}
Then you can call it with a closure, without having to create an explicit implementation of the interface:
assert filter(['Java','Groovy'], { it.contains 'G'} as Predicate) == ['Groovy']
But since Groovy 2.2.0, you are also able to omit the explicit coercion and call the method as if it used a closure:
assert filter(['Java','Groovy']) { it.contains 'G'} == ['Groovy']
As you can see, this has the advantage of letting you use the closure syntax for method calls, that is to say put the closure outside of the parenthesis, improving the readability of your code.
In addition to SAM types, a closure can be coerced to any type and in particular interfaces. Let’s define the following interface:
interface FooBar {
int foo()
void bar()
}
You can coerce a closure into the interface using the as
keyword:
def impl = { println 'ok'; 123 } as FooBar
This produces a class for which all methods are implemented using the closure:
assert impl.foo() == 123
impl.bar()
But it is also possible to coerce a closure to any class. For example, we can replace the interface
that we defined
with class
without changing the assertions:
class FooBar {
int foo() { 1 }
void bar() { println 'bar' }
}
def impl = { println 'ok'; 123 } as FooBar
assert impl.foo() == 123
impl.bar()
Map to type coercion
Usually using a single closure to implement an interface or a class with multiple methods is not the way to go. As an
alternative, Groovy allows you to coerce a map into an interface or a class. In that case, keys of the map are
interpreted as method names, while the values are the method implementation. The following example illustrates the
coercion of a map into an Iterator
:
def map
map = [
i: 10,
hasNext: { map.i > 0 },
next: { map.i-- },
]
def iter = map as Iterator
Of course this is a rather contrived example, but illustrates the concept. You only need to implement those methods
that are actually called, but if a method is called that doesn’t exist in the map a MissingMethodException
or an
UnsupportedOperationException
is thrown, depending on the arguments passed to the call,
as in the following example:
interface X {
void f()
void g(int n)
void h(String s, int n)
}
x = [ f: {println "f called"} ] as X
x.f() // method exists
x.g() // MissingMethodException here
x.g(5) // UnsupportedOperationException here
The type of the exception depends on the call itself:
-
MissingMethodException
if the arguments of the call do not match those from the interface/class -
UnsupportedOperationException
if the arguments of the call match one of the overloaded methods of the interface/class
String to enum coercion
Groovy allows transparent String
(or GString
) to enum values coercion. Imagine you define the following enum:
enum State {
up,
down
}
then you can assign a string to the enum without having to use an explicit as
coercion:
State st = 'up'
assert st == State.up
It is also possible to use a GString
as the value:
def val = "up"
State st = "${val}"
assert st == State.up
However, this would throw a runtime error (IllegalArgumentException
):
State st = 'not an enum value'
Note that it is also possible to use implicit coercion in switch statements:
State switchState(State st) {
switch (st) {
case 'up':
return State.down // explicit constant
case 'down':
return 'up' // implicit coercion for return types
}
}
in particular, see how the case
use string constants. But if you call a method that uses an enum with a String
argument, you still have to use an explicit as
coercion:
assert switchState('up' as State) == State.down
assert switchState(State.down) == State.up
Custom type coercion
It is possible for a class to define custom coercion strategies by implementing the asType
method. Custom coercion
is invoked using the as
operator and is never implicit. As an example,
imagine you defined two classes, Polar
and Cartesian
, like in the following example:
class Polar {
double r
double phi
}
class Cartesian {
double x
double y
}
And that you want to convert from polar coordinates to cartesian coordinates. One way of doing this is to define
the asType
method in the Polar
class:
def asType(Class target) {
if (Cartesian==target) {
return new Cartesian(x: r*cos(phi), y: r*sin(phi))
}
}
which allows you to use the as
coercion operator:
def sigma = 1E-16
def polar = new Polar(r:1.0,phi:PI/2)
def cartesian = polar as Cartesian
assert abs(cartesian.x-sigma) < sigma
Putting it all together, the Polar
class looks like this:
class Polar {
double r
double phi
def asType(Class target) {
if (Cartesian==target) {
return new Cartesian(x: r*cos(phi), y: r*sin(phi))
}
}
}
but it is also possible to define asType
outside of the Polar
class, which can be practical if you want to define
custom coercion strategies for "closed" classes or classes for which you don’t own the source code, for example using
a metaclass:
Polar.metaClass.asType = { Class target ->
if (Cartesian==target) {
return new Cartesian(x: r*cos(phi), y: r*sin(phi))
}
}
Class literals vs variables and the as operator
Using the as
keyword is only possible if you have a static reference to a class, like in the following code:
interface Greeter {
void greet()
}
def greeter = { println 'Hello, Groovy!' } as Greeter // Greeter is known statically
greeter.greet()
But what if you get the class by reflection, for example by calling Class.forName
?
Class clazz = Class.forName('Greeter')
Trying to use the reference to the class with the as
keyword would fail:
greeter = { println 'Hello, Groovy!' } as clazz
// throws:
// unable to resolve class clazz
// @ line 9, column 40.
// greeter = { println 'Hello, Groovy!' } as clazz
It is failing because the as
keyword only works with class literals. Instead, you need to call the asType
method:
greeter = { println 'Hello, Groovy!' }.asType(clazz)
greeter.greet()
The Groovy Truth
Groovy decides whether a expression is true or false by applying the rules given below.
Iterators and Enumerations
Iterators and Enumerations with further elements are coerced to true.
assert [0].iterator()
assert ![].iterator()
Vector v = [0] as Vector
Enumeration enumeration = v.elements()
assert enumeration
enumeration.nextElement()
assert !enumeration
Typing
Optional typing
Optional typing is the idea that a program can work even if you don’t put an explicit type on a variable. Being a dynamic language, Groovy naturally implements that feature, for example when you declare a variable:
String aString = 'foo' (1)
assert aString.toUpperCase() (2)
1 | foo is declared using an explicit type, String |
2 | we can call the toUpperCase method on a String |
Groovy will let you write this instead:
def aString = 'foo' (1)
assert aString.toUpperCase() (2)
1 | foo is declared using def |
2 | we can still call the toUpperCase method, because the type of aString is resolved at runtime |
So it doesn’t matter that you use an explicit type here. It is in particular interesting when you combine this feature with static type checking, because the type checker performs type inference.
Likewise, Groovy doesn’t make it mandatory to declare the types of a parameter in a method:
String concat(String a, String b) {
a+b
}
assert concat('foo','bar') == 'foobar'
can be rewritten using def
as both return type and parameter types, in order to take advantage of duck typing, as
illustrated in this example:
def concat(def a, def b) { (1)
a+b
}
assert concat('foo','bar') == 'foobar' (2)
assert concat(1,2) == 3 (3)
1 | both the return type and the parameter types use def |
2 | it makes it possible to use the method with String |
3 | but also with int`s since the `plus method is defined |
Using the def keyword here is recommanded to describe the intent of a method which is supposed to work on any
type, but technically, we could use Object instead and the result would be the same: def is, in Groovy, strictly
equivalent to using Object .
|
Eventually, the type can be removed altogether from both the return type and the descriptor. But if you want to remove it from the return type, you then need to add an explicit modifier for the method, so that the compiler can make a difference between a method declaration and a method call, like illustrated in this example:
private concat(a,b) { (1)
a+b
}
assert concat('foo','bar') == 'foobar' (2)
assert concat(1,2) == 3 (3)
1 | if we want to omit the return type, an explicit modifier has to be set. |
2 | it is still possible to use the method with String |
3 | and also with `int`s |
Omitting types is in general considered a bad practice in method parameters or method return types for public APIs.
While using def in a local variable is not really a problem because the visibility of the variable is limited to the
method itself, while set on a method parameter, def will be converted to Object in the method signature, making it
difficult for users to know which is the expected type of the arguments. This means that you should limit this to cases
where you are explicitly relying on duck typing.
|
Static type checking
By default, Groovy performs minimal type checking at compile time. Since it is primarily a dynamic language, most checks that a static compiler would normally do aren’t possible at compile time. A method added via runtime metaprogramming might alter a class or object’s runtime behavior. Let’s illustrate why in the following example:
class Person { (1)
String firstName
String lastName
}
def p = new Person(firstName: 'Raymond', lastName: 'Devos') (2)
assert p.formattedName == 'Raymond Devos' (3)
1 | the Person class only defines two properties, firstName and lastName |
2 | we can create an instance of Person |
3 | and call a method named formattedName |
It is quite common in dynamic languages for code such as the above example not to throw any error. How can this be?
In Java, this would typically fail at compile time. However, in Groovy, it will not fail at compile time, and if coded
correctly, will also not fail at runtime. In fact, to make this work at runtime, one possibility is to rely on
runtime metaprogramming. So just adding this line after the declaration of the Person
class is enough:
Person.metaClass.getFormattedName = { "$delegate.firstName $delegate.lastName" }
This means that in general, in Groovy, you can’t make any assumption about the type of an object beyond its declaration type, and even if you know it, you can’t determine at compile time what method will be called, or which property will be retrieved, and this is perfectly fine. This is how dynamic languages work, and it has a lot of interest.
However, if your program doesn’t rely on dynamic features and that you come from the static world (in particular, from
a Java mindset), not catching such "errors" at compile time can be surprising. As we have seen in the previous example,
the compiler cannot be sure this is an error. To make it aware that it is, you have to explicitly instruct the compiler
that you are switching to a type checked mode. This can be done by annotating a class or a method with @groovy.lang.TypeChecked
.
When type checking is activated, the compiler performs much more work:
-
type inference is activated, meaning that even if you use
def
on a local variable for example, the type checker will be able to infer the type of the variable from the assignments -
method calls are resolved at compile time, meaning that if a method is not declared on a class, the compiler will throw an error
-
in general, all the compile time errors that you are used to find in a static language will appear: method not found, property not found, incompatible types for method calls, number precision errors, …
In this section, we will describe the behavior of the type checker in various situations and explain the limits of using
@TypeChecked
on your code.
@TypeChecked
annotationThe groovy.lang.TypeChecked
annotation enabled type checking. It can be placed on a class:
@groovy.transform.TypeChecked
class Calculator {
int sum(int x, int y) { x+y }
}
Or on a method:
class Calculator {
@groovy.transform.TypeChecked
int sum(int x, int y) { x+y }
}
In the first case, all methods, properties, fields, inner classes, … of the annotated class will be type checked, whereas in the second case, only the method and potential closures or anonymous inner classes that it contains will be type checked.
The scope of type checking can be restricted. For example, if a class is type checked, you can instruct the type checker
to skip a method by annotating it with @TypeChecked(TypeCheckingMode.SKIP)
:
import groovy.transform.TypeChecked
import groovy.transform.TypeCheckingMode
@TypeChecked (1)
class GreetingService {
String greeting() { (2)
doGreet()
}
@TypeChecked(TypeCheckingMode.SKIP) (3)
private String doGreet() {
def b = new SentenceBuilder()
b.Hello.my.name.is.John (4)
b
}
}
def s = new GreetingService()
assert s.greeting() == 'Hello my name is John'
1 | the GreetingService class is marked as type checked |
2 | so the greeting method is automatically type checked |
3 | but doGreet is marked with SKIP |
4 | the type checker doesn’t complain about missing properties here |
In the previous example, SentenceBuilder
relies on dynamic code. There’s no real Hello
method or property, so the
type checker would normally complain and compilation would fail. Since the method that uses the builder is marked with
TypeCheckingMode.SKIP
, type checking is skipped for this method, so the code will compile, even if the rest of the
class is type checked.
The following sections describe the semantics of type checking in Groovy.
An object o
of type A
can be assigned to a variable of type T
if and only if:
-
T
equalsA
Date now = new Date()
-
or
T
is one ofString
,boolean
,Boolean
orClass
String s = new Date() // implicit call to toString Boolean boxed = 'some string' // Groovy truth boolean prim = 'some string' // Groovy truth Class clazz = 'java.lang.String' // class coercion
-
or
o
is null andT
is not a primitive typeString s = null // passes int i = null // fails
-
or
T
is an array andA
is an array and the component type ofA
is assignable to the component type ofT
int[] i = new int[4] // passes int[] i = new String[4] // fails
-
or
T
is an array andA
is a list and the component type ofA
is assignable to the component type ofT
int[] i = [1,2,3] // passes int[] i = [1,2, new Date()] // fails
-
or
T
is a superclass ofA
AbstractList list = new ArrayList() // passes LinkedList list = new ArrayList() // fails
-
or
T
is an interface implemented byA
List list = new ArrayList() // passes RandomAccess list = new LinkedList() // fails
-
or
T
orA
are a primitive type and their boxed types are assignableint i = 0 Integer bi = 1 int x = new Integer(123) double d = new Float(5f)
-
or
T
extendsgroovy.lang.Closure
andA
is a SAM-type (single abstract method type)Runnable r = { println 'Hello' } interface SAMType { int doSomething() } SAMType sam = { 123 } assert sam.doSomething() == 123 abstract class AbstractSAM { int calc() { 2* value() } abstract int value() } AbstractSAM c = { 123 } assert c.calc() == 246
-
or
T
andA
derive fromjava.lang.Number
and conform to the following table
T | A | Examples |
---|---|---|
Double |
Any but BigDecimal or BigInteger |
|
Float |
Any type but BigDecimal, BigInteger or Double |
|
Long |
Any type but BigDecimal, BigInteger, Double or Float |
|
Integer |
Any type but BigDecimal, BigInteger, Double, Float or Long |
|
Short |
Any type but BigDecimal, BigInteger, Double, Float, Long or Integer |
|
Byte |
Byte |
|
In addition to the assignment rules above, if an assignment is deemed invalid, in type checked mode, a list literal or a map literal A
can be assigned
to a variable of type T
if:
-
the assignment is a variable declaration and
A
is a list literal andT
has a constructor whose parameters match the types of the elements in the list literal -
the assignment is a variable declaration and
A
is a map literal andT
has a no-arg constructor and a property for each of the map keys
For example, instead of writing:
@groovy.transform.TupleConstructor
class Person {
String firstName
String lastName
}
Person classic = new Person('Ada','Lovelace')
You can use a "list constructor":
Person list = ['Ada','Lovelace']
or a "map constructor":
Person map = [firstName:'Ada', lastName:'Lovelace']
If you use a map constructor, additional checks are done on the keys of the map to check if a property of the same name is defined. For example, the following will fail at compile time:
@groovy.transform.TupleConstructor
class Person {
String firstName
String lastName
}
Person map = [firstName:'Ada', lastName:'Lovelace', age: 24] (1)
1 | The type checker will throw an error No such property: age for class: Person at compile time |
In type checked mode, methods are resolved at compile time. Resolution works by name and arguments. The return type is irrelevant to method selection. Types of arguments are matched against the types of the parameters following those rules:
An argument o
of type A
can be used for a parameter of type T
if and only if:
-
T
equalsA
int sum(int x, int y) { x+y } assert sum(3,4) == 7
-
or
T
is aString
andA
is aGString
String format(String str) { "Result: $str" } assert format("${3+4}") == "Result: 7"
-
or
o
is null andT
is not a primitive typeString format(int value) { "Result: $value" } assert format(7) == "Result: 7" format(null) // fails
-
or
T
is an array andA
is an array and the component type ofA
is assignable to the component type ofT
String format(String[] values) { "Result: ${values.join(' ')}" } assert format(['a','b'] as String[]) == "Result: a b" format([1,2] as int[]) // fails
-
or
T
is a superclass ofA
String format(AbstractList list) { list.join(',') } format(new ArrayList()) // passes String format(LinkedList list) { list.join(',') } format(new ArrayList()) // fails
-
or
T
is an interface implemented byA
String format(List list) { list.join(',') } format(new ArrayList()) // passes String format(RandomAccess list) { 'foo' } format(new LinkedList()) // fails
-
or
T
orA
are a primitive type and their boxed types are assignableint sum(int x, Integer y) { x+y } assert sum(3, new Integer(4)) == 7 assert sum(new Integer(3), 4) == 7 assert sum(new Integer(3), new Integer(4)) == 7 assert sum(new Integer(3), 4) == 7
-
or
T
extendsgroovy.lang.Closure
andA
is a SAM-type (single abstract method type)interface SAMType { int doSomething() } int twice(SAMType sam) { 2*sam.doSomething() } assert twice { 123 } == 246 abstract class AbstractSAM { int calc() { 2* value() } abstract int value() } int eightTimes(AbstractSAM sam) { 4*sam.calc() } assert eightTimes { 123 } == 984
-
or
T
andA
derive fromjava.lang.Number
and conform to the same rules as assignment of numbers
If a method with the appropriate name and arguments is not found at compile time, an error is thrown. The difference with "normal" Groovy is illustrated in the following example:
class MyService {
void doSomething() {
printLine 'Do something' (1)
}
}
1 | printLine is an error, but since we’re in a dynamic mode, the error is not caught at compile time |
The example above shows a class that Groovy will be able to compile. However, if you try to create an instance of MyService
and call the
doSomething
method, then it will fail at runtime, because printLine
doesn’t exist. Of course, we already showed how Groovy could make
this a perfectly valid call, for example by catching MethodMissingException
or implementing a custom meta-class, but if you know you’re
not in such a case, @TypeChecked
comes handy:
class MyService {
void doSomething() {
printLine 'Do something' (1)
}
}
1 | printLine is this time a compile-time error |
Just adding @TypeChecked
will trigger compile time method resolution. The type checker will try to find a method printLine
accepting
a String
on the MyService
class, but cannot find one. It will fail compilation with the following message:
Cannot find matching method MyService#printLine(java.lang.String)
It is important to understand the logic behind the type checker: it is a compile-time check, so by definition, the type checker
is not aware of any kind of runtime metaprogramming that you do. This means that code which is perfectly valid without @TypeChecked will
not compile anymore if you activate type checking. This is in particular true if you think of duck typing: |
class Duck {
void quack() { (1)
println 'Quack!'
}
}
class QuackingBird {
void quack() { (2)
println 'Quack!'
}
}
@groovy.transform.TypeChecked
void accept(quacker) {
quacker.quack() (3)
}
accept(new Duck()) (4)
1 | we define a Duck class which defines a quack method |
2 | we define another QuackingBird class which also defines a quack method |
3 | quacker is loosely typed, so since the method is @TypeChecked , we will obtain a compile-time error |
4 | even if in non type-checked Groovy, this would have passed |
There are possible workarounds, like introducing an interface, but basically, by activating type checking, you gain type safety but you loose some features of the language. Hopefully, Groovy introduces some features like flow typing to reduce the gap between type-checked and non type-checked Groovy.
When code is annotated with @TypeChecked
, the compiler performs type inference. It doesn’t simply rely on static types, but also uses various
techniques to infer the types of variables, return types, literals, … so that the code remains as clean as possible even if you activate the
type checker.
The simplest example is infering the type of a variable:
def message = 'Welcome to Groovy!' (1)
println message.toUpperCase() (2)
println message.upper() // compile time error (3)
1 | a variable is declared using the def keyword |
2 | calling toUpperCase is allowed by the type checker |
3 | calling upper will fail at compile time |
The reason the call to toUpperCase
works is because the type of message
was inferred as being a String
.
It is worth noting that although the compiler performs type inference on local variables, it does not perform any kind of type inference on fields, always falling back to the declared type of a field. To illustrate this, let’s take a look at this example:
class SomeClass {
def someUntypedField (1)
String someTypedField (2)
void someMethod() {
someUntypedField = '123' (3)
someUntypedField = someUntypedField.toUpperCase() // compile-time error (4)
}
void someSafeMethod() {
someTypedField = '123' (5)
someTypedField = someTypedField.toUpperCase() (6)
}
void someMethodUsingLocalVariable() {
def localVariable = '123' (7)
someUntypedField = localVariable.toUpperCase() (8)
}
}
1 | someUntypedField uses def as a declaration type |
2 | someTypedField uses String as a declaration type |
3 | we can assign anything to someUntypedField |
4 | yet calling toUpperCase fails at compile time because the field is not typed properly |
5 | we can assign a String to a field of type String |
6 | and this time toUpperCase is allowed |
7 | if we assign a String to a local variable |
8 | then calling toUpperCase is allowed on the local variable |
Why such a difference? The reason is thread safety. At compile time, we can’t make any guarantee about the type of a field. Any thread can access any field at any time and between the moment a field is assigned a variable of some type in a method and the time is is used the line after, another thread may have changed the contents of the field. This is not the case for local variables: we know if they "escape" or not, so we can make sure that the type of a variable is constant (or not) over time. Note that even if a field is final, the JVM makes no guarantee about it, so the type checker doesn’t behave differently if a field is final or not.
This is one of the reasons why we recommend to use typed fields. While using def for local variables is perfectly
fine thanks to type inference, this is not the case for fields, which also belong to the public API of a class, hence the
type is important.
|
Groovy provides a syntax for various type literals. There are three native collection literals in Groovy:
-
lists, using the
[]
literal -
maps, using the
[:]
literal -
ranges, using the
(..,..)
literal
The inferred type of a literal depends on the elements of the literal, as illustrated in the following table:
Literal | Inferred type |
---|---|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
As you can see, with the noticeable exception of the IntRange
, the inferred type makes use of generics types to describe
the contents of a collection. In case the collection contains elements of different types, the type checker still performs
type inference of the components, but uses the notion of least upper bound.
In Groovy, the least upper bound of two types A
and B
is defined as a type which:
-
superclass corresponds to the common super class of
A
andB
-
interfaces correspond to the interfaces implemented by both
A
andB
-
if
A
orB
is a primitive type and thatA
isn’t equal toB
, the least upper bound ofA
andB
is the least upper bound of their wrapper types
If A
and B
only have one (1) interface in common and that their common superclass is Object
, then the LUB of both
is the common interface.
The least upper bound represents the minimal type to which both A
and B
can be assigned. So for example, if A
and B
are both String
, then the LUB (least upper bound) of both is also String
.
class Top {}
class Bottom1 extends Top {}
class Bottom2 extends Top {}
assert leastUpperBound(String, String) == String (1)
assert leastUpperBound(ArrayList, LinkedList) == AbstractList (2)
assert leastUpperBound(ArrayList, List) == List (3)
assert leastUpperBound(List, List) == List (4)
assert leastUpperBound(Bottom1, Bottom2) == Top (5)
assert leastUpperBound(List, Serializable) == Object (6)
1 | the LUB of String and String is String |
2 | the LUB of ArrayList and LinkedList is their common super type, AbstractList |
3 | the LUB of ArrayList and List is their only common interface, List |
4 | the LUB of two identical interfaces is the interface itself |
5 | the LUB of Bottom1 and Bottom2 is their superclass Top |
6 | the LUB of two types which have nothing in common is Object |
In those examples, the LUB is always representable as a normal, JVM supported, type. But Groovy internally represents the LUB as a type which can be more complex, and that you wouldn’t be able to use to define a variable for example. To illustrate this, let’s continue with this example:
interface Foo {}
class Top {}
class Bottom extends Top implements Serializable, Foo {}
class SerializableFooImpl implements Serializable, Foo {}
What is the least upper bound of Bottom
and SerializableFooImpl
? They don’t have a common super class (apart from Object
),
but they do share 2 interfaces (Serializable
and Foo
), so their least upper bound is a type which represents the union of
two interfaces (Serializable
and Foo
). This type cannot be defined in the source code, yet Groovy knows about it.
In the context of collection type inference (and generic type inference in general), this becomes handy, because the type of the components is inferred as the least upper bound. We can illustrate why this is important in the following example:
interface Greeter { void greet() } (1)
interface Salute { void salute() } (2)
class A implements Greeter, Salute { (3)
void greet() { println "Hello, I'm A!" }
void salute() { println "Bye from A!" }
}
class B implements Greeter, Salute { (4)
void greet() { println "Hello, I'm B!" }
void salute() { println "Bye from B!" }
void exit() { println 'No way!' } (5)
}
def list = [new A(), new B()] (6)
list.each {
it.greet() (7)
it.salute() (8)
it.exit() (9)
}
1 | the Greeter interface defines a single method, greet |
2 | the Salute interface defines a single method, salute |
3 | class A implements both Greeter and Salute but there’s no explicit interface extending both |
4 | same for B |
5 | but B defines an additional exit method |
6 | the type of list is inferred as "list of the LUB of A and B " |
7 | so it is possible to call greet which is defined on both A and B through the Greeter interface |
8 | and it is possible to call salut which is defined on both A and B through the Salut interface |
9 | yet calling exit is a compile time error because it doesn’t belong to the LUB of A and B (only defined in B ) |
The error message will look like:
[Static type checking] - Cannot find matching method Greeter or Salute#exit()
which indicates that the exit
method is neither defines on Greeter
nor Salute
, which are the two interfaces defined
in the least upper bound of A
and B
.
In normal, non type checked, Groovy, you can write things like:
class Greeter {
String greeting() { 'Hello' }
}
void doSomething(def o) {
if (o instanceof Greeter) { (1)
println o.greeting() (2)
}
}
doSomething(new Greeter())
1 | guard the method call with an instanceof check |
2 | make the call |
The method call works because of dynamic dispatch (the method is selected at runtime). The equivalent code in Java would
require to cast o
to a Greeter
before calling the greeting
method, because methods are selected at compile time:
if (o instanceof Greeter) {
System.out.println(((Greeter)o).greeting());
}
However, in Groovy, even if you add @TypeChecked
(and thus activate type checking) on the doSomething
method, the
cast is not necessary. The compiler embeds instanceof inference that makes the cast optional.
Flow typing is an important concept of Groovy in type checked mode and an extension of type inference. The idea is that the compiler is capable of infering the type of variables in the flow of the code, not just at initialization:
@groovy.transform.TypeChecked
void flowTyping() {
def o = 'foo' (1)
o = o.toUpperCase() (2)
o = 9d (3)
o = Math.sqrt(o) (4)
}
1 | first, o is declared using def and assigned a String |
2 | the compiler inferred that o is a String , so calling toUpperCase is allowed |
3 | o is reassigned with a double |
4 | calling Math.sqrt passes compilation because the compiler knows that at this point, o is a double |
So the type checker is aware of the fact that the concrete type of a variable is different over time. In particular, if you replace the last assignment with:
o = 9d
o = o.toUpperCase()
The type checker will now fail at compile time, because it knows that o
is a double
when toUpperCase
is called,
so it’s a type error.
It is important to understand that it is not the fact of declaring a variable with def
that triggers type inference.
Flow typing works for any variable of any type. Declaring a variable with an explicit type only constraints what you
can assign to a variable:
@groovy.transform.TypeChecked
void flowTypingWithExplicitType() {
List list = ['a','b','c'] (1)
list = list*.toUpperCase() (2)
list = 'foo' (3)
}
1 | list is declared as an unchecked List and assigned a list literal of `String`s |
2 | this line passes compilation because of flow typing: the type checker knows that list is at this point a List<String> |
3 | but you can’t assign a String to a List so this is a type checking error |
You can also note that even if the variable is declared without generics information, the type checker knows what is the component type. Therefore, such code would fail compilation:
@groovy.transform.TypeChecked
void flowTypingWithExplicitType() {
List list = ['a','b','c'] (1)
list.add(1) (2)
}
1 | list is inferred as List<String> |
2 | so adding an int to a List<String> is a compile-time error |
Fixing this requires adding an explicit generic type to the declaration:
@groovy.transform.TypeChecked
void flowTypingWithExplicitType() {
List<? extends Serializable> list = [] (1)
list.addAll(['a','b','c']) (2)
list.add(1) (3)
}
1 | list declared as List<? extends Serializable> and initialized with an empty list |
2 | elements added to the list conform to the declaration type of the list |
3 | so adding an int to a List<? extends Serializable> is allowed |
Flow typing has been introduced to reduce the difference in semantics between classic and static Groovy. In particular, consider the behavior of this code in Java:
public Integer compute(String str) {
return str.length();
}
public String compute(Object o) {
return "Nope";
}
// ...
Object string = "Some string"; (1)
Object result = compute(string); (2)
System.out.println(result); (3)
1 | o is declared as an Object and assigned a String |
2 | we call the compute method with o |
3 | and print the result |
In Java, this code will output 0
, because method selection is done at compile time and based on the declared types.
So even if o
is a String
at runtime, it is still the Object
version which is called, because o
has been declared
as an Object
. To be short, in Java, declared types are most important, be it variable types, parameter types or return
types.
In Groovy, we could write:
int compute(String string) { string.length() }
String compute(Object o) { "Nope" }
Object o = 'string'
def result = compute(o)
println result
But this time, it will return 6
, because the method which is chosen is chosen at runtime, based on the actual
argument types. So at runtime, o
is a String
so the String
variant is used. Note that this behavior has nothing
to do with type checking, it’s the way Groovy works in general: dynamic dispatch.
In type checked Groovy, we want to make sure the type checker selects the same method at compile time, that the runtime
would choose. It is not possible in general, due to the semantics of the language, but we can make things better with flow
typing. With flow typing, o
is inferred as a String
when the compute
method is called, so the version which takes
a String
and returns an int
is chosen. This means that we can infer the return type of the method to be an int
, and
not a String
. This is important for subsequent calls and type safety.
So in type checked Groovy, flow typing is a very important concept, which also implies that if @TypeChecked
is applied,
methods are selected based on the inferred types of the arguments, not on the declared types. This doesn’t ensure 100%
type safety, because the type checker may select a wrong method, but it ensures the closest semantics to dynamic Groovy.
A combination of flow typing and least upper bound inference is used to perform advanced type inference and ensure type safety in multiple situations. In particular, program control structures are likely to alter the inferred type of a variable:
class Top {
void methodFromTop() {}
}
class Bottom extends Top {
void methodFromBottom() {}
}
def o
if (someCondition) {
o = new Top() (1)
} else {
o = new Bottom() (2)
}
o.methodFromTop() (3)
o.methodFromBottom() // compilation error (4)
1 | if someCondition is true, o is assigned a Top |
2 | if someCondition is false, o is assigned a Bottom |
3 | calling methodFromTop is safe |
4 | but calling methodFromBottom is not, so it’s a compile time error |
When the type checker visits an if/else
control structure, it checks all variables which are assigned in if/else
branches
and computes the least upper bound of all assignments. This type is the type of the inferred variable
after the if/else
block, so in this example, o
is assigned a Top
in the if
branch and a Bottom
in the else
branch. The LUB of those is a Top
, so after the conditional branches, the compiler infers o
as being
a Top
. Calling methodFromTop
will therefore be allowed, but not methodFromBottom
.
The same reasoning exists with closures and in particular closure shared variables. A closure shared variable is a variable which is defined outside of a closure, but used inside a closure, as in this example:
def text = 'Hello, world!' (1)
def closure = {
println text (2)
}
1 | a variable named text is declared |
2 | text is used from inside a closure. It is a closure shared variable. |
Groovy allows developers to use those variables without requiring them to be final. This means that a closure shared variable can be reassigned inside a closure:
String result
doSomething { String it ->
result = "Result: $it"
}
result = result?.toUpperCase()
The problem is that a closure is an independent block of code that can be executed (or not) at any time. In particular,
doSomething
may be asynchronous, for example. This means that the body of a closure doesn’t belong to the main control
flow. For that reason, the type checker also computes, for each closure shared variable, the LUB of all
assignments of the variable, and will use that LUB
as the inferred type outside of the scope of the closure, like in
this example:
class Top {
void methodFromTop() {}
}
class Bottom extends Top {
void methodFromBottom() {}
}
def o = new Top() (1)
Thread.start {
o = new Bottom() (2)
}
o.methodFromTop() (3)
o.methodFromBottom() // compilation error (4)
1 | a closure-shared variable is first assigned a Top |
2 | inside the closure, it is assigned a Bottom |
3 | methodFromTop is allowed |
4 | methodFromBottom is a compilation error |
Here, it is clear that when methodFromBottom
is called, there’s no guarantee, at compile-time or runtime that the
type of o
will effectively be a Bottom
. There are chances that it will be, but we can’t make sure, because it’s
asynchronous. So the type checker will only allow calls on the least upper bound, which is here a Top
.
The type checker performs special inference on closures, resulting on additional checks on one side and improved fluency on the other side.
The first thing that the type checker is capable of doing is infering the return type of a closure. This is simply illustrated in the following example:
@groovy.transform.TypeChecked
int testClosureReturnTypeInference(String arg) {
def cl = { "Arg: $arg" } (1)
def val = cl() (2)
val.length() (3)
}
1 | a closure is defined, and it returns a string (more precisely a GString ) |
2 | we call the closure and assign the result to a variable |
3 | the type checker inferred that the closure would return a string, so calling length() is allowed |
As you can see, unlike a method which declares its return type explicitly, there’s no need to declare the return type of a closure: its type is inferred from the body of the closure.
In addition to the return type, it is possible for a closure to infer its parameter types from the context. There are two ways for the compiler to infer the parameter types:
-
through implicit SAM type coercion
-
through API metadata
To illustrate this, lets start with an example that will fail compilation due to the inability for the type checker to infer the parameter types:
class Person {
String name
int age
}
void inviteIf(Person p, Closure<Boolean> predicate) { (1)
if (predicate.call(p)) {
// send invite
// ...
}
}
@groovy.transform.TypeChecked
void failCompilation() {
Person p = new Person(name: 'Gerard', age: 55)
inviteIf(p) { (2)
it.age >= 18 // No such property: age (3)
}
}
1 | the inviteIf method accepts a Person and a Closure |
2 | we call it with a Person and a Closure |
3 | yet it is not statically known as being a Person and compilation fails |
In this example, the closure body contains it.age
. With dynamic, not type checked code, this would work, because the
type of it
would be a Person
at runtime. Unfortunately, at compile-time, there’s no way to know what is the type
of it
, just by reading the signature of inviteIf
.
To be short, the type checker doesn’t have enough contextual information on the inviteIf
method to determine statically
the type of it
. This means that the method call needs to be rewritten like this:
inviteIf(p) { Person it -> (1)
it.age >= 18
}
1 | the type of it needs to be declared explicitly |
By explicitly declaring the type of the it
variable, you can workaround the problem and make this code statically
checked.
For an API or framework designer, there are two ways to make this more elegant for users, so that they don’t have to declare an explicit type for the closure parameters. The first one, and easiest, is to replace the closure with a SAM type:
interface Predicate<On> { boolean apply(On e) } (1)
void inviteIf(Person p, Predicate<Person> predicate) { (2)
if (predicate.apply(p)) {
// send invite
// ...
}
}
@groovy.transform.TypeChecked
void passesCompilation() {
Person p = new Person(name: 'Gerard', age: 55)
inviteIf(p) { (3)
it.age >= 18 (4)
}
}
1 | declare a SAM interface with an apply method |
2 | inviteIf now uses a Predicate<Person> instead of a Closure<Boolean> |
3 | there’s no need to declare the type of the it variable anymore |
4 | it.age compiles properly, the type of it is inferred from the Predicate#apply method signature |
By using this technique, we leverage the automatic coercion of closures to SAM types feature of Groovy. The question whether you should use a SAM type or a Closure really depends on what you need to do. In a lot of cases, using a SAM interface is enough, especially if you consider functional interfaces as they are found in Java 8. However, closures provide features that are not accessible to functional interfaces. In particular, closures can have a delegate, and owner and can be manipulated as objects (for example, cloned, serialized, curried, …) before being called. They can also support multiple signatures (polymorphism). So if you need that kind of manipulation, it is preferable to switch to the most advanced type inference annotations which are described below. |
The original issue that needs to be solved when it comes to closure parameter type inference, that is to say, statically determining the types of the arguments of a closure without having to have them explicitly declared, is that the Groovy type system inherits the Java type system, which is insufficient to describe the types of the arguments.
@ClosureParams
annotationGroovy provides an annotation, @ClosureParams
which is aimed at completing type information. This annotation is primarily
aimed at framework and API developers who want to extend the capabilities of the type checker by providing type inference
metadata. This is important if your library makes use of closures and that you want the maximum level of tooling support
too.
Let’s illustrate this by fixing the original example, introducing the @ClosureParams
annotation:
import groovy.transform.stc.ClosureParams
import groovy.transform.stc.FirstParam
void inviteIf(Person p, @ClosureParams(FirstParam) Closure<Boolean> predicate) { (1)
if (predicate.call(p)) {
// send invite
// ...
}
}
inviteIf(p) { (2)
it.age >= 18
}
1 | the closure parameter is annotated with @ClosureParams |
2 | it’s not necessary to use an explicit type for it , which is inferred |
The @ClosureParams
annotation minimally accepts one argument, which is named a type hint. A type hint is a class which
is reponsible for completing type information at compile time for the closure. In this example, the type hint being used
is groovy.transform.stc.FirstParam
which indicated to the type checker that the closure will accept one parameter
whose type is the type of the first parameter of the method. In this case, the first parameter of the method is Person
,
so it indicates to the type checker that the first parameter of the closure is in fact a Person
.
The second argument is optional and named options. It’s semantics depends on the type hint class. Groovy comes with various bundled type hints, illustrated in the table below:
Type hint | Polymorphic? | Description and examples |
---|---|---|
|
No |
The first (resp. second, third) parameter type of the method
|
|
No |
The first generic type of the first (resp. second, third) parameter of the method
Variants for |
|
No |
A type hint for which the type of closure parameters comes from the options string.
This type hint supports a single signature and each of the parameter is specified as a value of the options array using a fully-qualified type name or a primitive type. |
|
Yes |
A dedicated type hint for closures that either work on a
This type hint requires that the first argument is a |
|
Yes |
Infers closure parameter types from the abstract method of some type. A signature is inferred for each abstract method.
If there are multiple signatures like in the example above, the type checker will only be able to infer the types of
the arguments if the arity of each method is different. In the example above, |
|
Yes |
Infers the closure parameter typs from the A single signature for a closure accepting a
A polymorphic closure, accepting either a
A polymorphic closure, accepting either a
|
Even though you use FirstParam , SecondParam or ThirdParam as a type hint, it doesn’t stricly mean that the
argument which will be passed to the closure will be the first (resp. second, third) argument of the method call. It
only means that the type of the parameter of the closure will be the same as the type of the first (resp. second,
third) argument of the method call.
|
In short, the lack of the @ClosureParams
annotation on a method accepting a Closure
will not fail compilation. If
present (and it can be present in Java sources as well as Groovy sources), then the type checker has more information
and can perform additional type inference. This makes this feature particularily interesting for framework developers.
@DelegatesTo
The @DelegatesTo
annotation is used by the type checker to infer the type of the delegate. It allows the API designer
to instruct the compiler what is the type of the delegate and the delegation strategy. The @DelegatesTo
annotation is
discussed in a specific section.
Static compilation
In the type checking section, we have seen that Groovy provides optional type checking thanks to the
@TypeChecked
annotation. The type checker runs at compile time and performs a static analysis of dynamic code. The
program will behave exactly the same whether type checking has been enabled or not. This means that the @TypeChecked
annotation is neutral with regards to the semantics of a program. Even though it may be necessary to add type information
in the sources so that the program is considered type safe, in the end, the semantics of the program are the same.
While this may sound fine, there is actually one issue with this: type checking of dynamic code, done at compile time, is by definition only correct if no runtime specific behavior occurs. For example, the following program passes type checking:
class Computer {
int compute(String str) {
str.length()
}
String compute(int x) {
String.valueOf(x)
}
}
@groovy.transform.TypeChecked
void test() {
def computer = new Computer()
computer.with {
assert compute(compute('foobar')) =='6'
}
}
There are two compute
methods. One accepts a String
and returns an int
, the other accepts an int
and returns
a String
. If you compile this, it is considered type safe: the inner compute('foobar')
call will return an int
,
and calling compute
on this int
will in turn return a String
.
Now, before calling test()
, consider adding the following line:
Computer.metaClass.compute = { String str -> new Date() }
Using runtime metaprogramming, we’re actually modifying the behavior of the compute(String)
method, so that instead of
returning the length of the provided argument, it will return a Date
. If you execute the program, it will fail at
runtime. Since this line can be added from anywhere, in any thread, there’s absolutely no way for the type checker to
statically make sure that no such thing happens. In short, the type checker is vulnerable to monkey patching. This is
just one example, but this illustrates the concept that doing static analysis of a dynamic program is inherently wrong.
The Groovy language provides an alternative annotation to @TypeChecked
which will actually make sure that the methods
which are inferred as being called will effectively be called at runtime. This annotation turns the Groovy compiler
into a static compiler, where all method calls are resolved at compile time and the generated bytecode makes sure
that this happens: the annotation is @groovy.transform.CompileStatic
.
@CompileStatic
annotationThe @CompileStatic
annotation can be added anywhere the @TypeChecked
annotation can be used, that is to say on
a class or a method. It is not necessary to add both @TypeChecked
and @CompileStatic
, as @CompileStatic
performs
everything @TypeChecked
does, but in addition triggers static compilation.
Let’s take the example which failed, but this time let’s replace the @TypeChecked
annotation
with @CompileStatic
:
class Computer {
int compute(String str) {
str.length()
}
String compute(int x) {
String.valueOf(x)
}
}
@groovy.transform.CompileStatic
void test() {
def computer = new Computer()
computer.with {
assert compute(compute('foobar')) =='6'
}
}
Computer.metaClass.compute = { String str -> new Date() }
run()
This is the only difference. If we execute this program, this time, there is no runtime error. The test
method
became immune to monkey patching, because the compute
methods which are called in its body are linked at compile
time, so even if the metaclass of Computer
changes, the program still behaves as expected by the type checker.
There are several benefits of using @CompileStatic
on your code:
-
type safety
-
immunity to monkey patching
-
performance improvements
The performance improvements depend on the kind of program you are executing. It it is I/O bound, the difference between statically compiled code and dynamic code is barely noticeable. On highly CPU intensive code, since the bytecode which is generated is very close, if not equal, to the one that Java would produce for an equivalent program, the performance is greatly improved.
Using the invokedynamic version of Groovy, which is accessible to people using JDK 7 and above, the performance of the dynamic code should be very close to the performance of statically compiled code. Sometimes, it can even be faster! There is only one way to determine which version you should choose: measuring. The reason is that depending on your program and the JVM that you use, the performance can be significantly different. In particular, the invokedynamic version of Groovy is very sensitive to the JVM version in use. |
1.4.5. Type checking extensions
Writing a type checking extension
Towards a smarter type checker
Despite being a dynamic language, Groovy can be used with a static type checker at compile time, enabled using the @TypeChecked annotation. In this mode, the compiler becomes more verbose and throws errors for, example, typos, non-existent methods,… This comes with a few limitations though, most of them coming from the fact that Groovy remains inherently a dynamic language. For example, you wouldn’t be able to use type checking on code that uses the markup builder:
def builder = new MarkupBuilder(out)
builder.html {
head {
// ...
}
body {
p 'Hello, world!'
}
}
In the previous example, none of the html
, head
, body
or p
methods
exist. However if you execute the code, it works because Groovy uses dynamic dispatch
and converts those method calls at runtime. In this builder, there’s no limitation about
the number of tags that you can use, nor the attributes, which means there is no chance
for a type checker to know about all the possible methods (tags) at compile time, unless
you create a builder dedicated to HTML for example.
Groovy is a platform of choice when it comes to implement internal DSLs. The flexible syntax, combined with runtime and compile-time metaprogramming capabilities make Groovy an interesting choice because it allows the programmer to focus on the DSL rather than on tooling or implementation. Since Groovy DSLs are Groovy code, it’s easy to have IDE support without having to write a dedicated plugin for example.
In a lot of cases, DSL engines are written in Groovy (or Java) then user
code is executed as scripts, meaning that you have some kind of wrapper
on top of user logic. The wrapper may consist, for example, in a
GroovyShell
or GroovyScriptEngine
that performs some tasks transparently
before running the script (adding imports, applying AST transforms,
extending a base script,…). Often, user written scripts come to
production without testing because the DSL logic comes to a point
where any user may write code using the DSL syntax. In the end, a user
may just ignore that what he writes is actually code. This adds some
challenges for the DSL implementor, such as securing execution of user
code or, in this case, early reporting of errors.
For example, imagine a DSL which goal is to drive a rover on Mars remotely. Sending a message to the rover takes around 15 minutes. If the rover executes the script and fails with an error (say a typo), you have two problems:
-
first, feedback comes only after 30 minutes (the time needed for the rover to get the script and the time needed to receive the error)
-
second, some portion of the script has been executed and you may have to change the fixed script significantly (implying that you need to know the current state of the rover…)
Type checking extensions is a mechanism that will allow the developer of a DSL engine to make those scripts safer by applying the same kind of checks that static type checking allows on regular groovy classes.
The principle, here, is to fail early, that is to say fail compilation of scripts as soon as possible, and if possible provide feedback to the user (including nice error messages).
In short, the idea behind type checking extensions is to make the compiler aware of all the runtime metaprogramming tricks that the DSL uses, so that scripts can benefit the same level of compile-time checks as a verbose statically compiled code would have. We will see that you can go even further by performing checks that a normal type checker wouldn’t do, delivering powerful compile-time checks for your users.
The extensions attribute
The @TypeChecked
annotation supports an attribute
named extensions
. This parameter takes an array of strings
corresponding to a list of _type checking extensions scripts. Those
scripts are found at compile time on classpath. For example, you would
write:
@TypeChecked(extensions='/path/to/myextension.groovy')
void foo() { ...}
In that case, the foo methods would be type checked with the rules of the normal type checker completed by those found in the myextension.groovy script. Note that while internally the type checker supports multiple mechanisms to implement type checking extensions (including plain old java code), the recommanded way is to use those type checking extension scripts.
A DSL for type checking
The idea behind type checking extensions is to use a DSL to extend the type checker capabilities. This DSL allows you to hook into the compilation process, more specifically the type checking phase, using an "event-driven" API. For example, when the type checker enters a method body, it throws a beforeVisitMethod event that the extension can react to:
beforeVisitMethod { methodNode ->
println "Entering ${methodNode.name}"
}
Imagine that you have this rover DSL at hand. A user would write:
robot.move 100
If you have a class defined as such:
class Robot {
Robot move(int qt) { this }
}
The script can be type checked before being executed using the following script:
def config = new CompilerConfiguration()
config.addCompilationCustomizers(
new ASTTransformationCustomizer(TypeChecked) (1)
)
def shell = new GroovyShell(config) (2)
def robot = new Robot()
shell.setVariable('robot', robot)
shell.evaluate(script) (3)
1 | a compiler configuration adds the @TypeChecked annotation to all classes |
2 | use the configuration in a GroovyShell |
3 | so that scripts compiled using the shell are compiled with @TypeChecked without the user having to add it explicitly |
Using the compiler configuration above, we can apply @TypeChecked transparently to the script. In that case, it will fail at compile time:
[Static type checking] - The variable [robot] is undeclared.
Now, we will slightly update the configuration to include the “extensions” parameter:
config.addCompilationCustomizers(
new ASTTransformationCustomizer(
TypeChecked,
extensions:['robotextension.groovy'])
)
Then add the following to your classpath:
unresolvedVariable { var ->
if ('robot'==var.name) {
storeType(var, classNodeFor(Robot))
handled = true
}
}
Here, we’re telling the compiler that if an unresolved variable is found
and that the name of the variable is robot, then we can make sure that the type of this
variable is Robot
.
Type checking extensions API
The type checking API is a low level API, dealing with the Abstract Syntax Tree. You will have to know your AST well to develop extensions, even if the DSL makes it much easier than just dealing with AST code from plain Java or Groovy.
The type checker sends the following events, to which an extension script can react:
Event name |
setup |
Called When |
Called after the type checker finished initialization |
Arguments |
|
Usage |
Can be used to perform setup of your extension |
Event name |
finish |
Called When |
Called after the type checker completed type checking |
Arguments |
|
Usage |
Can be used to perform additional checks after the type checker has finished its job. |
Event name |
unresolvedVariable |
Called When |
Called when the type checker finds an unresolved variable |
Arguments |
VariableExpression var |
Usage |
Allows the developer to help the type checker with user-injected variables. |
Event name |
unresolvedProperty |
Called When |
Called when the type checker cannot find a property on the receiver |
Arguments |
PropertyExpression pexp |
Usage |
Allows the developer to handle "dynamic" properties |
Event name |
unresolvedAttribute |
Called When |
Called when the type checker cannot find an attribute on the receiver |
Arguments |
AttributeExpression aex |
Usage |
Allows the developer to handle missing attributes |
Event name |
beforeMethodCall |
Called When |
Called before the type checker starts type checking a method call |
Arguments |
MethodCall call |
Usage |
Allows you to intercept method calls before the type checker performs its own checks. This is useful if you want to replace the default type checking with a custom one for a limited scope. In that case, you must set the handled flag to true, so that the type checker skips its own checks. |
Event name |
afterMethodCall |
Called When |
Called once the type checker has finished type checking a method call |
Arguments |
MethodCall call |
Usage |
Allow you to perform additional checks after the type
checker has done its own checks. This is in particular useful if you
want to perform the standard type checking tests but also want to ensure
additional type safety, for example checking the arguments against each
other.Note that |
Event name |
onMethodSelection |
Called When |
Called by the type checker when it finds a method appropriate for a method call |
Arguments |
Expression expr, MethodNode node |
Usage |
The type checker works by inferring argument types of a method call, then chooses a target method. If it finds one that corresponds, then it triggers this event. It is for example interesting if you want to react on a specific method call, such as entering the scope of a method that takes a closure as argument (as in builders).Please note that this event may be thrown for various types of expressions, not only method calls (binary expressions for example). |
Event name |
methodNotFound |
Called When |
Called by the type checker when it fails to find an appropriate method for a method call |
Arguments |
ClassNode receiver, String name, ArgumentListExpression argList, ClassNode[] argTypes,MethodCall call |
Usage |
Unlike |
Event name |
beforeVisitMethod |
Called When |
Called by the type checker before type checking a method body |
Arguments |
MethodNode node |
Usage |
The type checker will call this method before starting to type check a method body. If you want, for example, to perform type checking by yourself instead of letting the type checker do it, you have to set the handled flag to true.This event can also be used to help defining the scope of your extension (for example, applying it only if you are inside method foo). |
Event name |
afterVisitMethod |
Called When |
Called by the type checker after type checking a method body |
Arguments |
MethodNode node |
Usage |
Gives you the opportunity to perform additional checks after a method body is visited by the type checker. This is useful if you collect information, for example, and want to perform additional checks once everything has been collected. |
Event name |
beforeVisitClass |
Called When |
Called by the type checker before type checking a class |
Arguments |
ClassNode node |
Usage |
If a class is type checked, then
before visiting the class, this event will be sent. It is also the case
for inner classes defined inside a class annotated with |
Event name |
afterVisitClass |
Called When |
Called by the type checker after having finished the visit of a type checked class |
Arguments |
ClassNode node |
Usage |
Called
for every class being type checked after the type checker finished its
work. This includes classes annotated with |
Event name |
incompatibleAssignment |
Called When |
Called when the type checker thinks that an assignment is incorrect, meaning that the right hand side of an assignment is incompatible with the left hand side |
Arguments |
ClassNode lhsType, ClassNode rhsType, Expression assignment |
Usage |
Gives the
developper the ability to handle incorrect assignments. This is for
example useful if a class overrides |
Event name |
ambiguousMethods |
Called When |
Called when the type checker cannot choose between several candidate methods |
Arguments |
List<MethodNode> methods, Expression origin |
Usage |
Gives the
developper the ability to handle incorrect assignments. This is for
example useful if a class overrides |
Of course, an extension script may consist of several blocks, and you can have multiple blocks responding to the same event. This makes the DSL look nicer and easier to write. However, reacting to events is far from sufficient. If you know you can react to events, you also need to deal with the errors, which implies several helper methods that will make things easier.
Working with extensions
The DSL relies on a support class
called org.codehaus.groovy.transform.stc.GroovyTypeCheckingExtensionSupport
.
This class itself
extends org.codehaus.groovy.transform.stc.TypeCheckingExtension
. Those
two classes define a number of helper methods that will make working
with the AST easier, especially regarding type checking. One interesting
thing to know is that you have access to the type checker. This means
that you can programmatically call methods of the type checker,
including those that allow you to throw compilation errors.
The extension script delegates to
the org.codehaus.groovy.transform.stc.GroovyTypeCheckingExtensionSupport
class, meaning that you have
direct access to the following variables:
-
context: the type checker context, of type
org.codehaus.groovy.transform.stc.TypeCheckingContext
-
typeCheckingVisitor: the type checker itself, a
org.codehaus.groovy.transform.stc.StaticTypeCheckingVisitor
instance -
generatedMethods: a list of "generated methods", which is in fact the list of "dummy" methods that you can create inside a type checking extension using the
newMethod
calls
The type checking context contains a lot of information that is useful in context for the type checker. For example, the current stack of enclosing method calls, binary expressions, closures, … This information is in particular important if you have to know where you are when an error occurs and that you want to handle it.
Handling class nodes is something that needs particular attention when
you work with a type checking extension. Compilation works with an
abstract syntax tree (AST) and the tree may not be complete when you are
type checking a class. This also means that when you refer to types, you
must not use class literals such as String
or HashSet
, but to class
nodes representing those types. This requires a certain level of
abstraction and understanding how Groovy deals with class nodes. To make
things easier, Groovy supplies several helper methods to deal with class
nodes. For example, if you want to say "the type for String", you can
write:
assert classNodeFor(String) instanceof ClassNode
You would also note that there is a variant of classNodeFor that takes
a String
as an argument, instead of a Class
. In general, you
should not use that one, because it would create a class node for
which the name is String
, but without any method, any property, …
defined on it. The first version returns a class node that is resolved
but the second one returns one that is not. So the latter should be
reserved for very special cases.
The second problem that you might encounter is referencing a type which
is not yet compiled. This may happen more often than you think. For
example, when you compile a set of files together. In that case, if you
want to say "that variable is of type Foo" but Foo
is not yet
compiled, you can still refer to the Foo
class node
using lookupClassNodeFor
:
assert lookupClassNodeFor('Foo') instanceof ClassNode
Say that you know that variable foo
is of type Foo
and you want to
tell the type checker about it. Then you can use the storeType
method,
which takes two arguments: the first one is the node for which you want
to store the type and the second one is the type of the node. If you
look at the implementation of storeType
, you would see that it
delegates to the type checker equivalent method, which itself does a lot
of work to store node metadata. You would also see that storing the type
is not limited to variables: you can set the type of any expression.
Likewise, getting the type of an AST node is just a matter of
calling getType
on that node. This would in general be what you want,
but there’s something that you must understand:
-
getType
returns the inferred type of an expression. This means that it will not return, for a variable declared of typeObject
the class node forObject
, but the inferred type of this variable at this point of the code (flow typing) -
if you want to access the origin type of a variable (or field/parameter), then you must call the appropriate method on the AST node
To throw a type checking error, you only have to call the
addStaticTypeError
method which takes two arguments:
-
a message which is a string that will be displayed to the end user
-
an AST node responsible for the error. It’s better to provide the best suiting AST node because it will be used to retrieve the line and column numbers
It is often required to know the type of an AST node. For readability,
the DSL provides a special isXXXExpression method that will delegate to
x instance of XXXExpression
. For example, instead of writing:
if (node instanceof BinaryExpression) {
...
}
which requires you to import the BinaryExpression
class, you can just
write:
if (isBinaryExpression(node)) {
...
}
When you perform type checking of dynamic code, you may often face the case when you know that a method call is valid but there is no “real” method behind it. As an example, take the Grails dynamic finders. You can have a method call consisting of a method named findByName(…). As there’s no findByName method defined in the bean, the type checker would complain. Yet, you would know that this method wouldn’t fail at runtime, and you can even tell what is the return type of this method. For this case, the DSL supports two special constructs that consist of phantom methods. This means that you will return a method node that doesn’t really exist but is defined in the context of type checking. Three methods exist:
-
newMethod(String name, Class returnType)
-
newMethod(String name, ClassNode returnType)
-
newMethod(String name, Callable<ClassNode> return Type)
All three variants do the same: they create a new method node which name
is the supplied name and define the return type of this method.
Moreover, the type checker would add those methods in
the generatedMethods
list (see isGenerated
below). The reason why we
only set a name and a return type is that it is only what you need in
90% of the cases. For example, in the findByName
example upper, the
only thing you need to know is that findByName
wouldn’t fail at
runtime, and that it returns a domain class. The Callable
version of
return type is interesting because it defers the computation of the
return type when the type checker actually needs it. This is interesting
because in some circumstances, you may not know the actual return type
when the type checker demands it, so you can use a closure that will be
called each time getReturnType
is called by the type checker on this
method node. If you combine this with deferred checks, you can acheive
pretty complex type checking including handling of forward references.
newMethod(name) {
// each time getReturnType on this method node will be called, this closure will be called!
println 'Type checker called me!'
lookupClassNodeFor(Foo) // return type
}
Should you need more than the name and return type, you can always
create a new MethodNode
by yourself.
Scoping is very important in DSL type checking and is one of the reasons why we couldn’t use a pointcut based approach to DSL type checking. Basically, you must be able to define very precisely when your extension applies and when it does not. Moreover, you must be able to handle situations that a regular type checker would not be able to handle, such as forward references:
point a(1,1)
line a,b // b is referenced afterwards!
point b(5,2)
Say for example that you want to handle a builder:
builder.foo {
bar
baz(bar)
}
Your extension, then, should only be active once you’ve entered
the foo
method, and inactive outside of this scope. But you could have
complex situations like mutiple builders in the same file or embedded
builders (builders in builders). While you should not try to fix all
this from start (you must accept limitations to type checking), the type
checker does offer a nice mechanism to handle this: a scoping stack,
using the newScope
and scopeExit
methods.
-
newScope
creates a new scope and puts it on top of the stack -
scopeExits
pops a scope from the stack
A scope consists of:
-
a parent scope
-
a map of custom data
If you want to look at the implementation, it’s simply a LinkedHashMap
(org.codehaus.groovy.transform.stc.GroovyTypeCheckingExtensionSupport.TypeCheckingScope
),
but it’s quite powerful. For example, you can use such a scope to store
a list of closures to be executed when you exit the scope. This is how
you would handle forward references:
def scope = newScope()
scope.secondPassChecks = []
//...
scope.secondPassChecks << { println 'executed later' }
// ...
scopeExit {
secondPassChecks*.run() // execute deferred checks
}
That is to say, that if at some point you are not able to determine the
type of an expression, or that you are not able to check at this point
that an assignment is valid or not, you can still make the check later…
This is a very powerful feature. Now, newScope
and scopeExit
provide some interesting syntactic sugar:
newScope {
secondPassChecks = []
}
At anytime in the DSL, you can access the current scope
using getCurrentScope()
or more simply currentScope
:
//...
currentScope.secondPassChecks << { println 'executed later' }
// ...
The general schema would then be:
-
determine a pointcut where you push a new scope on stack and initialize custom variables within this scope
-
using the various events, you can use the information stored in your custom scope to perform checks, defer checks,…
-
determine a pointcut where you exit the scope, call
scopeExit
and eventually perform additional checks
For the complete list of helper methods, please refer to
the org.codehaus.groovy.transform.stc.GroovyTypeCheckingExtensionSupport
and
org.codehaus.groovy.transform.stc.TypeCheckingExtension
classes. However,
take special attention to those methods:
-
isDynamic
: takes a VariableExpression as argument and returns true if the variable is a DynamicExpression, which means, in a script, that it wasn’t defined using a type or def. -
isGenerated
: takes a MethodNode as an argument and tells if the method is one that was generated by the type checker extension using thenewMethod
method -
isAnnotatedBy
: takes an AST node and a Class (or ClassNode), and tells if the node is annotated with this class. For example:isAnnotatedBy(node, NotNull)
-
getTargetMethod
: takes a method call as argument and returns theMethodNode
that the type checker has determined for it -
delegatesTo
: emulates the behaviour of the@DelegatesTo
annotation. It allows you to tell that the argument will delegate to a specific type (you can also specify the delegation strategy)
Advanced type checking extensions
Precompiled type checking extensions
All the examples above use type checking scripts. They are found in source form in classpath, meaning that:
-
a Groovy source file, corresponding to the type checking extension, is available on compilation classpath
-
this file is compiled by the Groovy compiler for each source unit being compiled (often, a source unit corresponds to a single file)
It is a very convenient way to develop type checking extensions, however it implies a slower compilation phase, because of the compilation of the extension itself for each file being compiled. For those reasons, it can be practical to rely on a precompiled extension. You have two options to do this:
-
write the extension in Groovy, compile it, then use a reference to the extension class instead of the source
-
write the extension in Java, compile it, then use a reference to the extension class
Writing a type checking extension in Groovy is the easiest path. Basically, the idea is that the type checking extension script becomes the body of the main method of a type checking extension class, as illustrated here:
import org.codehaus.groovy.transform.stc.GroovyTypeCheckingExtensionSupport
class PrecompiledExtension extends GroovyTypeCheckingExtensionSupport.TypeCheckingDSL { (1)
@Override
Object run() { (2)
unresolvedVariable { var ->
if ('robot'==var.name) {
storeType(var, classNodeFor(Robot)) (3)
handled = true
}
}
}
}
1 | extending the TypeCheckingDSL class is the easiest |
2 | then the extension code needs to go inside the run method |
3 | and you can use the very same events as an extension written in source form |
Setting up the extension is very similar to using a source form extension:
config.addCompilationCustomizers(
new ASTTransformationCustomizer(
TypeChecked,
extensions:['typing.PrecompiledExtension'])
)
The difference is that instead of using a path in classpath, you just specify the fully qualified class name of the precompiled extension.
Using @Grab in a type checking extension
It is totally possible to use the @Grab
annotation in a type checking extension.
This means you can include libraries that would only be
available at compile time. In that case, you must understand that you
would increase the time of compilation significantly (at least, the
first time it grabs the dependencies).
Sharing or packaging type checking extensions
A type checking extension is just a script that need to be on classpath. As such, you can share it as is, or bundle it in a jar file that would be added to classpath.
Global type checking extensions
While you can configure the compiler to transparently add type checking extensions to your script, there is currently no way to apply an extension transparently just by having it on classpath.
Type checking extensions and @CompileStatic
Type checking extensions are used with @TypeChecked
but can also be used with @CompileStatic
. However, you must
be aware that:
-
a type checking extension used with
@CompileStatic
will in general not be sufficient to let the compiler know how to generate statically compilable code from "unsafe" code -
it is possible to use a type checking extension with
@CompileStatic
just to enhance type checking, that is to say introduce more compilation errors, without actually dealing with dynamic code
Let’s explain the first point, which is that even if you use an extension, the compiler will not know how to compile
your code statically: technically, even if you tell the type checker what is the type of a dynamic
variable, for example, it would not know how to compile it. Is it getBinding('foo')
, getProperty('foo')
,
delegate.getFoo()
,…? There’s absolutely no direct way to tell the static compiler how to compile such
code even if you use a type checking extension (that would, again, only give hints about the type).
One possible solution for this particular example is to instruct the compiler to use mixed mode compilation. The more advanced one is to use AST transformations during type checking but it is far more complex.
Type checking extensions allow you to help the type checker where it
fails, but it also allow you to fail where it doesn’t. In that context,
it makes sense to support extensions for @CompileStatic
too. Imagine
an extension that is capable of type checking SQL queries. In that case,
the extension would be valid in both dynamic and static context, because
without the extension, the code would still pass.
Mixed mode compilation
In the previous section, we highlighted the fact that you can activate type checking extensions with
@CompileStatic
. In that context, the type checker would not complain anymore about some unresolved variables or
unknown method calls, but it would still wouldn’t know how to compile them statically.
Mixed mode compilation offers a third way, which is to instruct the compiler that whenever an unresolved variable
or method call is found, then it should fall back to a dynamic mode. This is possible thanks to type checking extensions
and a special makeDynamic
call.
To illustrate this, let’s come back to the Robot
example:
robot.move 100
And let’s try to activate our type checking extension using @CompileStatic
instead of @TypeChecked
:
def config = new CompilerConfiguration()
config.addCompilationCustomizers(
new ASTTransformationCustomizer(
CompileStatic, (1)
extensions:['robotextension.groovy']) (2)
)
def shell = new GroovyShell(config)
def robot = new Robot()
shell.setVariable('robot', robot)
shell.evaluate(script)
1 | Apply @CompileStatic transparently |
2 | Activate the type checking extension |
The script will run fine because the static compiler is told about the type of the robot
variable, so it is capable
of making a direct call to move
. But before that, how did the compiler know how to get the robot
variable? In fact
by default, in a type checking extension, setting handled=true
on an unresolved variable will automatically trigger
a dynamic resolution, so in this case you don’t have anything special to make the compiler use a mixed mode. However,
let’s slightly update our example, starting from the robot script:
move 100
Here you can notice that there is no reference to robot
anymore. Our extension will not help then because we will not
be able to instruct the compiler that move
is done on a Robot
instance. This example of code can be executed in a
totally dynamic way thanks to the help of a groovy.util.DelegatingScript
:
def config = new CompilerConfiguration()
config.scriptBaseClass = 'groovy.util.DelegatingScript' (1)
def shell = new GroovyShell(config)
def runner = shell.parse(script) (2)
runner.setDelegate(new Robot()) (3)
runner.run() (4)
1 | we configure the compiler to use a DelegatingScript as the base class |
2 | the script source needs to be parsed and will return an instance of DelegatingScript |
3 | we can then call setDelegate to use a Robot as the delegate of the script |
4 | then execute the script. move will be directly executed on the delegate |
If we want this to pass with @CompileStatic
, we have to use a type checking extension, so let’s update our configuration:
config.addCompilationCustomizers(
new ASTTransformationCustomizer(
CompileStatic, (1)
extensions:['robotextension2.groovy']) (2)
)
1 | apply @CompileStatic transparently |
2 | use an alternate type checking extension meant to recognize the call to move |
Then in the previous section we have learnt how to deal with unrecognized method calls, so we are able to write this extension:
methodNotFound { receiver, name, argList, argTypes, call ->
if (isMethodCallExpression(call) (1)
&& call.implicitThis (2)
&& 'move'==name (3)
&& argTypes.length==1 (4)
&& argTypes[0] == classNodeFor(int) (5)
) {
handled = true (6)
newMethod('move', classNodeFor(Robot)) (7)
}
}
1 | if the call is a method call (not a static method call) |
2 | that this call is made on "implicit this" (no explicit this. ) |
3 | that the method being called is move |
4 | and that the call is done with a single argument |
5 | and that argument is of type int |
6 | then tell the type checker that the call is valid |
7 | and that the return type of the call is Robot |
If you try to execute this code, then you could be surprised that it actually fails at runtime:
java.lang.NoSuchMethodError: java.lang.Object.move()Ltyping/Robot;
The reason is very simple: while the type checking extension is sufficient for @TypeChecked
, which does not involve
static compilation, it is not enough for @CompileStatic
which requires additional information. In this case, you told
the compiler that the method existed, but you didn’t explain to it what method it is in reality, and what is the
receiver of the message (the delegate).
Fixing this is very easy and just implies replacing the newMethod
call with something else:
methodNotFound { receiver, name, argList, argTypes, call ->
if (isMethodCallExpression(call)
&& call.implicitThis
&& 'move'==name
&& argTypes.length==1
&& argTypes[0] == classNodeFor(int)
) {
makeDynamic(call, classNodeFor(Robot)) (1)
}
}
1 | tell the compiler that the call should be make dynamic |
The makeDynamic
call does 3 things:
-
it returns a virtual method just like
newMethod
-
automatically sets the
handled
flag totrue
for you -
but also marks the
call
to be done dynamically
So when the compiler will have to generate bytecode for the call to move
, since it is now marked as a dynamic call,
it will fallback to the dynamic compiler and let it handle the call. And since the extension tells us that the return
type of the dynamic call is a Robot
, subsequent calls will be done statically!
Some would wonder why the static compiler doesn’t do this by default without an extension. It is a design decision:
-
if the code is statically compiled, we normally want type safety and best performance
-
so if unrecognized variables/method calls are made dynamic, you loose type safety, but also all support for typos at compile time!
In short, if you want to have mixed mode compilation, it has to be explicit, through a type checking extension, so that the compiler, and the designer of the DSL, are totally aware of what they are doing.
makeDynamic
can be used on 3 kind of AST nodes:
-
a method node (
MethodNode
) -
a variable (
VariableExpression
) -
a property expression (
PropertyExpression
)
If that is not enough, then it means that static compilation cannot be done directly and that you have to rely on AST transformations.
Transforming the AST in an extension
Type checking extensions look very attractive from an AST transformation design point of view: extensions have access to context like inferred types, which is often nice to have. And an extension has a direct access to the abstract syntax tree. Since you have access to the AST, there is nothing in theory that prevents you from modifying the AST. However, we do not recommand you to do so, unless you are an advanced AST transformation designer and well aware of the compiler internals:
-
First of all, you would explicitely break the contract of type checking, which is to annotate, and only annotate the AST. Type checking should not modify the AST tree because you wouldn’t be able to guarantee anymore that code without the @TypeChecked annotation behaves the same without the annotation.
-
If your extension is meant to work with @CompileStatic, then you can modify the AST because this is indeed what @CompileStatic will eventually do. Static compilation doesn’t guarantee the same semantics at dynamic Groovy so there is effectively a difference between code compiled with @CompileStatic and code compiled with @TypeChecked. It’s up to you to choose whatever strategy you want to update the AST, but probably using an AST transformation that runs before type checking is easier.
-
if you cannot rely on a transformation that kicks in before the type checker, then you must be very careful
The type checking phase is the last phase running in the compiler before bytecode generation. All other AST transformations run before that and the compiler does a very good job at "fixing" incorrect AST generated before the type checking phase. As soon as you perform a transformation during type checking, for example directly in a type checking extension, then you have to do all this work of generating a 100% compiler compliant abstract syntax tree by yourself, which can easily become complex. That’s why we do not recommand to go that way if you are beginning with type checking extensions and AST transformations. |
Examples
Examples of real life type checking extensions are easy to find. You can download the source code for Groovy and take a look at the TypeCheckingExtensionsTest class which is linked to various extension scripts.
But an example of the most complex type checking extension can be found in the Markup Template Engine source code: this template engine relies on a type checking extension and AST transformations to transform templates into fully statically compiled code. Sources for this can be found here.
2. Tools
2.1. Compiling Groovy
2.1.1. groovyc, the Groovy compiler
groovyc
is the Groovy compiler command line tool. It allows you to compile Groovy sources into bytecode. It plays
the same role as javac
in the Java world. The easiest way to compile a Groovy script or class is to run the following command:
groovyc MyClass.groovy
This will produce a MyClass.class
file (as well as other .class files depending on the contents of the source). groovyc
supports
a number of command line switches:
Short version | Long version | Description | Example |
---|---|---|---|
-b |
--basescript |
Base class name for scripts (must derive from Script) |
|
-cp |
-classpath, --classpath |
Specify the compilation classpath. Must be the first argument. |
groovyc -cp lib/dep.jar MyClass.groovy |
--sourcepath* |
Directory where to find source files |
groovyc -sourcepath src script.groovy |
|
--temp |
Temporary directory for the compiler |
||
--encoding |
Encoding of the source files |
groovyc -encoding utf-8 script.groovy |
|
--help |
Displays help for the command line groovyc tool |
groovyc --help |
|
-v |
--version |
Displays the compiler version |
groovyc -v |
-e |
--exception |
Displays the stack trace in case of compilation error |
groovyc -e script.groovy |
-j |
--jointCompilation* |
Enables joint compilation |
groovyc -j A.groovy B.java |
Notes:
-
sourcepath
is not used anymore. Specifying this parameter will have no effect on compilation. -
for a full description of joint compilation, see the joint compilation section.
2.1.2. Ant task
<groovyc>
Description
Compiles Groovy source files and, if joint compilation option is used, Java source files.
Required taskdef
Assuming groovy-all-VERSION.jar
is in my.classpath you will need to
declare this task at some point in the build.xml
prior to the groovyc
task being invoked.
<taskdef name="groovyc"
classname="org.codehaus.groovy.ant.Groovyc"
classpathref="my.classpath"/>
<groovyc> Attributes
Attribute | Description | Required |
---|---|---|
configscript |
Set the configuration file used to customize the compilation configuration. |
No |
srcdir |
Location of the Groovy (and possibly Java) source files. |
Yes |
destdir |
Location to store the class files. |
Yes |
classpath |
The classpath to use. |
No |
classpathref |
The classpath to use given as a path references. |
No |
sourcepath |
The sourcepath to use. |
No |
sourcepathref |
The sourcepath to use given as a path reference. |
No |
encoding |
Encoding of source files. |
No |
verbose |
Asks the compiler for verbose output; defaults to no. |
No |
includeAntRuntime |
Whether to include the Ant run-time libraries in the classpath; defaults to yes. |
No |
includeJavaRuntime |
Whether to include the default run-time libraries from the executing VM in the classpath; defaults to no. |
No |
fork |
Whether to execute groovyc using a spawned instance of the JVM; defaults to no. |
No |
memoryInitialSize |
The initial size of the memory for the underlying VM, if using fork mode; ignored otherwise. Defaults to the standard VM memory setting. (Examples: 83886080, 81920k, or 80m) |
No |
memoryMaximumSize |
The maximum size of the memory for the underlying VM, if using fork mode; ignored otherwise. Defaults to the standard VM memory setting. (Examples: 83886080, 81920k, or 80m) |
No |
failonerror |
Indicates whether compilation errors will fail the build; defaults to true. |
No |
listfiles |
Indicates whether the source files to be compiled will be listed; defaults to no. |
No |
stacktrace |
if true each compile error message will contain a stacktrace |
No |
indy |
Enable compilation with the “invoke dynamic” support when using Groovy 2.0 and beyond and running on JDK 7 |
No |
scriptBaseClass |
Sets the base class for Groovy scripts |
No |
stubdir |
Set the stub directory into which the Java source stub files should be generated. The directory need not exist and will not be deleted automatically - though its contents will be cleared unless keepStubs is true. Ignored when forked. |
No |
keepStubs |
Set the keepStubs flag. Defaults to false. Set to true for debugging. Ignored when forked. |
No |
forceLookupUnnamedFiles |
The Groovyc Ant task is frequently used in the context of a build system that knows the complete list of source files to be compiled. In such a context, it is wasteful for the Groovy compiler to go searching the classpath when looking for source files and hence by default the Groovyc Ant task calls the compiler in a special mode with such searching turned off. If you wish the compiler to search for source files then you need to set this flag to true. Defaults to false. |
No |
Example:
<groovyc srcdir="src" destdir="target/classes">
</groovyc>
<groovyc> Nested Elements
element | kind | Required | Replaces Attribute |
---|---|---|---|
javac |
javac task |
No |
jointCompilationOptions |
src |
a path structure |
Yes (unless srcdir is used) |
srcdir |
classpath |
a path structure |
No |
classpath |
Notes:
-
For path structures see for example http://ant.apache.org/manual/using.html#path
-
For usages of the javac task see http://ant.apache.org/manual/CoreTasks/javac.html
-
The nested javac task behaves more or less as documented for the top-level
javac
task.srcdir
,destdir
,classpath
,encoding
for the nestedjavac
task are taken from the enclosinggroovyc
task. If these attributes are specified then they are added, they do not replace. In fact, you should not attempt to overwrite the destination. Other attributes and nested elements are unaffected, for examplefork
,memoryMaximumSize
, etc. may be used freely.
Joint Compilation
Joint compilation is enabled by using an embedded javac
element, as shown in
the following example:
<groovyc srcdir="${testSourceDirectory}" destdir="${testClassesDirectory}">
<classpath>
<pathelement path="${mainClassesDirectory}"/>
<pathelement path="${testClassesDirectory}"/>
<path refid="testPath"/>
</classpath>
<javac source="1.7" target="1.7" debug="on" />
</groovyc>
It is rare to specify srcdir
and destdir
, the nested javac
task is provided with the srcdir
and destdir
values from the enclosing groovyc
task, and it is invariable
the right thing to do just to leave this as is.
To restate: the javac
task gets the srcdir
, destdir
and classpath
from
the enclosing groovyc
task.
More details about joint compilation can be found in the joint compilation section.
2.1.3. Gant
Gant is a tool for scripting Ant tasks using Groovy instead of XML to specify the logic. As such, it has exactly the same features as the Groovyc Ant task.
2.1.5. Maven integration
There are several approaches to compiling Groovy code in your Maven projects. GMavenPlus is the most flexible and feature rich, but like most Groovy compiler tools, it can have difficulties with joint Java-Groovy projects (for the same reason GMaven and Gradle can have issues). The Groovy-Eclipse compiler plugin for Maven sidesteps the joint compilation issues. Read this for a deeper discussion of the benefits and disadvantages of the two approaches.
A third approach is to use Maven’s Ant plugin to compile a groovy project. Note that the Ant plugin is bound to the compile and test-compile phases of the build in the example below. It will be invoked during these phases and the contained tasks will be carried out which runs the Groovy compiler over the source and test directories. The resulting Java classes will coexist with and be treated like any standard Java classes compiled from Java source and will appear no different to the JRE, or the JUnit runtime.
<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/maven-v4_0_0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>com.mycomp.MyGroovy</groupId>
<artifactId>MyGroovy</artifactId>
<packaging>jar</packaging>
<version>1.0-SNAPSHOT</version>
<name>Maven Example building a Groovy project</name>
<dependencies>
<dependency>
<groupId>junit</groupId>
<artifactId>junit</artifactId>
<version>3.8.1</version>
<scope>test</scope>
</dependency>
<dependency>
<groupId>org.codehaus.groovy</groupId>
<artifactId>groovy-all</artifactId>
<version>2.1.6</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<artifactId>maven-antrun-plugin</artifactId>
<executions>
<execution>
<id>compile</id>
<phase>compile</phase>
<configuration>
<tasks>
<mkdir dir="${basedir}/src/main/groovy"/>
<taskdef name="groovyc"
classname="org.codehaus.groovy.ant.Groovyc">
<classpath refid="maven.compile.classpath"/>
</taskdef>
<mkdir dir="${project.build.outputDirectory}"/>
<groovyc destdir="${project.build.outputDirectory}"
srcdir="${basedir}/src/main/groovy/" listfiles="true">
<classpath refid="maven.compile.classpath"/>
</groovyc>
</tasks>
</configuration>
<goals>
<goal>run</goal>
</goals>
</execution>
<execution>
<id>test-compile</id>
<phase>test-compile</phase>
<configuration>
<tasks>
<mkdir dir="${basedir}/src/test/groovy"/>
<taskdef name="groovyc"
classname="org.codehaus.groovy.ant.Groovyc">
<classpath refid="maven.test.classpath"/>
</taskdef>
<mkdir dir="${project.build.testOutputDirectory}"/>
<groovyc destdir="${project.build.testOutputDirectory}"
srcdir="${basedir}/src/test/groovy/" listfiles="true">
<classpath refid="maven.test.classpath"/>
</groovyc>
</tasks>
</configuration>
<goals>
<goal>run</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
</project>
This assumes you have a Maven project setup with groovy
subfolders
as peers to the java src and test subfolders. You can use the java
/jar
archetype to set this up then rename the java folders to groovy or keep
the java folders and just create groovy peer folders. There exists, also
a groovy plugin which has not been tested or used in production. After
defining the build section as in the above example, you can invoke the
typical Maven build phases normally. For example, mvn test
will
execute the test phase, compiling Groovy source and Groovy test source
and finally executing the unit tests. If you run mvn jar
it will
execute the jar phase bundling up all of your compiled production
classes into a jar after all of the unit tests pass. For more detail on
Maven build phases consult the Maven2 documentation.
GMaven and GMavenPlus
GMaven
GMaven is the original Maven plugin for Groovy, supporting both compiling and scripting Groovy.
Important:
You should be aware that GMaven is not supported anymore and can have difficulties with joint compilation. GMavenPlus can be a good replacement, but if you are having problems with joint compilation, you might consider the Groovy Eclipse maven plugin.
GMavenPlus
GMavenPlus is a rewrite of GMaven and is in active development. It supports most of the features of GMaven (a couple notable exceptions being mojo Javadoc tags and support for older Groovy versions). Its joint compilation uses stubs (which means it has the same potential issues as GMaven and Gradle. The main advantage over its predecessor is that it supports recent Groovy versions, InvokeDynamic, and GroovyDoc.
2.1.6. The Groovy Eclipse Maven plugin
Groovy-Eclipse provides a compiler plugin for Maven. Using the compiler plugin, it is possible to compile your maven projects using the Groovy-Eclipse compiler.
The most recent version of the Groovy-Eclipse-Compiler plugin for maven is 2.8.0-01.2.9.0-01-SNAPSHOT is now available from http://nexus.codehaus.org/snapshots/ .The most recent version of the groovy-eclipse-batch artifact is 2.1.5-03 (for Groovy 2.1) and 2.0.7-03 (for Groovy 2.0). They are both available from maven central.
How to use the compiler plugin—Setting up the POM
In your plugin section, you must change the compiler used by the
maven-compiler-plugin.
Like the javac ant task,
the maven-compiler-plugin does not actually compile, but rather
delegates the compilation to a different artifact (in our case, the
groovy-eclipse-batch
artifact):
<build>
...
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<!-- 2.8.0-01 and later require maven-compiler-plugin 3.0 or higher -->
<version>3.0</version>
<configuration>
<compilerId>groovy-eclipse-compiler</compilerId>
<!-- set verbose to be true if you want lots of uninteresting messages -->
<!-- <verbose>true</verbose> -->
</configuration>
<dependencies>
<dependency>
<groupId>org.codehaus.groovy</groupId>
<artifactId>groovy-eclipse-compiler</artifactId>
<version>2.8.0-01</version>
</dependency>
<!-- for 2.8.0-01 and later you must have an explicit dependency on groovy-eclipse-batch -->
<dependency>
<groupId>org.codehaus.groovy</groupId>
<artifactId>groovy-eclipse-batch</artifactId>
<version>2.1.5-03</version>
<!-- or choose a different compiler version -->
<!-- <version>1.8.6-01</version> -->
<!-- <version>1.7.10-06</version> -->
</dependency>
</dependencies>
</plugin>
...
</plugins>
</build>
This will allow Groovy files to be compiled. The groovy-eclipse-compiler recognizes all settings supported by the maven-compiler-plugin.
Remember that you still need to specify a groovy artifact as a build
dependency in addition to the maven-compiler-plugin
dependency. The
groovy dependency version should match the compiler version. Something
like this:
<dependencies>
...
<dependency>
<groupId>org.codehaus.groovy</groupId>
<artifactId>groovy-all</artifactId>
<version>1.8.6</version>
</dependency>
...
</dependencies>
Note that the groovy-eclipse-compiler and groovy-eclipse-batch artifacts are available in Maven-central, so there is no need to explicitly declare any extra repositories.
Setting up the source folders
There are several ways to set up your maven project to recognize Groovy source files
Do nothing
The simplest way to set up your source folders is to do nothing at all:
add all of your Groovy files to src/main/java
and src/test/java
.
This requires absolutely no extra configuration and is easy to
implement. However, this is not a standard maven approach to setting up
your project. If you require a more standard maven approach, then it is
possible to put your Groovy files in src/main/groovy
and
src/test/groovy
and you Java files in src/main/java
and
src/test/java
. There are several ways of doing this.
Do almost nothing
If there is at least one file (Java or not) in src/main/java
, then
all files in src/main/groovy
will be found. If, however,
src/main/java
is empty, then src/main/groovy
will be ignored. You
can get around this by placing an empty file in src/main/java
just so
that src/main/groovy
will be recognized. The same is true for
src/test/java
and src/test/groovy
. This is actually a workaround for
GRECLIPSE-1221.
Use the groovy-eclipse-compiler
mojo for configuring source folders
(You only need this approach if your project has an empty
src/main/java
or src/test/java
.)
If your project has no Java files and you don’t want to add an empty
file in src/main/java
, then you can configure source files by
referencing the groovy-eclipse-compiler mojo. Just add this to the
plugins
section of your pom:
<build>
...
<plugin>
<groupId>org.codehaus.groovy</groupId>
<artifactId>groovy-eclipse-compiler</artifactId>
<version>2.8.0-01</version>
<extensions>true</extensions>
</plugin>
...
</build>
The <extensions>true</extensions>
section is important because this
redefines the default lifecycle of your project so that an extra phase
is added. This phase has an extra goal attached to it that adds the two
Groovy source folders.
Use the build-helper-maven-plugin
(You only need this approach if your project has an empty
src/main/java
or src/test/java
.)
The build-helper-maven-plugin
allows you to do things like adding
extra source folders to your project without needing to redefine the
default lifecycle. You need to add this configuration to your build
plugin section:
<build>
...
<plugin>
<groupId>org.codehaus.mojo</groupId>
<artifactId>build-helper-maven-plugin</artifactId>
<version>1.5</version>
<executions>
<execution>
<id>add-source</id>
<phase>generate-sources</phase>
<goals>
<goal>add-source</goal>
</goals>
<configuration>
<sources>
<source>src/main/groovy</source>
</sources>
</configuration>
</execution>
<execution>
<id>add-test-source</id>
<phase>generate-test-sources</phase>
<goals>
<goal>add-test-source</goal>
</goals>
<configuration>
<sources>
<source>src/test/groovy</source>
</sources>
</configuration>
</execution>
</executions>
</plugin>
...
</build>
The benefit of using this approach is that you do not need to make any changes to the default lifecycle. The downside is, of course, that you need 31 lines of configuration to do this!
Sample project and source code
There is an archetype available for this project. You can use it through a command like this:
mvn archetype:generate \
-DarchetypeGroupId=org.codehaus.groovy \
-DarchetypeArtifactId=groovy-eclipse-quickstart \
-DarchetypeVersion=2.5.2-01 \
-DgroupId=foo \
-DartifactId=bar \
-Dversion=1 \
-DinteractiveMode=false \
-DarchetypeRepository=https://nexus.codehaus.org/content/repositories/snapshots/
(This archetype is not actively maintained.)
A sample project using the compiler plugin as well as the source code for the plugin itself are available from the github repository:
The full URL to the maven projects is:https://github.com/groovy/groovy-eclipse/tree/master/extrasThere are several projects in the repository:groovy-eclipse-compiler : the compiler plugin itself (an m2eclipse project).groovy-eclipse-batch-builder : a set of ant scripts and configuration files used to build the groovy-eclipse-batch artifact. This artifact is an amalgamation of all jars required for compiling Groovy and Java code in Eclipse, including ecj (the Eclipse compiler for Java), the non-UI components of Groovy-Eclipse, the Groovy jars, and various required Eclipse bundles.groovy-eclipse-maven-tests : a sample project that uses the compiler plugin (an m2eclipse project).org.codehaus.groovy.m2eclipse : an Eclipse plugin that provides integration between Groovy-Eclipse and m2eclipse (the Maven tooling for Eclipse).Feature org.codehaus.groovy.m2eclipse : an Eclipse feature that is required for building and releasing the org.codehaus.groovy.m2eclipse plugin.
The sample project and archetype is not maintained as well as we would like. Some community help with this would be greatly appreciated. Please see GRECLIPSE-1285.
Why another Groovy compiler for Maven? What about GMaven?
GMaven 2.0 and later no longer supports compilation. You can read more about this on the GMaven 2 project page. GMaven 1.x is now deprecated.
GMaven 1.x had limitations over the groovy-eclipse-compiler and for the following reasons GMaven 2.0 compilation is no longer supported:
-
The compiler plugin does not require the creation of Java stubs so that your Groovy files can compile against Java files. This will prevent some arcane compile errors from appearing.
-
The Groovy-Eclipse compiler is the same inside Eclipse and inside Maven, and so configuration across the two platforms can be simplified.
-
The compiler plugin is a standard compiler plugin for Maven. It therefore follows all allows all the same standard configuration that the Javac compiler plugin uses. This makes it simpler to introduce Groovy into an existing Maven project. All you need to do is change the compiler plugin that the pom references.
There are still some reasons to use GMaven:
-
GroovyDoc tool is not supported because the compiler plugin does not produce stubs.
-
Groovy Mojos are not supported.
-
Groovy scripts cannot be executed in your poms.
Whether or not the Groovy-Eclipse compiler plugin for Maven is appropriate for your project will depend on your requirements.
Project Lombok
Project Lombok is compatible with the groovy-eclipse-compiler. There is some extra configuration that you need to do. The lombok jar needs to be added to both the build and compile dependencies sections:
<dependency>
<groupId>org.projectlombok</groupId>
<artifactId>lombok</artifactId>
<version>0.10.4</version>
</dependency>
Also, the following configuration needs to be added to the maven-compiler-plugin configuration:
<configuration>
<compilerId>groovy-eclipse-compiler</compilerId>
<verbose>true</verbose>
<compilerArguments>
<javaAgentClass>lombok.core.Agent</javaAgentClass>
</compilerArguments>
<fork>true</fork>
</configuration>
Groovy-Eclipse configurator for m2Eclipse
If you are going to be working with your maven project inside of Eclipse, it is strongly recommended that you use m2eclipse. And to use your Groovy projects with m2eclipse, you will need to install the Groovy-Eclipse configurator for m2eclipse. This feature is available any of the Groovy-Eclipse update sites (e.g., nightly, milestone, or release). Just go to your Eclipse update manager and add the Groovy-Eclipse update sites (if you haven’t done so already). Select the Groovy-Eclipse M2E integration.
Development Builds
Eclipse level |
Development update site |
4.2 (Juno) |
|
3.7 (Indigo) |
The Groovy-Eclipse configurator for m2eclipse is not compatible with AspectJ or Scala. So you cannot use a joint AspectJ/Scala/Groovy project in Eclipse. These languages must be separated into separate sub-projects.
2.1.7. Joint compilation
Joint compilation means that the Groovy compiler will parse the Groovy source files, create stubs for all of them, invoke the Java compiler to compile the stubs along with Java sources, and then continue compilation in the normal Groovy compiler way. This allows mixing of Java and Groovy files without constraint.
Joint compilation can be enabled using the -j
flag with the command-line compiler,
or using using a nested tag and all the attributes and further nested tags as required
for the Ant task.
It is important to know that if you don’t enable joint compilation and try to compile Java source files with the Groovy compiler, the Java source files will be compiled as if they were Groovy sources. In some situations, this might work since most of the Java syntax is compatible with Groovy, but semantics would be different.
3. groovysh, the Groovy shell
3.1. Groovy : Groovy Shell
The Groovy Shell, aka. groovysh
is a command-line application which
allows easy access to evaluate Groovy expressions, define classes and
run simple experiments.
3.1.1. Features
-
No need for
go
command to execute buffer. -
Rich cross-platform edit-line editing, history and completion thanks to JLine.
-
ANSI colors (prompt, exception traces, etc).
-
Simple, yet robust, command system with online help, user alias support and more.
-
User profile support
3.1.2. Command-line Options and Arguments
The shell supports several options to control verbosity, ANSI coloring and other features.
./bin/groovysh --help
usage: groovysh [options] [...]
-C, --color[=FLAG] Enable or disable use of ANSI colors
-D, --define=NAME=VALUE Define a system property
-T, --terminal=TYPE Specify the terminal TYPE to use
-V, --version Display the version
-d, --debug Enable debug output
-h, --help Display this help message
-q, --quiet Suppress superfluous output
-v, --verbose Enable verbose output
In addition to options, commands or expressions can be given on the command-line which will invoke the shell in non-interactive mode. The commands or expressions will be evaluated and the shell will exit. If no additional arguments are given the shell will startup interactively.
Evaluate an Expression
./bin/groovysh 'System.properties.each { k, v -> println("$k = $v") }' java.runtime.name = Java(TM) 2 Runtime Environment, Standard Edition sun.boot.library.path = /System/Library/Frameworks/JavaVM.framework/Versions/1.5.0/Libraries java.vm.version = 1.5.0_07-87 awt.nativeDoubleBuffering = true gopherProxySet = false ...
3.1.3. Evaluating Expressions
Evaluation Result
When a complete expression is found, it is compiled and evaluated. The result of the evaluation is stored into the _ variable.
Multi-line Expressions
Multi-line/complex expressions (like closure or class definitions) may be defined over several lines. When the shell detects that it has a complete expression it will compile and evaluate it.
Variables
Shell variables are all untyped (ie. no def
or other type
information).
This will set a shell variable:
foo = "bar"
But, this will evaluate a local variable and will not be saved to the shell’s environment:
def foo = "bar"
Functions
Functions can be defined in the shell, and will be saved for later use.
Defining a function is easy:
groovy:000> def hello(name) {
groovy:001> println("Hello $name")
groovy:002> }
And then using it is as one might expect:
hello("Jason")
Internally the shell creates a closure to encapsulate the function and then binds the closure to a variable. So variables and functions share the same namespace.
3.1.4. Commands
The shell has a number of different commands, which provide rich access to the shell’s environment.
Commands all have a name and a shortcut (which is something like
\h
). Commands may also have some predefined system aliases. Users
may also create their own aliases.
Recognized Commands
help
Display the list of commands (and aliases) or the help text for specific command.
The Command List
groovy:000> help For information about Groovy, visit: http://groovy.codehaus.org Available commands: help (\h ) Display this help message ? (\? ) Alias to: help exit (\x ) Exit the shell quit (\q ) Alias to: exit import (\i ) Import a class into the namespace display (\d ) Display the current buffer clear (\c ) Clear the buffer and reset the prompt counter. show (\S ) Show variables, classes or imports inspect (\n ) Inspect a variable or the last result with the GUI object browser purge (\p ) Purge variables, classes, imports or preferences edit (\e ) Edit the current buffer load (\l ) Load a file or URL into the buffer . (\. ) Alias to: load save (\s ) Save the current buffer to a file record (\r ) Record the current session to a file history (\H ) Display, manage and recall edit-line history alias (\a ) Create an alias set (\= ) Set (or list) preferences register (\rc) Registers a new command with the shell doc (\D ) Opens a browser window displaying the doc for the argument For help on a specific command type: help <command>
Help for a Command
While in the interactive shell, you can ask for help for any command to
get more details about its syntax or function. Here is an example of
what happens when you ask for help for the help
command:
groovy:000> help help usage: help [<command>] Display the list of commands or the help text for <command>.
exit
Exit the shell.
This is the only way to exit the shell. Well, you can still CTRL-C
,
but the shell will complain about an abnormal shutdown of the JVM.
import
Add a custom import which will be included for all shell evaluations.
This command can be given at any time to add new imports.
display
Display the contents of the current buffer.
This only displays the buffer of an incomplete expression. Once the expression is complete, the buffer is rest. The prompt will update to show the size of the current buffer as well.
Example
groovy:000> class Foo { groovy:001> def bar groovy:002> def baz() { groovy:003> display 001> class Foo { 002> def bar 003> def baz() {
clear
Clears the current buffer, resetting the prompt counter to 000. Can be used to recover from compilation errors.
show
Show variables, classes or preferences or imports.
show variables
groovy:000> show variables Variables: _ = true
show classes
show imports
show preferences
show all
purge
Purges objects from the shell.
purge variables
purge classes
purge imports
purge preferences
purge all
edit
Edit the current buffer in an external editor.
Currently only works on UNIX systems which have the EDITOR
environment
variable set, or have configured the editor
preference.
history
Display, manage and recall edit-line history.
history show
history recall
history flush
history clear
3.1.5. Preferences
Some of aspects of groovysh
behaviors can be customized by setting
preferences. Preferences are set using the set
command or the \=
shortcut.
Recognized Preferences
3.1.7. Custom commands
The register
command allows you to register custom commands in the shell. For example, writing the following
will register the Stats
command:
register Stats
where the Stats
class is a class extending the org.codehaus.groovy.tools.shell.CommandSupport
class. For example:
import org.codehaus.groovy.tools.shell.CommandSupport
import org.codehaus.groovy.tools.shell.Groovysh
class Stats extends CommandSupport {
protected Stats(final Groovysh shell) {
super(shell, 'stats', 'T')
}
public Object execute(List args) {
println "Free memory: ${Runtime.runtime.freeMemory()}"
}
}
Then the command can be called using:
groovy:000> stats stats Free memory: 139474880 groovy:000>
Note that the command class must be found on classpath: you cannot define a new command from within the shell.
3.1.8. Screen Shots
These shots have been taken over the development of the new shell, so some of the content might look slightly different. Also, note the yellow colors here are the shell’s bold color, so the colors might look different depending on how the enclosing shell has its colors setup.
3.1.9. Troubleshooting
Please report any problems you
run into. Please be sure to mark the JIRA issue with the Groovysh
component.
Platform Problems
Problems loading the JLine DLL
On Windows, JLine (which is used for the fancy
shell input/history/completion fluff), uses a tiny DLL file to trick
the evil Windows faux-shell (CMD.EXE
or COMMAND.COM
) into
providing Java with unbuffered input. In some rare cases, this might
fail to load or initialize.
One solution is to disable the frills and use the unsupported terminal
instance. You can do that on the command-line using the --terminal
flag and set it to one of:
-
none
-
false
-
off
-
jline.UnsupportedTerminal
groovysh --terminal=none
3.2. GMavenPlus Maven Plugin
GMavenPlus is a Maven plugin with goals that support launching a Groovy Shell or Groovy Console bound to a Maven project.
3.3. groovyConsole, the Groovy swing console
3.3.1. Groovy : Groovy Console
The Groovy Swing Console allows a user to enter and run Groovy scripts. This page documents the features of this user interface.
3.3.2. Basics
-
Groovy Console is launched via
groovyConsole
orgroovyConsole.bat
, both located in$GROOVY_HOME/bin
-
The Console has an input area and an output area.
-
You type a Groovy script in the input area.
-
When you select
Run
from theActions
menu, the console compiles the script and runs it. -
Anything that would normally be printed on
System.out
is printed in the output area. -
If the script returns a non-null result, that result is printed.
3.3.3. Features
Running Scripts
There are several shortcuts that you can use to run scripts or code snippets:
-
Ctrl+Enter
andCtrl+R
are both shortcut keys forRun Script
. -
If you highight just part of the text in the input area, then Groovy runs just that text.
-
The result of a script is the the value of the last expression executed.
-
You can turn the System.out capture on and off by selecting
Capture System.out
from theActions
menu
Editing Files
You can open any text file, edit it, run it (as a Groovy Script) and then save it again when you are finished.
-
Select
File > Open
(shortcut keyctrl+O
) to open a file -
Select
File > Save
(shortcut keyctrl+S
) to save a file -
Select
File > New File
(shortcut keyctrl+Q
) to start again with a blank input area
History and results
-
You can pop-up a gui inspector on the last (non-null) result by selecting
Inspect Last
from theActions
menu. The inspector is a convenient way to view lists and maps. -
The console remembers the last ten script runs. You can scroll back and forth through the history by selecting
Next
andPrevious
from theEdit
menu.Ctrl-N
andctrl-P
are convenient shortcut keys. -
The last (non-null) result is bound to a variable named
_
(an underscore). -
The last result (null and non-null) for every run in the history is bound into a list variable named
__
(two underscores). The result of the last run is__[-1]
, the result of the second to last run is__[-2]
and so forth.
Interrupting a script
The Groovy console is a very handy tool to develop scripts. Often, you will
find yourself running a script multiple times until it works the way you want
it to. However, what if your code takes too long to finish or worse, creates
an infinite loop? Interrupting script execution can be acheived by clicking
the interrupt
button on the small dialog box that pops up when a script
is executing or through the interrupt
icon in the tool bar.
However, this may not be sufficient to interrupt a script: clicking the button
will interrupt the execution thread, but if your code doesn’t handle the interrupt
flag, the script is likely to keep running without you being able to effectively
stop it. To avoid that, you have to make sure that the Script > Allow interruption
menu item is flagged. This will automatically apply an AST transformation to your
script which will take care of checking the interrupt flag (@ThreadInterrupt
).
This way, you guarantee that the script can be interrupted even if you don’t explicitly
handle interruption, at the cost of extra execution time.
And more
-
You can change the font size by selecting
Smaller Font
orLarger Font
from theActions menu
-
The console can be run as an Applet thanks to
groovy.ui.ConsoleApplet
-
Code is auto indented when you hit return
-
You can drag’n drop a Groovy script over the text area to open a file
-
You can modify the classpath with which the script in the console is being run by adding a new JAR or a directory to the classpath from the
Script
menu -
Error hyperlinking from the output area when a compilation error is expected or when an exception is thrown
3.3.4. Embedding the Console
To embed a Swing console in your application, simply create the Console
object,
load some variables, and then launch it. The console can be embedded in
either Java or Groovy code.
The Java code for this is:
import groovy.ui.Console;
...
Console console = new Console();
console.setVariable("var1", getValueOfVar1());
console.setVariable("var2", getValueOfVar2());
console.run();
...
Once the console is launched, you can use the variable values in Groovy code.
An example of how to embed either the GroovyConsole or GroovyShell in a Spring Web application can be found at Embedding a Groovy Console in a Java Server Application
3.3.5. Visualizing script output results
You can customize the way script output results are visualized. Let’s see how we can customize this. For example, viewing a map result would show something like this:
What you see here is the usual textual representation of a Map. But,
what if we enabled custom visualization of certain results? The Swing
console allows you to do just that. First of all, you have to ensure
that the visualization option is ticked: View -> Visualize Script
Results
— for the record, all settings of the Groovy Console are stored
and remembered thanks to the Preference API. There are a few result
visualizations built-in: if the script returns a java.awt.Image
, a
javax.swing.Icon
, or a java.awt.Component
with no parent, the object is
displayed instead of its toString()
representation. Otherwise,
everything else is still just represented as text. Now, create the
following Groovy script in ~/.groovy/OutputTransforms.groovy
:
import javax.swing.*
transforms << { result ->
if (result instanceof Map) {
def table = new JTable(
result.collect{ k, v ->
[k, v?.inspect()] as Object[]
} as Object[][],
['Key', 'Value'] as Object[])
table.preferredViewportSize = table.preferredSize
return new JScrollPane(table)
}
}
The Groovy Swing console will execute that script on startup, injecting a transforms list in the binding of the script, so that you can add your own script results representations. In our case, we transform the Map into a nice-looking Swing JTable. And we’re now able to visualize maps in a friendly and attractive fashion, as the screenshot below shows:
3.4. groovydoc, the Groovy & Java documentation generator
GroovyDoc is a tool responsible for generating documentation from your code. It acts like the Javadoc tool in the
Java world but is capable of handling both groovy
and java
files. The distribution comes with two ways of generating
documentation: from command line or from Apache Ant. Other build tools
like Maven or Gradle also offer wrappers for Groovydoc.
3.4.1. The groovydoc command line tool
The groovydoc
command line can be invoked to generate groovydocs:
groovydoc [options] [packagenames] [sourcefiles]
where options must be picked from the following table:
Short version | Long version | Description |
---|---|---|
-windowtitle <text> |
Browser window title for the documentation |
|
-author |
Include @author paragraphs (currently not used) |
|
-charset <charset> |
Charset for cross-platform viewing of generated documentation |
|
-classpath, -cp |
--classpath |
Specify where to find the class files - must be first argument |
-d |
--destdir <dir> |
Destination directory for output files |
--debug |
Enable debug output |
|
-doctitle <html> |
Include title for the overview page |
|
-exclude <pkglist> |
Specify a list of packages to exclude (separated by colons for all operating systems) |
|
-fileEncoding <charset> |
Charset for generated documentation files |
|
-footer <html> |
Include footer text for each page |
|
-header <html> |
Include header text for each page |
|
-help |
--help |
Display help message |
-nomainforscripts |
Don’t include the implicit public static void main method for scripts |
|
-noscripts |
Don’t process Groovy Scripts |
|
-overview <file> |
Read overview documentation from HTML file |
|
-package |
Show package/protected/public classes and members |
|
-private |
Show all classes and members |
|
-protected |
Show protected/public classes and members (default) |
|
-public |
Show only public classes and members |
|
-quiet |
Suppress superfluous output |
|
-sourcepath <pathlist> |
Specify where to find source files (dirs separated by platform path separator) |
|
-stylesheetfile <path> |
File to change style of the generated documentation |
|
-verbose |
Enable verbose output |
|
--version |
Display the version |
3.4.2. The groovydoc Ant task
The groovydoc
Ant task allows generating groovydocs from an Ant build.
Required taskdef
Assuming groovy-all-2.3.11.jar
is in my.classpath you will need to
declare this task at some point in the build.xml prior to the groovydoc
task being invoked.
<taskdef name = "groovydoc"
classname = "org.codehaus.groovy.ant.Groovydoc"
classpathref = "my.classpath"/>
<groovydoc> Attributes
Attribute | Description | Required |
---|---|---|
private |
Show all classes and members (i.e. including private ones) if set to “true”. |
No |
destdir |
Location to store the class files. |
Yes |
sourcepath |
The sourcepath to use. |
No |
packagenames |
Comma separated list of package files (with terminating wildcard). |
No |
use |
Create class and package usage pages. |
No |
windowtitle |
Browser window title for the documentation (text). |
No |
doctitle |
Include title for the package index(first) page (html-code). |
No |
header |
Include header text for each page (html-code). |
No |
footer |
Include footer text for each page (html-code). |
No |
overview |
Read overview documentation from HTML file. |
No |
<groovydoc> Nested Elements
link
Create link to groovydoc/javadoc output at the given URL.
Attribute | Description | Required |
---|---|---|
href |
Base URL of external site |
Yes |
packages |
Comma separated list of package prefixes |
Yes |
Example #1 - <groovydoc> Ant task
<taskdef name = "groovydoc"
classname = "org.codehaus.groovy.ant.Groovydoc"
classpathref = "path_to_groovy_all"/>
<groovydoc destdir = "${docsDirectory}/gapi"
sourcepath = "${mainSourceDirectory}"
packagenames = "**.*"
use = "true"
windowtitle = "${title}"
doctitle = "${title}"
header = "${title}"
footer = "${docFooter}"
overview = "src/main/overview.html"
private = "false">
<link packages="java.,org.xml.,javax.,org.xml." href="http://docs.oracle.com/javase/8/docs/api/"/>
<link packages="org.apache.tools.ant." href="http://docs.groovy-lang.org/docs/ant/api/"/>
<link packages="org.junit.,junit.framework." href="http://junit.org/apidocs/"/>
<link packages="groovy.,org.codehaus.groovy." href="http://docs.groovy-lang.org/latest/html/api/"/>
<link packages="org.codehaus.gmaven." href="http://groovy.github.io/gmaven/apidocs/"/>
</groovydoc>
Example #2 - Executing <groovydoc> from Groovy
def ant = new AntBuilder()
ant.taskdef(name: "groovydoc", classname: "org.codehaus.groovy.ant.Groovydoc")
ant.groovydoc(
destdir : "${docsDirectory}/gapi",
sourcepath : "${mainSourceDirectory}",
packagenames : "**.*",
use : "true",
windowtitle : "${title}",
doctitle : "${title}",
header : "${title}",
footer : "${docFooter}",
overview : "src/main/overview.html",
private : "false") {
link(packages:"java.,org.xml.,javax.,org.xml.",href:"http://docs.oracle.com/javase/8/docs/api/")
link(packages:"groovy.,org.codehaus.groovy.", href:"http://docs.groovy-lang.org/latest/html/api/")
link(packages:"org.apache.tools.ant.", href:"http://docs.groovy-lang.org/docs/ant/api/")
link(packages:"org.junit.,junit.framework.", href:"http://junit.org/apidocs/")
link(packages:"org.codehaus.gmaven.", href:"http://groovy.github.io/gmaven/apidocs/")
}
Custom templates
The groovydoc
Ant task supports custom templates, but it requires two steps:
-
A custom groovydoc class
-
A new groovydoc task definition
Custom Groovydoc class
The first step requires you to extend the Groovydoc
class, like in the following example:
package org.codehaus.groovy.tools.groovydoc;
import org.codehaus.groovy.ant.Groovydoc;
/**
* Overrides GroovyDoc's default class template - for testing purpose only.
*
* @author Andre Steingress
*/
public class CustomGroovyDoc extends Groovydoc {
@Override
protected String[] getClassTemplates() {
return new String[]{"org/codehaus/groovy/tools/groovydoc/testfiles/classDocName.html"};
}
}
You can override the following methods:
-
getClassTemplates
for class-level templates -
getPackageTemplates
for package-level templates -
getDocTemplates
for top-level templates
You can find the list of default templates in the org.codehaus.groovy.tools.groovydoc.gstringTemplates.GroovyDocTemplateInfo
class.
Using the custom groovydoc task
Once you’ve written the class, using it is just a matter of redefining the groovydoc
task:
<taskdef name = "groovydoc"
classname = "org.codehaus.groovy.ant.CustomGroovyDoc"
classpathref = "path_to_groovy_all"/>
Please note that template customization is provided as is. APIs are subject to change, so you must consider this as a fragile feature.
3.4.3. GMavenPlus Maven Plugin
GMavenPlus is a Maven plugin with goals that support GroovyDoc generation.
4. User Guides
4.1. Getting started
4.1.1. Download
In this download area, you will be able to download the distribution (binary and source), the Windows installer and the documentation for Groovy.
For a quick and effortless start on Mac OSX, Linux or Cygwin, you can use GVM (the Groovy enVironment Manager) to download and configure any Groovy version of your choice. Basic instructions can be found below.
Stable
-
Download zip: Binary Release | Source Release
-
Download documentation: JavaDoc and zipped online documentation
-
Combined binary / source / documentation bundle: Distribution bundle
You can learn more about this version in the release notes or in the JIRA release notes.
If you plan on using invokedynamic support, read those notes.
Snapshots
For those who want to test the very latest versions of Groovy and live on the bleeding edge, you can use our snapshot builds. As soon as a build succeeds on our continuous integration server a snapshot is deployed to Artifactory’s OSS snapshot repository.
4.1.2. Maven Repository
If you wish to embed Groovy in your application, you may just prefer to point to your favourite maven repositories or the codehaus maven repository.
Stable Release
Gradle | Maven | Explanation |
---|---|---|
'org.codehaus.groovy:groovy:2.3.11' |
<groupId>org.codehaus.groovy</groupId> <artifactId>groovy</artifactId> <version>2.3.11</version> |
Just the core of groovy without the modules (see below). |
'org.codehaus.groovy:groovy-$module:2.3.11' |
<groupId>org.codehaus.groovy</groupId> <artifactId>groovy-$module</artifactId> <version>2.3.11</version> |
"$module" stands for the different optional groovy modules "ant", "bsf", "console", "docgenerator", "groovydoc", "groovysh", "jmx", "json", "jsr223", "servlet", "sql", "swing", "test", "testng" and "xml". Example: <artifactId>groovy-sql</artifactId> |
'org.codehaus.groovy:groovy-all:2.3.11' |
<groupId>org.codehaus.groovy</groupId> <artifactId>groovy-all</artifactId> <version>2.3.11</version> |
The core plus all the modules. Optional dependencies are marked as optional. You may need to include some of the optional dependencies to use some features of Groovy, e.g. AntBuilder, GroovyMBeans, etc. |
To use the InvokeDynamic version of the jars just append ':indy’ for Gradle or <classifier>indy</classifier> for Maven.
4.1.3. GVM (the Groovy enVironment Manager)
This tool makes installing Groovy on any Bash platform (Mac OSX, Linux, Cygwin, Solaris or FreeBSD) very easy.
Simply open a new terminal and enter:
$ curl -s get.gvmtool.net | bash
Follow the instructions on-screen to complete installation.
Open a new terminal or type the command:
$ source "$HOME/.gvm/bin/gvm-init.sh"
Then install the latest stable Groovy:
$ gvm install groovy
After installation is complete and you’ve made it your default version, test it with:
$ groovy -version
That’s all there is to it!
4.1.4. Other ways to get Groovy
Installation on Windows
If you’re on Windows, you can also use the NSIS Windows installer.
Other Distributions
You may download other distributions of Groovy from this site.
Source Code
If you prefer to live on the bleeding edge, you can also grab the source code from GitHub.
IDE plugin
If you are an IDE user, you can just grab the latest IDE plugin and follow the plugin installation instructions.
4.1.5. Install Binary
These instructions describe how to install a binary distribution of Groovy.
-
First, Download a binary distribution of Groovy and unpack it into some file on your local file system.
-
Set your
GROOVY_HOME
environment variable to the directory you unpacked the distribution. -
Add
GROOVY_HOME/bin
to yourPATH
environment variable. -
Set your
JAVA_HOME
environment variable to point to your JDK. On OS X this is/Library/Java/Home
, on other unixes its often/usr/java
etc. If you’ve already installed tools like Ant or Maven you’ve probably already done this step.
You should now have Groovy installed properly. You can test this by typing the following in a command shell:
groovysh
Which should create an interactive groovy shell where you can type Groovy statements. Or to run the Swing interactive console type:
groovyConsole
To run a specific Groovy script type:
groovy SomeScript
4.2. Differences with Java
Groovy tries to be as natural as possible for Java developers. We’ve tried to follow the principle of least surprise when designing Groovy, particularly for developers learning Groovy who’ve come from a Java background.
Here we list all the major differences between Java and Groovy.
4.2.1. Default imports
All these packages and classes are imported by default, i.e. you do not
have to use an explicit import
statement to use them:
-
java.io.*
-
java.lang.*
-
java.math.BigDecimal
-
java.math.BigInteger
-
java.net.*
-
java.util.*
-
groovy.lang.*
-
groovy.util.*
4.2.2. Multi-methods
In Groovy, the methods which will be invoked are chosen at runtime. This is called runtime dispatch or multi-methods. It means that the method will be chosen based on the types of the arguments at runtime. In Java, this is the opposite: methods are chosen at compile time, based on the declared types.
The following code, written as Java code, can be compiled in both Java and Groovy, but it will behave differently:
int method(String arg) {
return 1;
}
int method(Object arg) {
return 2;
}
Object o = "Object";
int result = method(o);
In Java, you would have:
assertEquals(2, result);
Whereas in Groovy:
assertEquals(1, result);
That is because Java will use the static information type, which is that o
is declared as an Object
, whereas
Groovy will choose at runtime, when the method is actually called. Since it is called with a String
, then the
String
version is called.
4.2.3. Array initializers
In Groovy, the { ... }
block is reserved for closures. That means that you cannot create array literals with this
syntax:
int[] array = { 1, 2, 3}
You actually have to use:
int[] array = [1,2,3]
4.2.4. Package scope visibility
In Groovy, omitting a modifier on a field doesn’t result in a package-private field like in Java:
class Person {
String name
}
Instead, it is used to create a property, that is to say a private field, an associated getter and an associated _setter.
It is possible to create a package-private field by annotating it with @PackageScope
:
class Person {
@PackageScope String name
}
4.2.5. ARM blocks
ARM (Automatic Resource Management) block from Java 7 are not supported in Groovy. Instead, Groovy provides various methods relying on closures, which have the same effect while being more idiomatic. For example:
Path file = Paths.get("/path/to/file");
Charset charset = Charset.forName("UTF-8");
try (BufferedReader reader = Files.newBufferedReader(file, charset)) {
String line;
while ((line = reader.readLine()) != null) {
System.out.println(line);
}
} catch (IOException e) {
e.printStackTrace();
}
can be written like this:
new File('/path/to/file').eachLine('UTF-8') {
println it
}
or, if you want a version closer to Java:
new File('/path/to/file').withReader('UTF-8') { reader ->
reader.eachLine {
println it
}
}
4.2.6. Inner classes
The implementation of anonymous inner classes and nested classes follows the Java lead, but
you should not take out the Java Language Spec and keep shaking the head
about things that are different. The implementation done looks much like
what we do for groovy.lang.Closure , with some benefits and some
differences. Accessing private fields and methods for example can become
a problem, but on the other hand local variables don’t have to be final.
|
Static inner classes
Here’s an example of static inner class:
class A {
static class B {}
}
new A.B()
The usage of static inner classes is the best supported one. If you absolutely need an inner class, you should make it a static one.
Anonymous Inner Classes
boolean called = false
Timer timer = new Timer()
timer.schedule(new TimerTask() {
void run() {
called = true
}
}, 0)
sleep 100
assert called
Creating Instances of Non-Static Inner Classes
In Java you can do this:
public class Y {
public class X {}
public X foo() {
return new X();
}
public static X createX(Y y) {
return y.new X();
}
}
Groovy doesn’t support the y.new X()
syntax. Instead, you have to write new X(y)
, like in the code below:
public class Y {
public class X {}
public X foo() {
return new X()
}
public static X createX(Y y) {
return new X(y)
}
}
Caution though, Groovy supports calling methods with one parameter without giving an argument. The parameter will then have the value null. Basically the same rules apply to calling a constructor. There is a danger that you will write new X() instead of new X(this) for example. Since this might also be the regular way we have not yet found a good way to prevent this problem. |
4.2.7. Lambdas
Java 8 supports lambdas and method references:
Runnable run = () -> System.out.println("Run");
list.forEach(System.out::println);
Java 8 lambdas can be more or less considered as anonymous inner classes. Groovy doesn’t support that syntax, but has closures instead:
Runnable run = { println 'run' }
list.each { println it } // or list.each(this.&println)
4.2.8. GStrings
As double-quoted string literals are interpreted as GString
values, Groovy may fail
with compile error or produce subtly different code if a class with String
literal
containing a dollar character is compiled with Groovy and Java compiler.
While typically, Groovy will auto-cast between GString
and String
if an API declares
the type of a parameter, beware of Java APIs that accept an Object
parameter and then
check the actual type.
4.2.9. String and Character literals
Singly-quoted literals in Groovy are used for String
, and double-quoted result in
String
or GString
, depending whether there is interpolation in the literal.
assert 'c'.getClass()==String
assert "c".getClass()==String
assert "c${1}".getClass() in GString
Groovy will automatically cast a single-character String
to char
when assigning to
a variable of type char
. When calling methods with arguments of type char
we need
to either cast explicitly or make sure the value has been casted in advance.
char a='a'
assert Character.digit(a, 16)==10 : 'But Groovy does boxing'
assert Character.digit((char) 'a', 16)==10
try {
assert Character.digit('a', 16)==10
assert false: 'Need explicit cast'
} catch(MissingMethodException e) {
}
Groovy supports two styles of casting and in the case of casting to char
there
are subtle differences when casting a multi-char strings. The Groovy style cast is
more lenient and will take the first character, while the C-style cast will fail
with exception.
// for single char strings, both are the same
assert ((char) "c").class==Character
assert ("c" as char).class==Character
// for multi char strings they are not
try {
((char) 'cx') == 'c'
assert false: 'will fail - not castable'
} catch(GroovyCastException e) {
}
assert ('cx' as char) == 'c'
assert 'cx'.asType(char) == 'c'
4.4. Working with collections
Groovy provides native support for various collection types, including lists, maps or ranges. Most of those are based on the Java collection types and decorated with additional methods found in the Groovy development kit.
4.4.1. Lists
List literals
You can create lists as follows. Notice that []
is the empty list
expression.
def list = [5, 6, 7, 8]
assert list.get(2) == 7
assert list[2] == 7
assert list instanceof java.util.List
def emptyList = []
assert emptyList.size() == 0
emptyList.add(5)
assert emptyList.size() == 1
Each list expression creates an implementation of java.util.List.
Of course lists can be used as a source to construct another list:
def list1 = ['a', 'b', 'c']
//construct a new list, seeded with the same items as in list1
def list2 = new ArrayList<String>(list1)
assert list2 == list1 // == checks that each corresponding element is the same
// clone() can also be called
def list3 = list1.clone()
assert list3 == list1
A list is an ordered collection of objects:
def list = [5, 6, 7, 8]
assert list.size() == 4
assert list.getClass() == ArrayList // the specific kind of list being used
assert list[2] == 7 // indexing starts at 0
assert list.getAt(2) == 7 // equivalent method to subscript operator []
assert list.get(2) == 7 // alternative method
list[2] = 9
assert list == [5, 6, 9, 8,] // trailing comma OK
list.putAt(2, 10) // equivalent method to [] when value being changed
assert list == [5, 6, 10, 8]
assert list.set(2, 11) == 10 // alternative method that returns old value
assert list == [5, 6, 11, 8]
assert ['a', 1, 'a', 'a', 2.5, 2.5f, 2.5d, 'hello', 7g, null, 9 as byte]
//objects can be of different types; duplicates allowed
assert [1, 2, 3, 4, 5][-1] == 5 // use negative indices to count from the end
assert [1, 2, 3, 4, 5][-2] == 4
assert [1, 2, 3, 4, 5].getAt(-2) == 4 // getAt() available with negative index...
try {
[1, 2, 3, 4, 5].get(-2) // but negative index not allowed with get()
assert false
} catch (e) {
assert e instanceof ArrayIndexOutOfBoundsException
}
List as a boolean expression
Lists can be evaluated as a boolean
value:
assert ![] // an empty list evaluates as false
//all other lists, irrespective of contents, evaluate as true
assert [1] && ['a'] && [0] && [0.0] && [false] && [null]
Iterating on a list
Iterating on elements of a list is usually done calling the each
and eachWithIndex
methods, which execute code on each
item of a list:
[1, 2, 3].each {
println "Item: $it" // `it` is an implicit parameter corresponding to the current element
}
['a', 'b', 'c'].eachWithIndex { it, i -> // `it` is the current element, while `i` is the index
println "$i: $it"
}
In addition to iterating, it is often useful to create a new list by transforming each of its elements into
something else. This operation, often called mapping, is done in Groovy thanks to the collect
method:
assert [1, 2, 3].collect { it * 2 } == [2, 4, 6]
// shortcut syntax instead of collect
assert [1, 2, 3]*.multiply(2) == [1, 2, 3].collect { it.multiply(2) }
def list = [0]
// it is possible to give `collect` the list which collects the elements
assert [1, 2, 3].collect(list) { it * 2 } == [0, 2, 4, 6]
assert list == [0, 2, 4, 6]
Manipulating lists
Filtering and searching
The Groovy development kit contains a lot of methods on collections that enhance the standard collections with pragmatic methods, some of which are illustrated here:
assert [1, 2, 3].find { it > 1 } == 2 // find 1st element matching criteria
assert [1, 2, 3].findAll { it > 1 } == [2, 3] // find all elements matching critieria
assert ['a', 'b', 'c', 'd', 'e'].findIndexOf { // find index of 1st element matching criteria
it in ['c', 'e', 'g']
} == 2
assert ['a', 'b', 'c', 'd', 'c'].indexOf('c') == 2 // index returned
assert ['a', 'b', 'c', 'd', 'c'].indexOf('z') == -1 // index -1 means value not in list
assert ['a', 'b', 'c', 'd', 'c'].lastIndexOf('c') == 4
assert [1, 2, 3].every { it < 5 } // returns true if all elements match the predicate
assert ![1, 2, 3].every { it < 3 }
assert [1, 2, 3].any { it > 2 } // returns true if any element matches the predicate
assert ![1, 2, 3].any { it > 3 }
assert [1, 2, 3, 4, 5, 6].sum() == 21 // sum anything with a plus() method
assert ['a', 'b', 'c', 'd', 'e'].sum {
it == 'a' ? 1 : it == 'b' ? 2 : it == 'c' ? 3 : it == 'd' ? 4 : it == 'e' ? 5 : 0
// custom value to use in sum
} == 15
assert ['a', 'b', 'c', 'd', 'e'].sum { ((char) it) - ((char) 'a') } == 10
assert ['a', 'b', 'c', 'd', 'e'].sum() == 'abcde'
assert [['a', 'b'], ['c', 'd']].sum() == ['a', 'b', 'c', 'd']
// an initial value can be provided
assert [].sum(1000) == 1000
assert [1, 2, 3].sum(1000) == 1006
assert [1, 2, 3].join('-') == '1-2-3' // String joining
assert [1, 2, 3].inject('counting: ') {
str, item -> str + item // reduce operation
} == 'counting: 123'
assert [1, 2, 3].inject(0) { count, item ->
count + item
} == 6
And here is idiomatic Groovy code for finding the maximum and minimum in a collection:
def list = [9, 4, 2, 10, 5]
assert list.max() == 10
assert list.min() == 2
// we can also compare single characters, as anything comparable
assert ['x', 'y', 'a', 'z'].min() == 'a'
// we can use a closure to specify the sorting behaviour
def list2 = ['abc', 'z', 'xyzuvw', 'Hello', '321']
assert list2.max { it.size() } == 'xyzuvw'
assert list2.min { it.size() } == 'z'
In addition to closures, you can use a Comparator
to define the comparison criteria:
Comparator mc = { a, b -> a == b ? 0 : (a < b ? -1 : 1) }
def list = [7, 4, 9, -6, -1, 11, 2, 3, -9, 5, -13]
assert list.max(mc) == 11
assert list.min(mc) == -13
Comparator mc2 = { a, b -> a == b ? 0 : (Math.abs(a) < Math.abs(b)) ? -1 : 1 }
assert list.max(mc2) == -13
assert list.min(mc2) == -1
assert list.max { a, b -> a.equals(b) ? 0 : Math.abs(a) < Math.abs(b) ? -1 : 1 } == -13
assert list.min { a, b -> a.equals(b) ? 0 : Math.abs(a) < Math.abs(b) ? -1 : 1 } == -1
Adding or removing elements
We can use []
to assign a new empty list and <<
to append items to it:
def list = []
assert list.empty
list << 5
assert list.size() == 1
list << 7 << 'i' << 11
assert list == [5, 7, 'i', 11]
list << ['m', 'o']
assert list == [5, 7, 'i', 11, ['m', 'o']]
//first item in chain of << is target list
assert ([1, 2] << 3 << [4, 5] << 6) == [1, 2, 3, [4, 5], 6]
//using leftShift is equivalent to using <<
assert ([1, 2, 3] << 4) == ([1, 2, 3].leftShift(4))
We can add to a list in many ways:
assert [1, 2] + 3 + [4, 5] + 6 == [1, 2, 3, 4, 5, 6]
// equivalent to calling the `plus` method
assert [1, 2].plus(3).plus([4, 5]).plus(6) == [1, 2, 3, 4, 5, 6]
def a = [1, 2, 3]
a += 4 // creates a new list and assigns it to `a`
a += [5, 6]
assert a == [1, 2, 3, 4, 5, 6]
assert [1, *[222, 333], 456] == [1, 222, 333, 456]
assert [*[1, 2, 3]] == [1, 2, 3]
assert [1, [2, 3, [4, 5], 6], 7, [8, 9]].flatten() == [1, 2, 3, 4, 5, 6, 7, 8, 9]
def list = [1, 2]
list.add(3)
list.addAll([5, 4])
assert list == [1, 2, 3, 5, 4]
list = [1, 2]
list.add(1, 3) // add 3 just before index 1
assert list == [1, 3, 2]
list.addAll(2, [5, 4]) //add [5,4] just before index 2
assert list == [1, 3, 5, 4, 2]
list = ['a', 'b', 'z', 'e', 'u', 'v', 'g']
list[8] = 'x' // the [] operator is growing the list as needed
// nulls inserted if required
assert list == ['a', 'b', 'z', 'e', 'u', 'v', 'g', null, 'x']
It is however important that the +
operator on a list is not mutating. Compared to <<
, it will create a new
list, which is often not what you want and can lead to performance issues.
The Groovy development kit also contains methods allowing you to easily remove elements from a list by value:
assert ['a','b','c','b','b'] - 'c' == ['a','b','b','b']
assert ['a','b','c','b','b'] - 'b' == ['a','c']
assert ['a','b','c','b','b'] - ['b','c'] == ['a']
def list = [1,2,3,4,3,2,1]
list -= 3 // creates a new list by removing `3` from the original one
assert list == [1,2,4,2,1]
assert ( list -= [2,4] ) == [1,1]
It is also possible to remove an element by referring to its index, in which case the list is mutated:
def list = [1,2,3,4,5,6,2,2,1]
assert list.remove(2) == 3 // remove the third element, and return it
assert list == [1,2,4,5,6,2,2,1]
In case you only want to remove the first element having the same value in a list, instead of removing all
elements, you call call the remove
method:
def list= ['a','b','c','b','b']
assert list.remove('c') // remove 'c', and return true because element removed
assert list.remove('b') // remove first 'b', and return true because element removed
assert ! list.remove('z') // return false because no elements removed
assert list == ['a','b','b']
And removing all the elements in a list can be done by calling the clear
method:
def list= ['a',2,'c',4]
list.clear()
assert list == []
Set operations
The Groovy development kit also includes methods making it easy to reason on sets:
assert 'a' in ['a','b','c'] // returns true if an element belongs to the list
assert ['a','b','c'].contains('a') // equivalent to the `contains` method in Java
assert [1,3,4].containsAll([1,4]) // `containsAll` will check that all elements are found
assert [1,2,3,3,3,3,4,5].count(3) == 4 // count the number of elements which have some value
assert [1,2,3,3,3,3,4,5].count {
it%2==0 // count the number of elements which match the predicate
} == 2
assert [1,2,4,6,8,10,12].intersect([1,3,6,9,12]) == [1,6,12]
assert [1,2,3].disjoint( [4,6,9] )
assert ![1,2,3].disjoint( [2,4,6] )
Sorting
Working with collections often implies sorting. Groovy offers a variety of options to sort lists, from using closures to comparators, as in the following examples:
assert [6, 3, 9, 2, 7, 1, 5].sort() == [1, 2, 3, 5, 6, 7, 9]
def list = ['abc', 'z', 'xyzuvw', 'Hello', '321']
assert list.sort {
it.size()
} == ['z', 'abc', '321', 'Hello', 'xyzuvw']
def list2 = [7, 4, -6, -1, 11, 2, 3, -9, 5, -13]
assert list2.sort { a, b -> a == b ? 0 : Math.abs(a) < Math.abs(b) ? -1 : 1 } ==
[-1, 2, 3, 4, 5, -6, 7, -9, 11, -13]
Comparator mc = { a, b -> a == b ? 0 : Math.abs(a) < Math.abs(b) ? -1 : 1 }
// JDK 8+ only
// list2.sort(mc)
// assert list2 == [-1, 2, 3, 4, 5, -6, 7, -9, 11, -13]
def list3 = [6, -3, 9, 2, -7, 1, 5]
Collections.sort(list3)
assert list3 == [-7, -3, 1, 2, 5, 6, 9]
Collections.sort(list3, mc)
assert list3 == [1, 2, -3, 5, 6, -7, 9]
Duplicating elements
The Groovy development kit also takes advantage of operator overloading to provide methods allowing duplication of elements of a list:
assert [1, 2, 3] * 3 == [1, 2, 3, 1, 2, 3, 1, 2, 3]
assert [1, 2, 3].multiply(2) == [1, 2, 3, 1, 2, 3]
assert Collections.nCopies(3, 'b') == ['b', 'b', 'b']
// nCopies from the JDK has different semantics than multiply for lists
assert Collections.nCopies(2, [1, 2]) == [[1, 2], [1, 2]] //not [1,2,1,2]
4.4.2. Maps
Map literals
In Groovy, maps (also known as associative arrays) can be created using the map literal syntax: [:]
:
def map = [name: 'Gromit', likes: 'cheese', id: 1234]
assert map.get('name') == 'Gromit'
assert map.get('id') == 1234
assert map['name'] == 'Gromit'
assert map['id'] == 1234
assert map instanceof java.util.Map
def emptyMap = [:]
assert emptyMap.size() == 0
emptyMap.put("foo", 5)
assert emptyMap.size() == 1
assert emptyMap.get("foo") == 5
Map keys are strings by default: [a:1]
is equivalent to ['a':1]
. This can be confusing if you define a variable
named a
and that you want the value of a
to be the key in your map. If this is the case, then you must escape
the key by adding parenthesis, like in the following example:
def a = 'Bob'
def ages = [a: 43]
assert ages['Bob'] == null // `Bob` is not found
assert ages['a'] == 43 // because `a` is a literal!
ages = [(a): 43] // now we escape `a` by using parenthesis
assert ages['Bob'] == 43 // and the value is found!
In addition to map literals, it is possible, to get a new copy of a map, to clone it:
def map = [
simple : 123,
complex: [a: 1, b: 2]
]
def map2 = map.clone()
assert map2.get('simple') == map.get('simple')
assert map2.get('complex') == map.get('complex')
map2.get('complex').put('c', 3)
assert map.get('complex').get('c') == 3
The resulting map is a shallow copy of the original one, as illustrated in the previous example.
Map property notation
Maps also act like beans so you can use the property notation to get/set
items inside the Map
as long as the keys are strings which are valid
Groovy identifiers:
def map = [name: 'Gromit', likes: 'cheese', id: 1234]
assert map.name == 'Gromit' // can be used instead of map.get('Gromit')
assert map.id == 1234
def emptyMap = [:]
assert emptyMap.size() == 0
emptyMap.foo = 5
assert emptyMap.size() == 1
assert emptyMap.foo == 5
Note: by design map.foo
will always look for the key foo
in the map. This
means foo.class
will return null
on a map that doesn’t contain the class
key. Should you really want to know
the class, then you must use getClass()
:
def map = [name: 'Gromit', likes: 'cheese', id: 1234]
assert map.class == null
assert map.get('class') == null
assert map.getClass() == LinkedHashMap // this is probably what you want
map = [1 : 'a',
(true) : 'p',
(false): 'q',
(null) : 'x',
'null' : 'z']
assert map.containsKey(1) // 1 is not an identifier so used as is
assert map.true == null
assert map.false == null
assert map.get(true) == 'p'
assert map.get(false) == 'q'
assert map.null == 'z'
assert map.get(null) == 'x'
Iterating on maps
As usual in the Groovy development kit, idiomatic iteration on maps makes use of the each
and eachWithIndex
methods.
It’s worth noting that maps created using the map literal notation are ordered, that is to say that if you iterate
on map entries, it is guaranteed that the entries will be returned in the same order they were added in the map.
def map = [
Bob : 42,
Alice: 54,
Max : 33
]
// `entry` is a map entry
map.each { entry ->
println "Name: $entry.key Age: $entry.value"
}
// `entry` is a map entry, `i` the index in the map
map.eachWithIndex { entry, i ->
println "$i - Name: $entry.key Age: $entry.value"
}
// Alternatively you can use key and value directly
map.each { key, value ->
println "Name: $key Age: $value"
}
// Key, value and i as the index in the map
map.eachWithIndex { key, value, i ->
println "$i - Name: $key Age: $value"
}
Manipulating maps
Adding or removing elements
Adding an element to a map can be done either using the put
method, the subscript operator or using putAll
:
def defaults = [1: 'a', 2: 'b', 3: 'c', 4: 'd']
def overrides = [2: 'z', 5: 'x', 13: 'x']
def result = new LinkedHashMap(defaults)
result.put(15, 't')
result[17] = 'u'
result.putAll(overrides)
assert result == [1: 'a', 2: 'z', 3: 'c', 4: 'd', 5: 'x', 13: 'x', 15: 't', 17: 'u']
Removing all the elements of a map can be done by calling the clear
method:
def m = [1:'a', 2:'b']
assert m.get(1) == 'a'
m.clear()
assert m == [:]
Maps generated using the map literal syntax are using the object equals
and hashcode
methods. This means that
you should never use an object which hash code is subject to change over time, or you wouldn’t be able to get
the associated value back.
It is also worth noting that you should never use a GString
as the key of a map, because the hash code of a GString
is not the same as the hash code of an equivalent String
:
def key = 'some key'
def map = [:]
def gstringKey = "${key.toUpperCase()}"
map.put(gstringKey,'value')
assert map.get('SOME KEY') == null
Keys, values and entries
We can inspect the keys, values, and entries in a view:
def map = [1:'a', 2:'b', 3:'c']
def entries = map.entrySet()
entries.each { entry ->
assert entry.key in [1,2,3]
assert entry.value in ['a','b','c']
}
def keys = map.keySet()
assert keys == [1,2,3] as Set
Mutating values returned by the view (be it a map entry, a key or a value) is highly discouraged because success
of the operation directly depends on the type of the map being manipulated. In particular, Groovy relies on collections
from the JDK that in general make no guarantee that a collection can safely be manipulated through keySet
, entrySet
, or
values
.
Filtering and searching
The Groovy development kit contains filtering, searching and collecting methods similar to those found for lists:
def people = [
1: [name:'Bob', age: 32, gender: 'M'],
2: [name:'Johnny', age: 36, gender: 'M'],
3: [name:'Claire', age: 21, gender: 'F'],
4: [name:'Amy', age: 54, gender:'F']
]
def bob = people.find { it.value.name == 'Bob' } // find a single entry
def females = people.findAll { it.value.gender == 'F' }
// both return entries, but you can use collect to retrieve the ages for example
def ageOfBob = bob.value.age
def agesOfFemales = females.collect {
it.value.age
}
assert ageOfBob == 32
assert agesOfFemales == [21,54]
// but you could also use a key/pair value as the parameters of the closures
def agesOfMales = people.findAll { id, person ->
person.gender == 'M'
}.collect { id, person ->
person.age
}
assert agesOfMales == [32, 36]
// `every` returns true if all entries match the predicate
assert people.every { id, person ->
person.age > 18
}
// `any` returns true if any entry matches the predicate
assert people.any { id, person ->
person.age == 54
}
Grouping
We can group a list into a map using some criteria:
assert ['a', 7, 'b', [2, 3]].groupBy {
it.class
} == [(String) : ['a', 'b'],
(Integer) : [7],
(ArrayList): [[2, 3]]
]
assert [
[name: 'Clark', city: 'London'], [name: 'Sharma', city: 'London'],
[name: 'Maradona', city: 'LA'], [name: 'Zhang', city: 'HK'],
[name: 'Ali', city: 'HK'], [name: 'Liu', city: 'HK'],
].groupBy { it.city } == [
London: [[name: 'Clark', city: 'London'],
[name: 'Sharma', city: 'London']],
LA : [[name: 'Maradona', city: 'LA']],
HK : [[name: 'Zhang', city: 'HK'],
[name: 'Ali', city: 'HK'],
[name: 'Liu', city: 'HK']],
]
4.4.3. Ranges
Ranges allow you to create a list of sequential values. These can be
used as List
since
Range extends
java.util.List.
Ranges defined with the ..
notation are inclusive (that is the list
contains the from and to value).
Ranges defined with the ..<
notation are half-open, they include the
first value but not the last value.
// an inclusive range
def range = 5..8
assert range.size() == 4
assert range.get(2) == 7
assert range[2] == 7
assert range instanceof java.util.List
assert range.contains(5)
assert range.contains(8)
// lets use a half-open range
range = 5..<8
assert range.size() == 3
assert range.get(2) == 7
assert range[2] == 7
assert range instanceof java.util.List
assert range.contains(5)
assert !range.contains(8)
//get the end points of the range without using indexes
range = 1..10
assert range.from == 1
assert range.to == 10
Note that int ranges are implemented efficiently, creating a lightweight Java object containing a from and to value.
Ranges can be used for any Java object which implements java.lang.Comparable
for comparison and also have methods next()
and previous()
to return the
next / previous item in the range. For example, you can create a range of String
elements:
// an inclusive range
def range = 'a'..'d'
assert range.size() == 4
assert range.get(2) == 'c'
assert range[2] == 'c'
assert range instanceof java.util.List
assert range.contains('a')
assert range.contains('d')
assert !range.contains('e')
You can iterate on a range using a classic for
loop:
for (i in 1..10) {
println "Hello ${i}"
}
but alternatively you can achieve the same effect in a more Groovy idiomatic style, by iterating a range
with each
method:
(1..10).each { i ->
println "Hello ${i}"
}
Ranges can be also used in the switch
statement:
switch (years) {
case 1..10: interestRate = 0.076; break;
case 11..25: interestRate = 0.052; break;
default: interestRate = 0.037;
}
4.4.4. Syntax enhancements for collections
GPath support
Thanks to the support of property notation for both lists and maps, Groovy provides syntactic sugar making it really easy to deal with nested collections, as illustrated in the following examples:
def listOfMaps = [['a': 11, 'b': 12], ['a': 21, 'b': 22]]
assert listOfMaps.a == [11, 21] //GPath notation
assert listOfMaps*.a == [11, 21] //spread dot notation
listOfMaps = [['a': 11, 'b': 12], ['a': 21, 'b': 22], null]
assert listOfMaps*.a == [11, 21, null] // caters for null values
assert listOfMaps*.a == listOfMaps.collect { it?.a } //equivalent notation
// But this will only collect non-null values
assert listOfMaps.a == [11,21]
Spread operator
The spread operator can be used to "inline" a collection into another. It is syntactic sugar which often avoids calls
to putAll
and facilitates the realization of one-liners:
assert [ 'z': 900,
*: ['a': 100, 'b': 200], 'a': 300] == ['a': 300, 'b': 200, 'z': 900]
//spread map notation in map definition
assert [*: [3: 3, *: [5: 5]], 7: 7] == [3: 3, 5: 5, 7: 7]
def f = { [1: 'u', 2: 'v', 3: 'w'] }
assert [*: f(), 10: 'zz'] == [1: 'u', 10: 'zz', 2: 'v', 3: 'w']
//spread map notation in function arguments
f = { map -> map.c }
assert f(*: ['a': 10, 'b': 20, 'c': 30], 'e': 50) == 30
f = { m, i, j, k -> [m, i, j, k] }
//using spread map notation with mixed unnamed and named arguments
assert f('e': 100, *[4, 5], *: ['a': 10, 'b': 20, 'c': 30], 6) ==
[["e": 100, "b": 20, "c": 30, "a": 10], 4, 5, 6]
The star-dot ‘*.’ operator
The "star-dot" operator is a shortcut operator allowing you to call a method or a property on all elements of a collection:
assert [1, 3, 5] == ['a', 'few', 'words']*.size()
class Person {
String name
int age
}
def persons = [new Person(name:'Hugo', age:17), new Person(name:'Sandra',age:19)]
assert [17, 19] == persons*.age
Slicing with the subscript operator
You can index into lists, arrays, maps using the subscript expression. It is interesting that strings are considered as special kinds of collections in that context:
def text = 'nice cheese gromit!'
def x = text[2]
assert x == 'c'
assert x.class == String
def sub = text[5..10]
assert sub == 'cheese'
def list = [10, 11, 12, 13]
def answer = list[2,3]
assert answer == [12,13]
Notice that you can use ranges to extract part of a collection:
list = 100..200
sub = list[1, 3, 20..25, 33]
assert sub == [101, 103, 120, 121, 122, 123, 124, 125, 133]
The subscript operator can be used to update an existing collection (for collection type which are not immutable):
list = ['a','x','x','d']
list[1..2] = ['b','c']
assert list == ['a','b','c','d']
It is worth noting that negative indices are allowed, to extract more easily from the end of a collection:
You can use negative indices to count from the end of the List, array, String etc.
text = "nice cheese gromit!"
x = text[-1]
assert x == "!"
def name = text[-7..-2]
assert name == "gromit"
Eventually, if you use a backwards range (the starting index is greater than the end index), then the answer is reversed.
text = "nice cheese gromit!"
name = text[3..1]
assert name == "eci"
4.4.5. Enhanced Collection Methods
In addition to lists, maps or ranges, Groovy offers a lot of additional methods for filtering, collecting, grouping, counting, … which are directly available on either collections or more easily iterables.
In particular, we invite you to read the Groovy development kit API docs and specifically:
4.4.6. Handy utilities
ConfigSlurper
ConfigSlurper
is a utility class for reading configuration files defined in the form of Groovy scripts. Like it is
the case with Java *.properties
files, ConfigSlurper
allows a dot notation. But in addition, it allows for Closure scoped
configuration values and arbitrary object types.
def config = new ConfigSlurper().parse('''
app.date = new Date() (1)
app.age = 42
app { (2)
name = "Test${42}"
}
''')
assert config.app.date instanceof Date
assert config.app.age == 42
assert config.app.name == 'Test42'
1 | Usage of the dot notation |
2 | Usage of Closure scopes as an alternative to the dot notation |
As can be seen in the above example, the parse
method can be used to retrieve groovy.util.ConfigObject
instances. The
ConfigObject
is a specialized java.util.Map
implementation that either returns the configured value or a new ConfigObject
instance but never null
.
def config = new ConfigSlurper().parse('''
app.date = new Date()
app.age = 42
app.name = "Test${42}"
''')
assert config.test != null (1)
1 | config.test has not been specified yet it returns a ConfigObject when being called. |
In the case of a dot being part of a configuration variable name, it can be escaped by using single or double quotes.
def config = new ConfigSlurper().parse('''
app."person.age" = 42
''')
assert config.app."person.age" == 42
In addition, ConfigSlurper
comes with support for environments
. The environments
method can be used to hand over
a Closure instance that itself may consist of a several sections. Let’s say we wanted to create a particular configuration
value for the development environment. When creating the ConfigSlurper
instance we can use the ConfigSlurper(String)
constructor to specify the target environment.
def config = new ConfigSlurper('development').parse('''
environments {
development {
app.port = 8080
}
test {
app.port = 8082
}
production {
app.port = 80
}
}
''')
assert config.app.port == 8080
The ConfigSlurper environments aren’t restricted to any particular environment names. It solely depends on the
ConfigSlurper client code what value are supported and interpreted accordingly.
|
The environments
method is built-in but the registerConditionalBlock
method can be used to register other method names
in addition to the environments
name.
def slurper = new ConfigSlurper()
slurper.registerConditionalBlock('myProject', 'developers') (1)
def config = slurper.parse('''
sendMail = true
myProject {
developers {
sendMail = false
}
}
''')
assert !config.sendMail
1 | Once the new block is registered ConfigSlurper can parse it. |
For Java integration purposes the toProperties
method can be used to convert the ConfigObject
to a java.util.Properties
object that might be stored to a *.properties
text file. Be aware though that the configuration values are converted to
String
instances during adding them to the newly created Properties
instance.
def config = new ConfigSlurper().parse('''
app.date = new Date()
app.age = 42
app {
name = "Test${42}"
}
''')
def properties = config.toProperties()
assert properties."app.date" instanceof String
assert properties."app.age" == '42'
assert properties."app.name" == 'Test42'
Expando
The Expando
class can be used to create a dynamically expandable object. Despite its name it does not use the
ExpandoMetaClass
underneath. Each Expando
object represents a standalone, dynamically-crafted instance that can be
extended with properties (or methods) at runtime.
def expando = new Expando()
expando.name = 'John'
assert expando.name == 'John'
A special case occurs when a dynamic property registers a Closure
code block. Once being registered it can be invoked
as it would be done with a method call.
def expando = new Expando()
expando.toString = { -> 'John' }
expando.say = { String s -> "John says: ${s}" }
assert expando as String == 'John'
assert expando.say('Hi') == 'John says: Hi'
Observable list, map and set
Groovy comes with observable lists, maps and sets. Each of these collections trigger java.beans.PropertyChangeEvent
events when elements
are added, removed or changed. Note that a PropertyChangeEvent
is not only signaling that a certain event has
occurred, moreover, it holds information on the property name and the old/new value a certain property has been changed to.
Depending on the type of change that has happened, observable collections might fire more specialized PropertyChangeEvent
types. For example, adding an element to an observable list fires an ObservableList.ElementAddedEvent
event.
def event (1)
def listener = {
if (it instanceof ObservableList.ElementEvent) { (2)
event = it
}
} as PropertyChangeListener
def observable = [1, 2, 3] as ObservableList (3)
observable.addPropertyChangeListener(listener) (4)
observable.add 42 (5)
assert event instanceof ObservableList.ElementAddedEvent
def elementAddedEvent = event as ObservableList.ElementAddedEvent
assert elementAddedEvent.changeType == ObservableList.ChangeType.ADDED
assert elementAddedEvent.index == 3
assert elementAddedEvent.oldValue == null
assert elementAddedEvent.newValue == 42
1 | Declares a PropertyChangeEventListener that is capturing the fired events |
2 | ObservableList.ElementEvent and its descendant types are relevant for this listener |
3 | Registers the listener |
4 | Creates an ObservableList from the given list |
5 | Triggers an ObservableList.ElementAddedEvent event |
Be aware that adding an element in fact causes two events to be triggered. The first is of type ObservableList.ElementAddedEvent ,
the second is a plain PropertyChangeEvent that informs listeners about the change of property size .
|
The ObservableList.ElementClearedEvent
event type is another interesting one. Whenever multiple
elements are removed, for example when calling clear()
, it holds the elements being removed from the list.
def event
def listener = {
if (it instanceof ObservableList.ElementEvent) {
event = it
}
} as PropertyChangeListener
def observable = [1, 2, 3] as ObservableList
observable.addPropertyChangeListener(listener)
observable.clear()
assert event instanceof ObservableList.ElementClearedEvent
def elementClearedEvent = event as ObservableList.ElementClearedEvent
assert elementClearedEvent.values == [1, 2, 3]
assert observable.size() == 0
To get an overview of all the supported event types the reader is encouraged to have a look at the JavaDoc documentation or the source code of the observable collection in use.
ObservableMap
and ObservableSet
come with the same concepts as we have seen for ObservableList
in this section.
4.5. Metaprogramming
The Groovy language supports two flavors of metaprogramming: runtime metaprogramming and compile-time metaprogramming. The first one allows altering the class model and the behavior of a program at runtime, while the second only occurs at compile-time. Both have pros and cons, that we will detail in this section.
4.5.1. Runtime metaprogramming (TBD)
methodMissing
Groovy supports the concept of methodMissing
. This method differs from invokeMethod
in that it
is only invoked in the case of a failed method dispatch, when no method can be found for the given name and/or the
given arguments.
class Foo {
def methodMissing(String name, def args) {
return "this is me"
}
}
assert new Foo().someUnknownMethod(42l) == 'this is me'
Typically when using methodMissing
the code will react in some way that makes it possible for the next time the same
method is called, that it goes through the regular Groovy method dispatch logic.
For example consider dynamic finders in GORM. These are implemented in terms of methodMissing
. The code resembles
something like this:
class GORM {
def dynamicMethods = [...] // an array of dynamic methods that use regex
def methodMissing(String name, args) {
def method = dynamicMethods.find { it.match(name) }
if(method) {
GORM.metaClass."$name" = { Object[] varArgs ->
method.invoke(delegate, name, varArgs)
}
return method.invoke(delegate,name, args)
}
else throw new MissingMethodException(name, delegate, args)
}
}
Notice how, if we find a method to invoke then we dynamically register a new method on the fly using ExpandoMetaClass
.
This is so that the next time the same method is called it is more efficient. This way methodMissing
doesn’t have
the overhead of invokeMethod
and is not expensive for the second call.
propertyMissing
Groovy supports the concept of propertyMissing
for intercepting otherwise failing property resolution attempts. In the
case of a getter method, propertyMissing
takes a single String argument resembling the property name:
class Foo {
def propertyMissing(String name) { name }
}
assert new Foo().boo == 'boo'
The propertyMissing(String)
method is only called when no getter method for the given property can be found by the Groovy
runtime.
For a setter methods a second propertyMissing
definition can be added that takes an additional value argument:
class Foo {
def storage = [:]
def propertyMissing(String name, value) { storage[name] = value }
def propertyMissing(String name) { storage[name] }
}
def f = new Foo()
f.foo = "bar"
assert f.foo == "bar"
As with methodMissing
it is best practice to dynamically register new properties at runtime to improve the overall lookup
performance.
methodMissing and propertyMissing that deal with static methods and properties can be added via
the ExpandoMetaClass.
|
Categories
There are situations where it is useful if a class not under control had additional methods. In order to enable this capability, Groovy implements a feature borrowed from Objective-C, called Categories.
Categories are implemented with so-called category classes. A category class is special in that it needs to meet certain pre-defined rules for defining extension methods.
There are a few categories that are included in the system for adding functionality to classes that make them more usable within the Groovy environment:
Category classes aren’t enabled by default. To use the methods defined in a category class it is necessary to apply
the scoped use
method that is provided by the GDK and available from inside every Groovy object instance:
use(TimeCategory) {
println 1.minute.from.now (1)
println 10.hours.ago
def someDate = new Date() (2)
println someDate - 3.months
}
1 | TimeCategory adds methods to Integer |
2 | TimeCategory adds methods to Date |
The use
method takes the category class as its first parameter and a closure code block as second parameter. Inside the
Closure
access to the category methods is available. As can be seen in the example above even JDK classes
like java.lang.Integer
or java.util.Date
can be enriched with user-defined methods.
A category needs not to be directly exposed to the user code, the following will also do:
class JPACategory{
// Let's enhance JPA EntityManager without getting into the JSR committee
static void persistAll(EntityManager em , Object[] entities) { //add an interface to save all
entities?.each { em.persist(it) }
}
}
def transactionContext = {
EntityManager em, Closure c ->
def tx = em.transaction
try {
tx.begin()
use(JPACategory) {
c()
}
tx.commit()
} catch (e) {
tx.rollback()
} finally {
//cleanup your resource here
}
}
// user code, they always forget to close resource in exception, some even forget to commit, let's not rely on them.
EntityManager em; //probably injected
transactionContext (em) {
em.persistAll(obj1, obj2, obj3)
// let's do some logics here to make the example sensible
em.persistAll(obj2, obj4, obj6)
}
When we have a look at the groovy.time.TimeCategory
class we see that the extension methods are all declared as static
methods. In fact, this is one of the requirements that must be met by category classes for its methods to be successfully added to
a class inside the use
code block:
public class TimeCategory {
public static Date plus(final Date date, final BaseDuration duration) {
return duration.plus(date);
}
public static Date minus(final Date date, final BaseDuration duration) {
final Calendar cal = Calendar.getInstance();
cal.setTime(date);
cal.add(Calendar.YEAR, -duration.getYears());
cal.add(Calendar.MONTH, -duration.getMonths());
cal.add(Calendar.DAY_OF_YEAR, -duration.getDays());
cal.add(Calendar.HOUR_OF_DAY, -duration.getHours());
cal.add(Calendar.MINUTE, -duration.getMinutes());
cal.add(Calendar.SECOND, -duration.getSeconds());
cal.add(Calendar.MILLISECOND, -duration.getMillis());
return cal.getTime();
}
// ...
Another requirement is the first argument of the static method must define the type the method is attached to once being activated. The other arguments are the normal arguments the method will take as parameters.
Because of the parameter and static method convention, category method definitions may be a bit less intuitive than
normal method definitions. As an alternative Groovy comes with a @Category
annotation that transforms annotated classes
into category classes at compile-time.
class Distance {
def number
String toString() { "${number}m" }
}
@Category(Number)
class NumberCategory {
Distance getMeters() {
new Distance(number: this)
}
}
use (NumberCategory) {
assert 42.meters.toString() == '42m'
}
Applying the @Category
annotation has the advantage of being able to use instance methods without the target type as a
first parameter. The target type class is given as an argument to the annotation instead.
There is a distinct section on @Category in the compile-time metaprogramming section.
|
Metaclasses (TBD)
ExpandoMetaClass
Groovy comes with a special MetaClass
the so-called ExpandoMetaClass
. It is special in that it allows for dynamically
adding or changing methods, constructors, properties and even static methods by using a neat closure syntax.
Applying those modifications can be especially useful in mocking or stubbing scenarios as shown in the Testing Guide.
Every java.lang.Class
is supplied by Groovy with a special metaClass
property that will give you a reference to an
ExpandoMetaClass
instance. This instance can then be used to add methods or change the behaviour of already existing
ones.
By default ExpandoMetaClass doesn’t do inheritance. To enable this you must call ExpandoMetaClass#enableGlobally()
before your app starts such as in the main method or servlet bootstrap.
|
The following sections go into detail on how ExpandoMetaClass
can be used in various scenarios.
Once the ExpandoMetaClass
is accessed by calling the metaClass
property, methods can added by using either the left shift
<<
or the =
operator.
Note that the left shift operator is used to append a new method. If the method already exists
an exception will be thrown. If you want to replace a method you can use the = operator.
|
The operators are applied on a non-existent property of metaClass
passing an instance of a Closure
code block.
class Book {
String title
}
Book.metaClass.titleInUpperCase << {-> title.toUpperCase() }
def b = new Book(title:"The Stand")
assert "THE STAND" == b.titleInUpperCase()
The example above shows how a new method can be added to a class by accessing the metaClass
property and using the <<
or
=
operator to assign a Closure
code block. The Closure
parameters are interpreted as method parameters. Parameterless methods
can be added by using the {-> ...}
syntax.
ExpandoMetaClass
supports two mechanisms for adding or overriding properties.
Firstly, it has support for declaring a mutable property by simply assigning a value to a property of metaClass
:
class Book {
String title
}
Book.metaClass.author = "Stephen King"
def b = new Book()
assert "Stephen King" == b.author
Another way is to add getter and/or setter methods by using the standard mechanisms for adding instance methods.
class Book {
String title
}
Book.metaClass.getAuthor << {-> "Stephen King" }
def b = new Book()
assert "Stephen King" == b.author
In the source code example above the property is dictated by the closure and is a read-only property. It is feasible to add an equivalent setter method but then the property value needs to be stored for later usage. This could be done as shown in the following example.
class Book {
String title
}
def properties = Collections.synchronizedMap([:])
Book.metaClass.setAuthor = { String value ->
properties[System.identityHashCode(delegate) + "author"] = value
}
Book.metaClass.getAuthor = {->
properties[System.identityHashCode(delegate) + "author"]
}
This is not the only technique however. For example in a servlet container one way might be to store the values in the currently executing request as request attributes (as is done in some cases in Grails).
Constructors can be added by using a special constructor
property. Either the <<
or =
operator can be used
to assign a Closure
code block. The Closure
arguments will become the constructor arguments when the code is
executed at runtime.
class Book {
String title
}
Book.metaClass.constructor << { String title -> new Book(title:title) }
def book = new Book('Groovy in Action - 2nd Edition')
assert book.title == 'Groovy in Action - 2nd Edition'
Be careful when adding constructors however, as it is very easy to get into stack overflow troubles. |
Static methods can be added using the same technique as instance methods with the addition of the static
qualifier
before the method name.
class Book {
String title
}
Book.metaClass.static.create << { String title -> new Book(title:title) }
def b = Book.create("The Stand")
With ExpandoMetaClass
it is possible to use Groovy’s method pointer syntax to borrow methods from other classes.
class Person {
String name
}
class MortgageLender {
def borrowMoney() {
"buy house"
}
}
def lender = new MortgageLender()
Person.metaClass.buyHouse = lender.&borrowMoney
def p = new Person()
assert "buy house" == p.buyHouse()
Since Groovy allows you to use Strings as property names this in turns allows you to dynamically create method and property names at runtime. To create a method with a dynamic name simply use the language feature of reference property names as strings.
class Person {
String name = "Fred"
}
def methodName = "Bob"
Person.metaClass."changeNameTo${methodName}" = {-> delegate.name = "Bob" }
def p = new Person()
assert "Fred" == p.name
p.changeNameToBob()
assert "Bob" == p.name
The same concept can be applied to static methods and properties.
One application of dynamic method names can be found in the Grails web application framework. The concept of "dynamic codecs" is implemented by using dynamic method names.
HTMLCodec
Classclass HTMLCodec {
static encode = { theTarget ->
HtmlUtils.htmlEscape(theTarget.toString())
}
static decode = { theTarget ->
HtmlUtils.htmlUnescape(theTarget.toString())
}
}
The example above shows a codec implementation. Grails comes with various codec implementations each defined in a single class.
At runtime there will be multiple codec classes in the application classpath. At application startup the framework adds
a encodeXXX
and a decodeXXX
method to certain meta-classes where XXX
is the first part of the codec class name (e.g.
encodeHTML
). This mechanism is in the following shown in some Groovy pseudo-code:
def codecs = classes.findAll { it.name.endsWith('Codec') }
codecs.each { codec ->
Object.metaClass."encodeAs${codec.name-'Codec'}" = { codec.newInstance().encode(delegate) }
Object.metaClass."decodeFrom${codec.name-'Codec'}" = { codec.newInstance().decode(delegate) }
}
def html = '<html><body>hello</body></html>'
assert '<html><body>hello</body></html>' == html.encodeAsHTML()
At runtime it is often useful to know what other methods or properties exist at the time the method is executed. ExpandoMetaClass
provides the following methods as of this writing:
-
getMetaMethod
-
hasMetaMethod
-
getMetaProperty
-
hasMetaProperty
Why can’t you just use reflection? Well because Groovy is different, it has the methods that are "real" methods and methods that are available only at runtime. These are sometimes (but not always) represented as MetaMethods. The MetaMethods tell you what methods are available at runtime, thus your code can adapt.
This is of particular use when overriding invokeMethod
, getProperty
and/or setProperty
.
Another feature of ExpandoMetaClass
is that it allows to override the methods invokeMethod
, getProperty
and
setProperty
, all of them can be found in the groovy.lang.GroovyObject
class.
The following example shows how to override invokeMethod
:
class Stuff {
def invokeMe() { "foo" }
}
Stuff.metaClass.invokeMethod = { String name, args ->
def metaMethod = Stuff.metaClass.getMetaMethod(name, args)
def result
if(metaMethod) result = metaMethod.invoke(delegate,args)
else {
result = "bar"
}
result
}
def stf = new Stuff()
assert "foo" == stf.invokeMe()
assert "bar" == stf.doStuff()
The first step in the Closure
code is to lookup the MetaMethod
for the given name and arguments. If the method
can be found everything is fine and it is delegated to. If not, a dummy value is returned.
A MetaMethod is a method that is known to exist on the MetaClass whether added at runtime or at compile-time.
|
The same logic can be used to override setProperty
or getProperty
.
class Person {
String name = "Fred"
}
Person.metaClass.getProperty = { String name ->
def metaProperty = Person.metaClass.getMetaProperty(name)
def result
if(metaProperty) result = metaProperty.getProperty(delegate)
else {
result = "Flintstone"
}
result
}
def p = new Person()
assert "Fred" == p.name
assert "Flintstone" == p.other
The important thing to note here is that instead of a MetaMethod
a MetaProperty
instance is looked up. If that exists
the getProperty
method of the MetaProperty
is called, passing the delegate.
ExpandoMetaClass
even allows for overriding static method with a special invokeMethod
syntax.
class Stuff {
static invokeMe() { "foo" }
}
Stuff.metaClass.'static'.invokeMethod = { String name, args ->
def metaMethod = Stuff.metaClass.getStaticMetaMethod(name, args)
def result
if(metaMethod) result = metaMethod.invoke(delegate,args)
else {
result = "bar"
}
result
}
assert "foo" == Stuff.invokeMe()
assert "bar" == Stuff.doStuff()
The logic that is used for overriding the static method is the same as we’ve seen before for overriding instance methods. The
only difference is the access to the metaClass.static
property and the call to getStaticMethodName
for retrieving
the static MetaMethod
instance.
It is possible to add methods onto interfaces with ExpandoMetaClass
. To do this however, it must be enabled
globally using the ExpandoMetaClass.enableGlobally()
method before application start-up.
List.metaClass.sizeDoubled = {-> delegate.size() * 2 }
def list = []
list << 1
list << 2
assert 4 == list.sizeDoubled()
Extension modules
Extending existing classes
An extension module allows you to add new methods to existing classes, including classes which are precompiled, like classes from the JDK. Those new methods, unlike those defined through a metaclass or using a category, are available globally. For example, when you write:
def file = new File(...)
def contents = file.getText('utf-8')
The getText
method doesn’t exist on the File
class. However, Groovy knows it because it is defined in a special
class, ResourceGroovyMethods
:
public static String getText(File file, String charset) throws IOException {
return IOGroovyMethods.getText(newReader(file, charset));
}
You may notice that the extension method is defined using a static method in a “helper” class (where various extension
methods are defined). The first argument of the getText
method corresponds to the receiver, while additional parameters
correspond to the arguments of the extension method. So here, we are defining a method called getText on
the File
class (because the first argument is of type File
), which takes a single argument as a parameter (the encoding String
).
The process of creating an extension module is simple:
-
write an extension class like above
-
write a module descriptor file
Then you have to make the extension module visible to Groovy, which is as simple as having the extension module classes and descriptor available on classpath. This means that you have the choice:
-
either provide the classes and module descriptor directly on classpath
-
or bundle your extension module into a jar for reusability
An extension module may add two kind of methods to a class:
-
instance methods (to be called on an instance of a class)
-
static methods (to be called on the class itself)
Instance methods
To add an instance method to an existing class, you need to create an extension class. For example, let’s say you
want to add a maxRetries
method on Integer
which accepts a closure and executes it at most n times until no
exception is thrown. To do that, you only need to write the following:
class MaxRetriesExtension { (1)
static void maxRetries(Integer self, Closure code) { (2)
int retries = 0
Throwable e
while (retries<self) {
try {
code.call()
break
} catch (Throwable err) {
e = err
retries++
}
}
if (retries==0 && e) {
throw e
}
}
}
1 | The extension class |
2 | First argument of the static method corresponds to the receiver of the message, that is to say the extended instance |
Then, after having declared your extension class, you can call it this way:
int i=0
5.maxRetries {
i++
}
assert i == 1
i=0
try {
5.maxRetries {
throw new RuntimeException("oops")
}
} catch (RuntimeException e) {
assert i == 5
}
Static methods
It is also possible to add static methods to a class. In that case, the static method needs to be defined in its own file:
class StaticStringExtension { (1)
static String greeting(String self) { (2)
'Hello, world!'
}
}
1 | The static extension class |
2 | First argument of the static method corresponds to the class being extended and is unused |
In which case you can call it directly on the String
class:
assert String.greeting() == 'Hello, world!'
Module descriptor
For Groovy to be able to load your extension methods, you must declare
your extension helper classes. You must create a file named
org.codehaus.groovy.runtime.ExtensionModule
into the
META-INF/services
directory:
moduleName=Test module for specifications moduleVersion=1.0-test extensionClasses=support.MaxRetriesExtension staticExtensionClasses=support.StaticStringExtension
The module descriptor requires 4 keys:
-
moduleName : the name of your module
-
moduleVersion: the version of your module. Note that version number is only used to check that you don’t load the same module in two different versions.
-
extensionClasses: the list of extension helper classes for instance methods. You can provide several classes, given that they are comma separated.
-
staticExtensionClasses: the list of extension helper classes for static methods. You can provide several classes, given that they are comma separated.
Note that it is not required for a module to define both static helpers and instance helpers, and that you may add several classes to a single module. You can also extend different classes in a single module without problem. It is even possible to use different classes in a single extension class, but it is recommended to group extension methods into classes by feature set.
Extension modules and classpath
It’s worth noting that you can’t use an extension which is compiled at the same time as code using it. That means that to use an extension, it has to be available on classpath, as compiled classes, before the code using it gets compiled. Usually, this means that you can’t have the test classes in the same source unit as the extension class itself. Since in general, test sources are separated from normal sources and executed in another step of the build, this is not an issue.
4.5.2. Compile-time metaprogramming
Compile-time metaprogramming in Groovy allows code generation at compile-time. Those transformations are altering the Abstract Syntax Tree (AST) of a program, which is why in Groovy we call it AST transformations. AST transformations allow you to hook into the compilation process, modify the AST and continue the compilation process to generate regular bytecode. Compared to runtime metaprogramming, this has the advantage of making the changes visible in the class file itself (that is to say, in the bytecode). Making it visible in the bytecode is important for example if you want the transformations to be part of the class contract (implementing interfaces, extending abstract classes, …) or even if you need your class to be callable from Java (or other JVM languages). For example, an AST transformation can add methods to a class. If you do it with runtime metaprogramming, the new method would only be visible from Groovy. If you do the same using compile-time metaprogramming, the method would be visible from Java too. Last but not least, performance would likely be better with compile-time metaprogramming (because no initialization phase is required).
In this section, we will start with explaining the various compile-time transformations that are bundled with the Groovy distribution. In a subsequent section, we will describe how you can implement your own AST transformations and what are the disadvantages of this technique.
Available AST transformations
Groovy comes with various AST transformations covering different needs: reducing boilerplate (code generation), implementing design patterns (delegation, …), logging, declarative concurrency, cloning, safer scripting, tweaking the compilation, implementing Swing patterns, testing and eventually managing dependencies. If none of those AST transformations cover your needs, you can still implement your own, as show in section Developing your own AST transformations.
AST transformations can be separated into two categories:
-
global AST transformations are applied transparently, globally, as soon as they are found on compile classpath
-
local AST transformations are applied by annotating the source code with markers. Unlike global AST transformations, local AST transformations may support parameters.
Groovy doesn’t ship with any global AST transformation, but you can find a list of local AST transformations available for you to use in your code here:
Code generation transformations
This category of transformation includes AST transformations which help removing boilerplate code. This is typically code that you have to write but that does not carry any useful information. By autogenerating this boilerplate code, the code you have to write is left clean and concise and the chance of introducing an error by getting such boilerplate code incorrect is reduced.
The @ToString
AST transformation generates a human readable toString
representation of the class. For example,
annotating the Person
class like below will automatically generate the toString
method for you:
import groovy.transform.ToString
@ToString
class Person {
String firstName
String lastName
}
With this definition, then the following assertion passes, meaning that a toString
method taking the field valuess from
the class and printing them out has been generated:
def p = new Person(firstName: 'Jack', lastName: 'Nicholson')
assert p.toString() == 'Person(Jack, Nicholson)'
The @ToString
annotation accepts several parameters which are summarized in the following table:
Attribute | Default value | Description | Example |
---|---|---|---|
includeNames |
false |
Whether to include names of properties in generated toString. |
|
excludes |
Empty list |
List of properties to exclude from toString |
|
includes |
Empty list |
List of fields to include in toString |
|
includeSuper |
False |
Should superclass be included in toString |
|
includeFields |
False |
Should fields be included in toString, in addition to properties |
|
ignoreNulls |
False |
Should properties/fields with null value be displayed |
|
includePackage |
False |
Use fully qualified class name instead of simple name in toString |
|
cache |
False |
Cache the toString string. Should only be set to true if the class is immutable. |
|
The @EqualsAndHashCode
AST transformation aims at generating equals
and hashCode
methods for you. The generated
hashcode follows the best practices as described in Effective Java by Josh Bloch:
import groovy.transform.EqualsAndHashCode
@EqualsAndHashCode
class Person {
String firstName
String lastName
}
def p1 = new Person(firstName: 'Jack', lastName: 'Nicholson')
def p2 = new Person(firstName: 'Jack', lastName: 'Nicholson')
assert p1==p2
assert p1.hashCode() == p2.hashCode()
There are several options available to tweak the behavior of @EqualsAndHashCode
:
Attribute | Default value | Description | Example |
---|---|---|---|
excludes |
Empty list |
List of properties to exclude from equals/hashCode |
|
includes |
Empty list |
List of fields to include in equals/hashCode |
|
callSuper |
False |
Whether to include super in equals and hashCode calculations |
|
includeFields |
False |
Should fields be included in equals/hashCode, in addition to properties |
|
cache |
False |
Cache the hashCode computation. Should only be set to true if the class is immutable. |
|
useCanEqual |
True |
Should equals call canEqual helper method. |
The @TupleConstructor
annotation aims at eliminating boilerplate code by generating constructors for you. A tuple
constructor is created for each property, with default values (using the Java default values). For example, the
following code will generate 3 constructors:
import groovy.transform.TupleConstructor
@TupleConstructor
class Person {
String firstName
String lastName
}
// traditional map-style constructor
def p1 = new Person(firstName: 'Jack', lastName: 'Nicholson')
// generated tuple constructor
def p2 = new Person('Jack', 'Nicholson')
// generated tuple constructor with default value for second property
def p3 = new Person('Jack')
The first constructor is a no-arg constructor which allows the traditional map-style construction. It is worth noting that if the first property (or field) has type LinkedHashMap or if there is a single Map, AbstractMap or HashMap property (or field), then the map-style mapping is not available.
The other constructors are generated by taking the properties in the order they are defined. Groovy will generate as many constructors as they are properties (or fields, depending on the options).
The @TupleConstructor
AST transformation accepts several configuration options:
Attribute | Default value | Description | Example |
---|---|---|---|
excludes |
Empty list |
List of properties to exclude from tuple constructor generation |
|
includes |
Empty list |
List of fields to include in tuple constructor generation |
|
includeFields |
False |
Should fields be included in tuple constructor generation, in addition to properties |
|
includeProperties |
True |
Should properties be included in tuple constructor generation |
|
includeSuperFields |
False |
Should fields from super classes be included in tuple constructor generation |
|
includeSuperProperties |
True |
Should properties from super classes be included in tuple constructor generation |
|
callSuper |
False |
Should super properties be called within a call to the parent constructor rather than set as properties |
|
force |
False |
By default, the transformation will do nothing if a constructor is already defined. Setting this property to true, the constructor will be generated and it’s your responsability to ensure that no duplicate constructor is defined |
See javadocs |
The @Canonical
AST transformation combines the effects of the @ToString,
@EqualsAndHashCode and @TupleConstructor
annotations:
import groovy.transform.Canonical
@Canonical
class Person {
String firstName
String lastName
}
def p1 = new Person(firstName: 'Jack', lastName: 'Nicholson')
assert p1.toString() == 'Person(Jack, Nicholson)' // Effect of @ToString
def p2 = new Person('Jack','Nicholson') // Effect of @TupleConstructor
assert p2.toString() == 'Person(Jack, Nicholson)'
assert p1==p2 // Effect of @EqualsAndHashCode
assert p1.hashCode()==p2.hashCode() // Effect of @EqualsAndHashCode
A similar immutable class can be generated using the @Immutable AST transformation instead.
The @Canonical
AST transformation supports several configuration options:
Attribute | Default value | Description | Example |
---|---|---|---|
excludes |
Empty list |
List of properties to exclude from tuple constructor generation |
|
includes |
Empty list |
List of fields to include in tuple constructor generation |
|
The @InheritConstructor
AST transformation aims at generating constructors matching super constructors for you. This
is in particular useful when overridding exception classes:
import groovy.transform.InheritConstructors
@InheritConstructors
class CustomException extends Exception {}
// all those are generated constructors
new CustomException()
new CustomException("A custom message")
new CustomException("A custom message", new RuntimeException())
new CustomException(new RuntimeException())
// Java 7 only
// new CustomException("A custom message", new RuntimeException(), false, true)
The @Category
AST transformation simplifies the creation of Groovy categories. Historically, a Groovy category was
written like this:
class TripleCategory {
public static Integer triple(Integer self) {
3*self
}
}
use (TripleCategory) {
assert 9 == 3.triple()
}
The @Category
transformation lets you write the same using an instance-style class, rather than a static class style.
This removes the need for having the first argument of each method being the receiver. The category can be written like
this:
@Category(Integer)
class TripleCategory {
public Integer triple() { 3*this }
}
use (TripleCategory) {
assert 9 == 3.triple()
}
Note that the mixed in class can be referenced using this
instead. It’s also worth noting that using instance fields
in a category class is inherently unsafe: categories are not stateful (like traits).
The @IndexedProperty
annotation aims at generating indexed getters/setters for properties of list/array types.
This is in particular useful if you want to use a Groovy class from Java. While Groovy supports GPath to access properties,
this is not available from Java. The @IndexedProperty
annotation will generate indexed properties of the following
form:
class SomeBean {
@IndexedProperty String[] someArray = new String[2]
@IndexedProperty List someList = []
}
def bean = new SomeBean()
bean.setSomeArray(0, 'value')
bean.setSomeList(0, 123)
assert bean.someArray[0] == 'value'
assert bean.someList == [123]
The @Lazy
AST transformation implements lazy initialization of fields. For example, the following code:
class SomeBean {
@Lazy LinkedList myField
}
will produce the following code:
List $myField
List getMyField() {
if ($myField!=null) { return $myField }
else {
$myField = new LinkedList()
return $myField
}
}
The default value which is used to initialize the field is the default constructor of the declaration type. It is possible to define a default value by using a closure on the right hand side of the property assignment, as in the following example:
class SomeBean { @Lazy LinkedList myField = { ['a','b','c']}() }
In that case, the generated code looks like the following:
List $myField List getMyField() { if ($myField!=null) { return $myField } else { $myField = { ['a','b','c']}() return $myField } }
If the field is declared volatile then initialization will be synchronized using the double-checked locking pattern.
Using the soft=true
parameter, the helper field will use a SoftReference
instead, providing a simple way to
implement caching. In that case, if the garbage collector decides to collect the reference, initialization will occur
the next time the field is accessed.
The @Newify
AST transformation is used to bring alternative syntaxes to construct objects:
-
Using the
Python
style:
@Newify([Tree,Leaf]) class TreeBuilder { Tree tree = Tree(Leaf('A'),Leaf('B'),Tree(Leaf('C'))) }
-
or using the
Ruby
style:
@Newify([Tree,Leaf]) class TreeBuilder { Tree tree = Tree.new(Leaf.new('A'),Leaf.new('B'),Tree.new(Leaf.new('C'))) }
The Ruby
version can be disabled by setting the auto
flag to false
.
The @Sortable
AST transformation is used to help write classes that are Comparable
and easily sorted by
numerous properties. It is easy to use as shown in the following example where we annotate the Person
class:
import groovy.transform.Sortable
@Sortable class Person {
String first
String last
Integer born
}
The generated class has the following properties:
-
it implements the
Comparable
interface -
it contains a
compareTo
method with an implementation based on the natural ordering of thefirst
,last
andborn
properties -
it has three methods returning comparators:
comparatorByFirst
,comparatorByLast
andcomparatorByBorn
.
The generated compareTo
method will look like this:
public int compareTo(java.lang.Object obj) {
if (this.is(obj)) {
return 0
}
if (!(obj instanceof Person)) {
return -1
}
java.lang.Integer value = this.first <=> obj.first
if (value != 0) {
return value
}
value = this.last <=> obj.last
if (value != 0) {
return value
}
value = this.born <=> obj.born
if (value != 0) {
return value
}
return 0
}
As an example of the generated comparators, the comparatorByFirst
comparator will have a compare
method that looks like this:
public int compare(java.lang.Object arg0, java.lang.Object arg1) {
if (arg0 == arg1) {
return 0
}
if (arg0 != null && arg1 == null) {
return -1
}
if (arg0 == null && arg1 != null) {
return 1
}
return arg0.first <=> arg1.first
}
The Person
class can be used wherever a Comparable
is expected and the generated comparators
wherever a Comparator
is expected as shown by these examples:
def people = [
new Person(first: 'Johnny', last: 'Depp', born: 1963),
new Person(first: 'Keira', last: 'Knightley', born: 1985),
new Person(first: 'Geoffrey', last: 'Rush', born: 1951),
new Person(first: 'Orlando', last: 'Bloom', born: 1977)
]
assert people[0] > people[2]
assert people.sort()*.last == ['Rush', 'Depp', 'Knightley', 'Bloom']
assert people.sort(false, Person.comparatorByFirst())*.first == ['Geoffrey', 'Johnny', 'Keira', 'Orlando']
assert people.sort(false, Person.comparatorByLast())*.last == ['Bloom', 'Depp', 'Knightley', 'Rush']
assert people.sort(false, Person.comparatorByBorn())*.last == ['Rush', 'Depp', 'Bloom', 'Knightley']
Normally, all properties are used in the generated compareTo
method in the priority order in which they are defined.
You can include or exclude certain properties from the generated compareTo
method by giving a list of property names
in the includes
or excludes
annotation attributes. If using includes
, the order of the property names given will
determine the priority of properties when comparing. To illustrate, consider the following Person
class definition:
@Sortable(includes='first,born') class Person {
String last
int born
String first
}
It will have two comparator methods comparatorByFirst
and comparatorByBorn
and the generated compareTo
method will look like this:
public int compareTo(java.lang.Object obj) {
if (this.is(obj)) {
return 0
}
if (!(obj instanceof Person)) {
return -1
}
java.lang.Integer value = this.first <=> obj.first
if (value != 0) {
return value
}
value = this.born <=> obj.born
if (value != 0) {
return value
}
return 0
}
This Person
class can be used as follows:
def people = [
new Person(first: 'Ben', last: 'Affleck', born: 1972),
new Person(first: 'Ben', last: 'Stiller', born: 1965)
]
assert people.sort()*.last == ['Stiller', 'Affleck']
The @Builder
AST transformation is used to help write classes that can be created using fluent api calls.
The transform supports multiple building strategies to cover a range of cases and there are a number
of configuration options to customize the building process. If you’re an AST hacker, you can also define your own
strategy class. The following table lists the available strategies that are bundled with Groovy and the
configuration options each strategy supports.
Strategy |
Description |
builderClassName |
builderMethodName |
buildMethodName |
prefix |
includes/excludes |
|
chained setters |
n/a |
n/a |
n/a |
yes, default "set" |
yes |
|
explicit builder class, class being built untouched |
n/a |
n/a |
yes, default "build" |
yes, default "" |
yes |
|
creates a nested helper class |
yes, default <TypeName>Builder |
yes, default "builder" |
yes, default "build" |
yes, default "" |
yes |
|
creates a nested helper class providing type-safe fluent creation |
yes, default <TypeName>Initializer |
yes, default "createInitializer" |
yes, default "create" but usually only used internally |
yes, default "" |
yes |
To use the SimpleStrategy
, annotate your Groovy class using the @Builder
annotation, and specify the strategy as shown in this example:
import groovy.transform.builder.*
@Builder(builderStrategy=SimpleStrategy)
class Person {
String first
String last
Integer born
}
Then, just call the setters in a chained fashion as shown here:
def p1 = new Person().setFirst('Johnny').setLast('Depp').setBorn(1963)
assert "$p1.first $p1.last" == 'Johnny Depp'
For each property, a generated setter will be created which looks like this:
public Person setFirst(java.lang.String first) {
this.first = first
return this
}
You can specify a prefix as shown in this example:
import groovy.transform.builder.*
@Builder(builderStrategy=SimpleStrategy, prefix="")
class Person {
String first
String last
Integer born
}
And calling the chained setters would look like this:
def p = new Person().first('Johnny').last('Depp').born(1963)
assert "$p.first $p.last" == 'Johnny Depp'
You can use the SimpleStrategy
in conjunction with @Canonical
. If your @Builder
annotation doesn’t have
explicit includes
or excludes
annotation attributes but your @Canonical
annotation does, the ones
from @Canonical
will be re-used for @Builder
.
The annotation attributes builderClassName
, buildMethodName
, builderMethodName
and forClass
are not supported for this strategy.
Groovy already has built-in building mechanisms. Don’t rush to using @Builder if the built-in mechanisms meet your needs. Some examples:
|
def p2 = new Person(first: 'Keira', last: 'Knightley', born: 1985)
def p3 = new Person().with {
first = 'Geoffrey'
last = 'Rush'
born = 1951
}
To use the ExternalStrategy
, create and annotate a Groovy builder class using the @Builder
annotation, specify the
class the builder is for using forClass
and indicate use of the ExternalStrategy
.
Suppose you have the following class you would like a builder for:
class Person {
String first
String last
int born
}
you explicitly create and use your builder class as follows:
import groovy.transform.builder.*
@Builder(builderStrategy=ExternalStrategy, forClass=Person)
class PersonBuilder { }
def p = new PersonBuilder().first('Johnny').last('Depp').born(1963).build()
assert "$p.first $p.last" == 'Johnny Depp'
Note that the (normally empty) builder class you provide will be filled in with appropriate setters and a build method. The generated build method will look something like:
public Person build() {
Person _thePerson = new Person()
_thePerson.first = first
_thePerson.last = last
_thePerson.born = born
return _thePerson
}
The class you are creating the builder for can be any Java or Groovy class following the normal JavaBean conventions, e.g. a no-arg constructor and setters for the properties. Here is an example using a Java class:
import groovy.transform.builder.*
@Builder(builderStrategy=ExternalStrategy, forClass=javax.swing.DefaultButtonModel)
class ButtonModelBuilder {}
def model = new ButtonModelBuilder().enabled(true).pressed(true).armed(true).rollover(true).selected(true).build()
assert model.isArmed()
assert model.isPressed()
assert model.isEnabled()
assert model.isSelected()
assert model.isRollover()
The generated builder can be customised using the prefix
, includes
, excludes
and buildMethodName
annotation attributes.
Here is an example illustrating various customisations:
import groovy.transform.builder.*
import groovy.transform.Canonical
@Canonical
class Person {
String first
String last
int born
}
@Builder(builderStrategy=ExternalStrategy, forClass=Person, includes=['first', 'last'], buildMethodName='create', prefix='with')
class PersonBuilder { }
def p = new PersonBuilder().withFirst('Johnny').withLast('Depp').create()
assert "$p.first $p.last" == 'Johnny Depp'
The builderMethodName
and builderClassName
annotation attributes for @Builder
aren’t applicable for this strategy.
You can use the ExternalStrategy
in conjunction with @Canonical
. If your @Builder
annotation doesn’t have
explicit includes
or excludes
annotation attributes but the @Canonical
annotation of the class you are creating
the builder for does, the ones from @Canonical
will be re-used for @Builder
.
To use the DefaultStrategy
, annotate your Groovy class using the @Builder
annotation as shown in this example:
import groovy.transform.builder.Builder
@Builder
class Person {
String firstName
String lastName
int age
}
def person = Person.builder().firstName("Robert").lastName("Lewandowski").age(21).build()
assert person.firstName == "Robert"
assert person.lastName == "Lewandowski"
assert person.age == 21
If you want, you can customize various aspects of the building process
using the builderClassName
, buildMethodName
, builderMethodName
, prefix
, includes
and excludes
annotation attributes,
some of which are used in the example here:
import groovy.transform.builder.Builder
@Builder(buildMethodName='make', builderMethodName='maker', prefix='with', excludes='age')
class Person {
String firstName
String lastName
int age
}
def p = Person.maker().withFirstName("Robert").withLastName("Lewandowski").make()
assert "$p.firstName $p.lastName" == "Robert Lewandowski"
This strategy also supports annotating static methods and constructors. In this case, the static method or constructor
parameters become the properties to use for building purposes and in the case of static methods, the return type
of the method becomes the target class being built. If you have more than one @Builder
annotation used within
a class (at either the class, method or constructor positions) then it is up to you to ensure that the generated
helper classes and factory methods have unique names (i.e. no more than one can use the default name values).
Here is an example highlighting method and constructor usage (and also illustrating the renaming required for unique names).
import groovy.transform.builder.*
import groovy.transform.*
@ToString
@Builder
class Person {
String first, last
int born
Person(){}
@Builder(builderClassName='MovieBuilder', builderMethodName='byRoleBuilder')
Person(String roleName) {
if (roleName == 'Jack Sparrow') {
this.first = 'Johnny'; this.last = 'Depp'; this.born = 1963
}
}
@Builder(builderClassName='NameBuilder', builderMethodName='nameBuilder', prefix='having', buildMethodName='fullName')
static String join(String first, String last) {
first + ' ' + last
}
@Builder(builderClassName='SplitBuilder', builderMethodName='splitBuilder')
static Person split(String name, int year) {
def parts = name.split(' ')
new Person(first: parts[0], last: parts[1], born: year)
}
}
assert Person.splitBuilder().name("Johnny Depp").year(1963).build().toString() == 'Person(Johnny, Depp, 1963)'
assert Person.byRoleBuilder().roleName("Jack Sparrow").build().toString() == 'Person(Johnny, Depp, 1963)'
assert Person.nameBuilder().havingFirst('Johnny').havingLast('Depp').fullName() == 'Johnny Depp'
assert Person.builder().first("Johnny").last('Depp').born(1963).build().toString() == 'Person(Johnny, Depp, 1963)'
The forClass
annotation attribute is not supported for this strategy.
To use the InitializerStrategy
, annotate your Groovy class using the @Builder
annotation, and specify the strategy as shown in this example:
import groovy.transform.builder.*
import groovy.transform.*
@ToString
@Builder(builderStrategy=InitializerStrategy)
class Person {
String firstName
String lastName
int age
}
Your class will be locked down to have a single public constructor taking a "fully set" initializer. It will also have a factory method to create the initializer. These are used as follows:
@CompileStatic
def firstLastAge() {
assert new Person(Person.createInitializer().firstName("John").lastName("Smith").age(21)).toString() == 'Person(John, Smith, 21)'
}
firstLastAge()
Any attempt to use the initializer which doesn’t involve setting all the properties (though order is not important) will result in
a compilation error. If you don’t need this level of strictness, you don’t need to use @CompileStatic
.
You can use the InitializerStrategy
in conjunction with @Canonical
and @Immutable
. If your @Builder
annotation
doesn’t have explicit includes
or excludes
annotation attributes but your @Canonical
annotation does, the ones
from @Canonical
will be re-used for @Builder
. Here is an example using @Builder
with @Immutable
:
import groovy.transform.builder.*
import groovy.transform.*
@Builder(builderStrategy=InitializerStrategy)
@Immutable
class Person {
String first
String last
int born
}
@CompileStatic
def createFirstLastBorn() {
def p = new Person(Person.createInitializer().first('Johnny').last('Depp').born(1963))
assert "$p.first $p.last $p.born" == 'Johnny Depp 1963'
}
createFirstLastBorn()
The annotation attribute forClass
is not supported for this strategy.
Class design annotations
This category of annotations are aimed at simplifying the implementation of well-known design patterns (delegation, singleton, …) by using a declarative style.
The @Delegate
AST transformation aims at implementing the delegation design pattern. In the following class:
class Event {
@Delegate Date when
String title
}
The when
field is annotated with @Delegate
, meaning that the Event
class will delegate calls to Date
methods
to the when
field. In this case, the generated code looks like this:
class Event {
Date when
String title
boolean before(Date other) {
when.before(other)
}
// ...
}
Then you can call the before
method, for example, directly on the Event
class:
def ev = new Event(title:'Groovy keynote', when: Date.parse('yyyy/MM/dd', '2013/09/10'))
def now = new Date()
assert ev.before(now)
The behavior of the @Delegate
AST transformation can be changed using the following parameters:
Attribute | Default value | Description | Example |
---|---|---|---|
interfaces |
True |
Should the interfaces implemented by the field be implemented by the class too |
|
deprecated |
false |
If true, also delegates methods annotated with @Deprecated |
|
methodAnnotations |
False |
Whether to carry over annotations from the methods of the delegate to your delegating method. |
|
parameterAnnotations |
False |
Whether to carry over annotations from the method parameters of the delegate to your delegating method. |
|
excludes |
Empty array |
A list of methods to be excluded from delegation. For more fine-grained control, see also |
|
includes |
Empty array |
A list of methods to be included in delegation. For more fine-grained control, see also |
|
excludeTypes |
Empty array |
A list of interfaces containing method signatures to be excluded from delegation |
|
includeTypes |
Empty array |
A list of interfaces containing method signatures to be included in delegation |
|
The @Immutable
AST transformation simplifies the creation of immutable classes, that is to say classes for which
members are deemed immutable. For that, all you have to do is annotating the class like in the following example:
import groovy.transform.Immutable
@Immutable
class Point {
int x
int y
}
Immutable classes generated with @Immutable
are automatically made final. For a class to be immutable, you have to
make sure that properties are of an immutable type (primitive or boxed types), of a known-immutable type or another
class annotated with @Immutable
. The effect of applying @Immutable
to a class are pretty similar to those of
applying the @Canonical AST transformation, but with an immutable class: automatic generation of
toString
, equals
and hashCode
methods for example, but trying to modify a property would throw a ReadOnlyPropertyException
in that case.
Since @Immutable
relies on a predefined list of known immutable classes (like java.net.URI
or java.lang.String
and fails if you use a type which is not in that list, you are allowed to instruct the transformation that some types
are deemed immutable thanks to the following parameters:
Attribute | Default value | Description | Example |
---|---|---|---|
knownImmutableClasses |
Empty list |
A list of classes which are deemed immutable. |
|
knownImmutables |
Empty list |
A list of property names which are deemed immutable. |
|
copyWith |
false |
A boolean whether to generate a |
|
The @Memoized
AST transformations simplifies the implementation of caching by allowing the result of method calls
to be cached just by annotating the method with @Memoized
. Let’s imagine the following method:
long longComputation(int seed) {
// slow computation
Thread.sleep(1000*seed)
System.nanoTime()
}
This emulates a long computation, based on the actual parameters of the method. Without @Memoized
, each method call
would take several seconds plus it would return a random result:
def x = longComputation(1)
def y = longComputation(1)
assert x!=y
Adding @Memoized
changes the semantics of the method by adding caching, based on the parameters:
@Memoized
long longComputation(int seed) {
// slow computation
Thread.sleep(1000*seed)
System.nanoTime()
}
def x = longComputation(1) // returns after 1 second
def y = longComputation(1) // returns immediatly
def z = longComputation(2) // returns after 2 seconds
assert x==y
assert x!=z
The size of the cache can be configured using two optional parameters:
-
protectedCacheSize: the number of results which are guaranteed not to be cleared after garbage collection
-
maxCacheSize: the maximum number of results that can be kept in memory
By default, the size of the cache is unlimited and no cache result is protected from garbage collection. Setting a protectedCacheSize>0 would create an unlimited cache with some results protected. Setting maxCacheSize>0 would create a limited cache but without any protection from garbage protection. Setting both would create a limited, protected cache.
The @Singleton
annotation can be used to implement the singleton design pattern on a class. The singleton instance
is defined eagerly by default, using class initialization, or lazily, in which case the field is initialized using
double checked locking.
@Singleton
class GreetingService {
String greeting(String name) { "Hello, $name!" }
}
assert GreetingService.instance.greeting('Bob') == 'Hello, Bob!'
By default, the singleton is created eagerly when the class is initialized and available through the instance
property.
It is possible to change the name of the singleton using the property
parameter:
@Singleton(property='theOne')
class GreetingService {
String greeting(String name) { "Hello, $name!" }
}
assert GreetingService.theOne.greeting('Bob') == 'Hello, Bob!'
And it is also possible to make initialization lazy using the lazy
parameter:
class Collaborator {
public static boolean init = false
}
@Singleton(lazy=true,strict=false)
class GreetingService {
static void init() {}
GreetingService() {
Collaborator.init = true
}
String greeting(String name) { "Hello, $name!" }
}
GreetingService.init() // make sure class is initialized
assert Collaborator.init == false
GreetingService.instance
assert Collaborator.init == true
assert GreetingService.instance.greeting('Bob') == 'Hello, Bob!'
In this example, we also set the strict
parameter to false, which allows us to define our own constructor.
Logging improvements
Groovy provides AST transformation that helps integrating with the most widely used logging frameworks. It’s worth noting that annotating a class with one of those annotations doesn’t prevent you from adding the appropriate logging framework on classpath.
All transformations work in a similar way:
-
add static final
log
field corresponding to the logger -
wrap all calls to
log.level()
into the appropriatelog.isLevelEnabled
guard, depending on the underlying framework
Those transformations support two parameters:
-
value
(defaultlog
) corresponds to the name of the logger field -
category
(defaults to the class name) is the name of the logger category
The first logging AST transformation available is the @Log
annotation which relies on the JDK logging framework. Writing:
@groovy.util.logging.Log
class Greeter {
void greet() {
log.info 'Called greeter'
println 'Hello, world!'
}
}
is equivalent to writing:
import java.util.logging.Level
import java.util.logging.Logger
class Greeter {
private static final Logger log = Logger.getLogger(Greeter.name)
void greet() {
if (log.isLoggable(Level.INFO)) {
log.info 'Called greeter'
}
println 'Hello, world!'
}
}
Groovy supports the Apache Commons Logging framework using to the
@Commons
annotation. Writing:
@groovy.util.logging.Commons
class Greeter {
void greet() {
log.debug 'Called greeter'
println 'Hello, world!'
}
}
is equivalent to writing:
import org.apache.commons.logging.LogFactory
import org.apache.commons.logging.Log
class Greeter {
private static final Log log = LogFactory.getLog(Greeter)
void greet() {
if (log.isDebugEnabled()) {
log.debug 'Called greeter'
}
println 'Hello, world!'
}
}
Groovy supports the Apache Log4j 1.x framework using to the
@Log4j
annotation. Writing:
@groovy.util.logging.Log4j
class Greeter {
void greet() {
log.debug 'Called greeter'
println 'Hello, world!'
}
}
is equivalent to writing:
import org.apache.log4j.Logger
class Greeter {
private static final Logger log = Logger.getLogger(Greeter)
void greet() {
if (log.isDebugEnabled()) {
log.debug 'Called greeter'
}
println 'Hello, world!'
}
}
Groovy supports the Apache Log4j 2.x framework using to the
@Log4j2
annotation. Writing:
@groovy.util.logging.Log4j2
class Greeter {
void greet() {
log.debug 'Called greeter'
println 'Hello, world!'
}
}
is equivalent to writing:
import org.apache.logging.log4j.LogManager
import org.apache.logging.log4j.Logger
class Greeter {
private static final Logger log = LogManager.getLogger(Greeter)
void greet() {
if (log.isDebugEnabled()) {
log.debug 'Called greeter'
}
println 'Hello, world!'
}
}
Groovy supports the Simple Logging Facade for Java (SLF4J) framework using to the
@Slf4j
annotation. Writing:
@groovy.util.logging.Slf4j
class Greeter {
void greet() {
log.debug 'Called greeter'
println 'Hello, world!'
}
}
is equivalent to writing:
import org.slf4j.LoggerFactory
import org.slf4j.Logger
class Greeter {
private static final Logger log = LoggerFactory.getLogger(Greeter)
void greet() {
if (log.isDebugEnabled()) {
log.debug 'Called greeter'
}
println 'Hello, world!'
}
}
Declarative concurrency
The Groovy language provides a set of annotations aimed at simplifying common concurrency patterns in a declarative approach.
The @Synchronized
AST transformations works in a similar way to the synchronized
keyword but locks on different
objects for safer concurrency. It can be applied on any method or static method:
import groovy.transform.Synchronized
import java.util.concurrent.Executors
import java.util.concurrent.TimeUnit
class Counter {
int cpt
@Synchronized
int incrementAndGet() {
cpt++
}
int get() {
cpt
}
}
Writing this is equivalent to creating a lock object and wrapping the whole method into a synchronized block:
class Counter {
int cpt
private final Object $lock = new Object()
int incrementAndGet() {
synchronized($lock) {
cpt++
}
}
int get() {
cpt
}
}
By default, @Synchronized
creates a field named $lock
(or $LOCK
for a static method) but you can make it use any
field you want by specifying the value attribute, like in the following example:
import groovy.transform.Synchronized
import java.util.concurrent.Executors
import java.util.concurrent.TimeUnit
class Counter {
int cpt
private final Object myLock = new Object()
@Synchronized('myLock')
int incrementAndGet() {
cpt++
}
int get() {
cpt
}
}
The @WithReadLock
AST transformation works in conjunction with the @WithWriteLock
transformation
to provide read/write synchronization using the ReentrantReadWriteLock
facility that the JDK provides. The annotation
can be added to a method or a static method. It will transparently create a $reentrantLock
final field (or
$REENTRANTLOCK
for a static method) and proper synchronization code will be added. For example, the following code:
import groovy.transform.WithReadLock
import groovy.transform.WithWriteLock
class Counters {
public final Map<String,Integer> map = [:].withDefault { 0 }
@WithReadLock
int get(String id) {
map.get(id)
}
@WithWriteLock
void add(String id, int num) {
Thread.sleep(200) // emulate long computation
map.put(id, map.get(id)+num)
}
}
is equivalent to this:
import groovy.transform.WithReadLock as WithReadLock
import groovy.transform.WithWriteLock as WithWriteLock
public class Counters {
private final Map<String, Integer> map
private final java.util.concurrent.locks.ReentrantReadWriteLock $reentrantlock
public int get(java.lang.String id) {
$reentrantlock.readLock().lock()
try {
map.get(id)
}
finally {
$reentrantlock.readLock().unlock()
}
}
public void add(java.lang.String id, int num) {
$reentrantlock.writeLock().lock()
try {
java.lang.Thread.sleep(200)
map.put(id, map.get(id) + num )
}
finally {
$reentrantlock.writeLock().unlock()
}
}
}
Both @WithReadLock
and @WithWriteLock
support specifying an alternative lock object. In that case, the referenced
field must be declared by the user, like in the following alternative:
import groovy.transform.WithReadLock
import groovy.transform.WithWriteLock
import java.util.concurrent.locks.ReentrantReadWriteLock
class Counters {
public final Map<String,Integer> map = [:].withDefault { 0 }
private final ReentrantReadWriteLock customLock = new ReentrantReadWriteLock()
@WithReadLock('customLock')
int get(String id) {
map.get(id)
}
@WithWriteLock('customLock')
void add(String id, int num) {
Thread.sleep(200) // emulate long computation
map.put(id, map.get(id)+num)
}
}
For details
-
See Javadoc for
groovy.transform.WithReadLock
-
See Javadoc for
groovy.transform.WithWriteLock
Easier cloning and externalizing
Groovy provides two annotations aimed at facilitating the implementation of Clonable
and Externalizable
interfaces,
respectively named @AutoClone
and @AutoExternalize
.
The @AutoClone
annotation is aimed at implementing the @java.lang.Cloneable
interface using various strategies, thanks to the style
parameter:
-
the default
AutoCloneStyle.CLONE
strategy callssuper.clone()
first thenclone()
on each cloneable property -
the
AutoCloneStyle.SIMPLE
strategy uses a regular constructor call and copies properties from the source to the clone -
the
AutoCloneStyle.COPY_CONSTRUCTOR
strategy creates and uses a copy constructor -
the
AutoCloneStyle.SERIALIZATION
strategy uses serialization (or externalization) to clone the object
Each of those strategies have pros and cons which are discussed in the Javadoc for groovy.transform.AutoClone
and groovy.transform.AutoCloneStyle
.
For example, the following example:
import groovy.transform.AutoClone
@AutoClone
class Book {
String isbn
String title
List<String> authors
Date publicationDate
}
is equivalent to this:
class Book implements Cloneable {
String isbn
String title
List<String> authors
Date publicationDate
public Book clone() throws CloneNotSupportedException {
Book result = super.clone()
result.authors = authors instanceof Cloneable ? (List) authors.clone() : authors
result.publicationDate = publicationDate.clone()
result
}
}
Note that the String properties aren’t explicitly handled because Strings are immutable and the clone()
method from Object
will copy the String references. The same would apply to primitive fields and most of the concrete subclasses of java.lang.Number
.
In addition to cloning styles, @AutoClone
supports multiple options:
Attribute | Default value | Description | Example |
---|---|---|---|
excludes |
Empty list |
A list of property or field names that need to be excluded from cloning. A string consisting of a comma-separated field/property names is also allowed.
See |
|
includeFields |
false |
By default, only properties are cloned. Setting this flag to true will also clone fields. |
|
The @AutoExternalize
AST transformation will assist in the creation of java.io.Externalizable
classes. It will
automatically add the interface to the class and generate the writeExternal
and readExternal
methods. For example, this
code:
import groovy.transform.AutoExternalize
@AutoExternalize
class Book {
String isbn
String title
float price
}
will be converted into:
class Book implements java.io.Externalizable {
String isbn
String title
float price
void writeExternal(ObjectOutput out) throws IOException {
out.writeObject(isbn)
out.writeObject(title)
out.writeFloat( price )
}
public void readExternal(ObjectInput oin) {
isbn = (String) oin.readObject()
title = (String) oin.readObject()
price = oin.readFloat()
}
}
The @AutoExternalize
annotation supports two parameters which will let you slightly customize its behavior:
Attribute | Default value | Description | Example |
---|---|---|---|
excludes |
Empty list |
A list of property or field names that need to be excluded from externalizing. A string consisting of a comma-separated field/property names is also allowed.
See |
|
includeFields |
false |
By default, only properties are externalized. Setting this flag to true will also clone fields. |
|
Safer scripting
The Groovy language makes it easy to execute user scripts at runtime (for example using groovy.lang.GroovyShell
),
but how do you make sure that a script won’t eat all CPU (infinite loops) or that concurrent scripts won’t slowly consume
all available threads of a thread pool? Groovy provides several annotations which are aimed towards safer scripting,
generating code which will for example allow you to interrupt execution automatically.
One complicated situation in the JVM world is when a thread can’t be stopped. The Thread#stop
method exists but is
deprecated (and isn’t reliable) so your only chance relies in Thread#interrupt
. Calling the latter will set the
interrupt
flag on the thread, but it will not stop the execution of the thread. This is problematic because it’s the
responsibility of the code executing in the thread to check the interrupt flag and properly exit. This makes sense when
you, as a developer, know that the code you are executing is meant to be run in an independent thread, but in general,
you don’t know it. It’s even worse with user scripts, who might not even know what a thread is (think of DSLs).
@ThreadInterrupt
simplifies this by adding thread interruption checks at critical places in the code:
-
loops (for, while)
-
first instruction of a method
-
first instruction of a closure body
Let’s imagine the following user script:
while (true) {
i++
}
This is an obvious infinite loop. If this code executes in its own thread, interrupting wouldn’t help: if you join
on
the thread, then the calling code would be able to continue, but the thread would still be alive, running in background
without any ability for you to stop it, slowly causing thread starvation.
One possibility to work around this is to set up your shell this way:
def config = new CompilerConfiguration()
config.addCompilationCustomizers(
new ASTTransformationCustomizer(ThreadInterrupt)
)
def binding = new Binding(i:0)
def shell = new GroovyShell(binding,config)
The shell is then configured to automatically apply the @ThreadInterrupt
AST transformations on all scripts. This allows
you to execute user scripts this way:
def t = Thread.start {
shell.evaluate(userCode)
}
t.join(500) // give at most 500ms for the script to complete
if (t.alive) {
t.interrupt()
}
The transformation automatically modified user code like this:
while (true) {
if (Thread.currentThread().interrupted) {
throw new InterruptedException('The current thread has been interrupted.')
}
i++
}
The check which is introduced inside the loop guarantees that if the interrupt
flag is set on the current thread, an
exception will be thrown, interrupting the execution of the thread.
@ThreadInterrupt
supports multiple options that will let you further customize the behavior of the transformation:
Attribute | Default value | Description | Example |
---|---|---|---|
thrown |
|
Specifies the type of exception which is thrown if the thread is interrupted. |
|
checkOnMethodStart |
true |
Should an interruption check be inserted at the beginning of each method body. See |
|
applyToAllClasses |
true |
Should the transformation be applied on all classes of the same source unit (in the same source file). See |
|
applyToAllMembers |
true |
Should the transformation be applied on all members of class. See |
|
The @TimedInterrupt
AST transformation tries to solve a slightly different problem from @groovy.transform.ThreadInterrupt: instead of checking the interrupt
flag of the thread, it will automatically
throw an exception if the thread has been running for too long.
This annotation does not spawn a monitoring thread. Instead, it works in a similar manner as @ThreadInterrupt by placing checks at appropriate places in the code. This means that if you
have a thread blocked by I/O, it will not be interrupted.
|
Imagine the following user code:
def fib(int n) { n<2?n:fib(n-1)+fib(n-2) }
result = fib(600)
The implementation of the famous Fibonacci number computation here is far from optimized. If it is called with a high n
value, it can take minutes to answer. With @TimedInterrupt
, you can
choose how long a script is allowed to run. The following setup code will allow the user script to run for 1 second at max:
def config = new CompilerConfiguration()
config.addCompilationCustomizers(
new ASTTransformationCustomizer(value:1, TimedInterrupt)
)
def binding = new Binding(result:0)
def shell = new GroovyShell(this.class.classLoader, binding,config)
This code is equivalent to annotating a class with @TimedInterrupt
like this:
@TimedInterrup(value=1, unit=TimeUnit.SECONDS)
class MyClass {
def fib(int n) {
n<2?n:fib(n-1)+fib(n-2)
}
}
@TimedInterrupt
supports multiple options that will let you further customize the behavior of the transformation:
Attribute | Default value | Description | Example |
---|---|---|---|
value |
Long.MAX_VALUE |
Used in combination with |
|
unit |
TimeUnit.SECONDS |
Used in combination with |
|
thrown |
|
Specifies the type of exception which is thrown if timeout is reached. |
|
checkOnMethodStart |
true |
Should an interruption check be inserted at the beginning of each method body. See |
|
applyToAllClasses |
true |
Should the transformation be applied on all classes of the same source unit (in the same source file). See |
|
applyToAllMembers |
true |
Should the transformation be applied on all members of class. See |
|
@TimedInterrupt is currently not compatible with static methods!
|
The last annotation for safer scripting is the base annotation when you want to interrupt a script using a custom strategy. In particular, this is the annotation of choice if you
want to use resource management (limit the number of calls to an API, …). In the following example, user code is using an infinite loop, but @ConditionalInterrupt
will allow us
to check a quota manager and interrupt automatically the script:
@ConditionalInterrupt({Quotas.disallow('user')})
class UserCode {
void doSomething() {
int i=0
while (true) {
println "Consuming resources ${++i}"
}
}
}
The quota checking is very basic here, but it can be any code:
class Quotas {
static def quotas = [:].withDefault { 10 }
static boolean disallow(String userName) {
println "Checking quota for $userName"
(quotas[userName]--)<0
}
}
We can make sure @ConditionalInterrupt
works properly using this test code:
assert Quotas.quotas['user'] == 10
def t = Thread.start {
new UserCode().doSomething()
}
t.join(1000)
assert !t.alive
assert Quotas.quotas['user'] < 0
Of course, in practice, it is unlikely that @ConditionalInterrupt
will be itself added by hand on user code. It can be injected in a similar manner as the example shown in the
ThreadInterrupt section, using the org.codehaus.groovy.control.customizers.ASTTransformationCustomizer
:
def config = new CompilerConfiguration()
def checkExpression = new ClosureExpression(
Parameter.EMPTY_ARRAY,
new ExpressionStatement(
new MethodCallExpression(new ClassExpression(ClassHelper.make(Quotas)), 'disallow', new ConstantExpression('user'))
)
)
config.addCompilationCustomizers(
new ASTTransformationCustomizer(value: checkExpression, ConditionalInterrupt)
)
def shell = new GroovyShell(this.class.classLoader,new Binding(),config)
def userCode = """
int i=0
while (true) {
println "Consuming resources \\${++i}"
}
"""
assert Quotas.quotas['user'] == 10
def t = Thread.start {
shell.evaluate(userCode)
}
t.join(1000)
assert !t.alive
assert Quotas.quotas['user'] < 0
@ConditionalInterrupt
supports multiple options that will let you further customize the behavior of the transformation:
Attribute | Default value | Description | Example |
---|---|---|---|
value |
The closure which will be called to check if execution is allowed. If the closure returns false, execution is allowed. If it returns true, then an exception will be thrown. |
|
|
thrown |
|
Specifies the type of exception which is thrown if execution should be aborted. |
|
checkOnMethodStart |
true |
Should an interruption check be inserted at the beginning of each method body. See |
|
applyToAllClasses |
true |
Should the transformation be applied on all classes of the same source unit (in the same source file). See |
|
applyToAllMembers |
true |
Should the transformation be applied on all members of class. See |
|
Compiler directives
This category of AST transformations groups annotations which have a direct impact on the semantics of the code, rather than focusing on code generation. With that regards, they can be seen as compiler directives that either change the behavior of a program at compile time or runtime.
The @Field
annotation only makes sense in the context of a script and aims at solving a common scoping error with
scripts. The following example will for example fail at runtime:
def x
String line() {
"="*x
}
x=3
assert "===" == line()
x=5
assert "=====" == line()
The error that is thrown may be difficult to interpret: groovy.lang.MissingPropertyException: No such property: x
. The reason is that scripts are compiled
to classes and the script body is itself compiled as a single run() method. Methods which are defined in the scripts are independent, so the code above is
equivalent to this:
class MyScript extends Script {
String line() {
"="*x
}
public def run() {
def x
x=3
assert "===" == line()
x=5
assert "=====" == line()
}
}
So def x
is effectiveley interpreted as a local variable, outside of the scope of the line
method. The @Field
AST transformation aims at fixing this
by changing the scope of the variable to a field of the enclosing script:
@Field def x
String line() {
"="*x
}
x=3
assert "===" == line()
x=5
assert "=====" == line()
The resulting, equivalent, code is now:
class MyScript extends Script {
def x
String line() {
"="*x
}
public def run() {
x=3
assert "===" == line()
x=5
assert "=====" == line()
}
}
By default, Groovy visibility rules imply that if you create a field without specifying a modifier, then the field is interpreted as a property:
class Person {
String name // this is a property
}
Should you want to create a package private field instead of a property (private field+getter/setter), then annotate your field with @PackageScope
:
class Person {
@PackageScope String name // not a property anymore
}
@AnnotationCollector
allows the creation of meta-annotation, which are described in a dedicated section.
@TypeChecked
activates compile-time type checking on your Groovy code. See section on type checking for details.
@CompileStatic
activates static compilation on your Groovy code. See section on type checking for details.
@CompileDynamic
disables static compilation on parts of your Groovy code. See section on type checking for details.
@DelegatesTo
is not, technically speaking, an AST transformation. It is aimed at documenting code and helping the compiler in case you are
using type checking or static compilation. The annotation is described thoroughly in the
DSL section of this guide.
Swing patterns
@Bindable
is an AST transformation that transforms a regular property into a bound property (according to the JavaBeans specification).
The @Bindable
annotation can be placed on a property or a class. To convert all properties of a class into bound properties, on can annotate the class like in this example:
import groovy.beans.Bindable
@Bindable
class Person {
String name
int age
}
This is equivalent to writing this:
import java.beans.PropertyChangeListener
import java.beans.PropertyChangeSupport
class Person {
final private PropertyChangeSupport this$propertyChangeSupport
String name
int age
public void addPropertyChangeListener(PropertyChangeListener listener) {
this$propertyChangeSupport.addPropertyChangeListener(listener)
}
public void addPropertyChangeListener(String name, PropertyChangeListener listener) {
this$propertyChangeSupport.addPropertyChangeListener(name, listener)
}
public void removePropertyChangeListener(PropertyChangeListener listener) {
this$propertyChangeSupport.removePropertyChangeListener(listener)
}
public void removePropertyChangeListener(String name, PropertyChangeListener listener) {
this$propertyChangeSupport.removePropertyChangeListener(name, listener)
}
public void firePropertyChange(String name, Object oldValue, Object newValue) {
this$propertyChangeSupport.firePropertyChange(name, oldValue, newValue)
}
public PropertyChangeListener[] getPropertyChangeListeners() {
return this$propertyChangeSupport.getPropertyChangeListeners()
}
public PropertyChangeListener[] getPropertyChangeListeners(String name) {
return this$propertyChangeSupport.getPropertyChangeListeners(name)
}
}
@Bindable
therefore removes a lot of boilerplate from your class, dramatically increasing readability. If the annotation is put on a single property, only that property is bound:
import groovy.beans.Bindable
class Person {
String name
@Bindable int age
}
The @ListenerList
AST transformation generates code for adding, removing and getting the list of listeners to a class, just by annotating a collection property:
import java.awt.event.ActionListener
import groovy.beans.ListenerList
class Component {
@ListenerList
List<ActionListener> listeners;
}
The transform will generate the appropriate add/remove methods based on the generic type of the list. In addition, it will also create fireXXX
methods based on the public methods declared on the class:
import java.awt.event.ActionEvent
import java.awt.event.ActionListener as ActionListener
import groovy.beans.ListenerList as ListenerList
public class Component {
@ListenerList
private List<ActionListener> listeners
public void addActionListener(ActionListener listener) {
if ( listener == null) {
return
}
if ( listeners == null) {
listeners = []
}
listeners.add(listener)
}
public void removeActionListener(ActionListener listener) {
if ( listener == null) {
return
}
if ( listeners == null) {
listeners = []
}
listeners.remove(listener)
}
public ActionListener[] getActionListeners() {
Object __result = []
if ( listeners != null) {
__result.addAll(listeners)
}
return (( __result ) as ActionListener[])
}
public void fireActionPerformed(ActionEvent param0) {
if ( listeners != null) {
ArrayList<ActionListener> __list = new ArrayList<ActionListener>(listeners)
for (def listener : __list ) {
listener.actionPerformed(param0)
}
}
}
}
@Bindable
supports multiple options that will let you further customize the behavior of the transformation:
Attribute | Default value | Description | Example |
---|---|---|---|
name |
Generic type name |
By default, the suffix which will be appended to add/remove/… methods is the simple class name of the generic type of the list. |
|
synchronize |
false |
If set to true, generated methods will be synchronized |
|
The @Vetoable
annotation works in a similar manner to @Bindable
but generates constrained property according to the JavaBeans specification, instead of bound properties. The annotation
can be placed on a class, meaning that all properties will be converted to constrained properties, or on a single property. For example, annotating this class with @Vetoable
:
import groovy.beans.Vetoable
import java.beans.PropertyVetoException
import java.beans.VetoableChangeListener
@Vetoable
class Person {
String name
int age
}
is equivalent to writing this:
public class Person {
private String name
private int age
final private java.beans.VetoableChangeSupport this$vetoableChangeSupport
public void addVetoableChangeListener(VetoableChangeListener listener) {
this$vetoableChangeSupport.addVetoableChangeListener(listener)
}
public void addVetoableChangeListener(String name, VetoableChangeListener listener) {
this$vetoableChangeSupport.addVetoableChangeListener(name, listener)
}
public void removeVetoableChangeListener(VetoableChangeListener listener) {
this$vetoableChangeSupport.removeVetoableChangeListener(listener)
}
public void removeVetoableChangeListener(String name, VetoableChangeListener listener) {
this$vetoableChangeSupport.removeVetoableChangeListener(name, listener)
}
public void fireVetoableChange(String name, Object oldValue, Object newValue) throws PropertyVetoException {
this$vetoableChangeSupport.fireVetoableChange(name, oldValue, newValue)
}
public VetoableChangeListener[] getVetoableChangeListeners() {
return this$vetoableChangeSupport.getVetoableChangeListeners()
}
public VetoableChangeListener[] getVetoableChangeListeners(String name) {
return this$vetoableChangeSupport.getVetoableChangeListeners(name)
}
public void setName(String value) throws PropertyVetoException {
this.fireVetoableChange('name', name, value)
name = value
}
public void setAge(int value) throws PropertyVetoException {
this.fireVetoableChange('age', age, value)
age = value
}
}
If the annotation is put on a single property, only that property is made vetoable:
import groovy.beans.Vetoable
class Person {
String name
@Vetoable int age
}
Test assistance
@NotYetImplemented
is used to invert the result of a JUnit 3/4 test case. It is in particular useful if a feature is not yet implemented but the test is. In that case, it is expected
that the test fails. Marking it with @NotYetImplemented
will inverse the result of the test, like in this example:
import groovy.transform.NotYetImplemented
class Maths {
static int fib(int n) {
// todo: implement later
}
}
class MathsTest extends GroovyTestCase {
@NotYetImplemented
void testFib() {
def dataTable = [
1:1,
2:1,
3:2,
4:3,
5:5,
6:8,
7:13
]
dataTable.each { i, r ->
assert Maths.fib(i) == r
}
}
}
Another advantage of using this technique is that you can write test cases for bugs before knowing how to fix them. If some time in the future, a modification in the code fixes a bug by side effect, you’ll be notified because a test which was expected to fail passed.
@ASTTest
is a special AST transformation meant to help debugging other AST transformations or the Groovy compiler itself. It will let the developer "explore" the AST during compilation and
perform assertions on the AST rather than on the result of compilation. This means that this AST transformations gives access to the AST before the bytecode is produced. @ASTTest
can be
placed on any annotable node and requires two parameters:
-
phase: sets at which phase at which
@ASTTest
will be triggered. The test code will work on the AST tree at the end of this phase. -
value: the code which will be executed once the phase is reached, on the annotated node
Compile phase has to be chosen from one of org.codehaus.groovy.control.CompilePhase . However, since it is not possible to annotate a node twice with the same annotation, you will
not be able to use @ASTTest on the same node at two distinct compile phases.
|
value
is a closure expression which has access to a special variable node
corresponding to the annotated node, and a helper lookup
method which will be discussed here.
For example, you can annotate a class node like this:
import groovy.transform.ASTTest
import org.codehaus.groovy.ast.ClassNode
import static org.codehaus.groovy.control.CompilePhase.*
@ASTTest(phase=CONVERSION, value={ (1)
assert node instanceof ClassNode (2)
assert node.name == 'Person' (3)
})
class Person {
}
1 | we’re checking the state of the Abstract Syntax Tree after the CONVERSION phase |
2 | node refers to the AST node which is annotated by @ASTTest |
3 | it can be used to perform assertions at compile time |
One interesting feature of @ASTTest
is that if an assertion fails, then compilation will fail. Now imagine that we want to check the behavior of an AST transformation at compile time.
We will take @PackageScope
here, and we will want to verify that a property annotated with @PackageScope
becomes a package private field. For this, we have to know at which phase the
transform runs, which can be found in org.codehaus.groovy.transform.PackageScopeASTTransformation
: semantic analysis. Then a test can be written like this:
import groovy.transform.ASTTest
import groovy.transform.PackageScope
import static org.codehaus.groovy.control.CompilePhase.*
@ASTTest(phase=SEMANTIC_ANALYSIS, value= {
def nameNode = node.properties.find { it.name == 'name' }
def ageNode = node.properties.find { it.name == 'age' }
assert nameNode
assert ageNode == null // shouldn't be a property anymore
def ageField = node.getDeclaredField 'age'
assert ageField.modifiers == 0
})
class Person {
String name
@PackageScope int age
}
The @ASTTest
annotation can only be placed wherever the grammar allows it. Sometimes, you would like to test the contents of an AST node which is not annotable. In this case,
@ASTTest
provides a convenient lookup
method which will search the AST for nodes which are labelled with a special token:
def list = lookup('anchor') (1)
Statement stmt = list[0] (2)
1 | returns the list of AST nodes which label is anchor |
2 | it is always necessary to choose which element to process since lookup always returns a list |
Imagine, for example, that you want to test the declared type of a for loop variable. Then you can do it like this:
import groovy.transform.ASTTest
import groovy.transform.PackageScope
import org.codehaus.groovy.ast.ClassHelper
import org.codehaus.groovy.ast.expr.DeclarationExpression
import org.codehaus.groovy.ast.stmt.ForStatement
import static org.codehaus.groovy.control.CompilePhase.*
class Something {
@ASTTest(phase=SEMANTIC_ANALYSIS, value= {
def forLoop = lookup('anchor')[0]
assert forLoop instanceof ForStatement
def decl = forLoop.collectionExpression.expressions[0]
assert decl instanceof DeclarationExpression
assert decl.variableExpression.name == 'i'
assert decl.variableExpression.originType == ClassHelper.int_TYPE
})
void someMethod() {
int x = 1;
int y = 10;
anchor: for (int i=0; i<x+y; i++) {
println "$i"
}
}
}
Grape handling
Grape
is a dependency management engine embedded into Groovy, relying on several annotations which are described
thoroughly in this section of the guide.
4.6. Dependency management with Grape
4.6.1. Quick start
Add a Dependency
Grape is a JAR dependency manager embedded into Groovy. Grape lets you quickly add maven repository dependencies to your classpath, making scripting even easier. The simplest use is as simple as adding an annotation to your script:
@Grab(group='org.springframework', module='spring-orm', version='3.2.5.RELEASE')
import org.springframework.jdbc.core.JdbcTemplate
@Grab
also supports a shorthand notation:
@Grab('org.springframework:spring-orm:3.2.5.RELEASE')
import org.springframework.jdbc.core.JdbcTemplate
Note that we are using an annotated import here, which is the recommanded way. You can also search for
dependencies on mvnrepository.com and it will
provide you the @Grab
annotation form of the pom.xml
entry.
Specify Additional Repositories
Not all dependencies are in maven central. You can add new ones like this:
@GrabResolver(name='restlet', root='http://maven.restlet.org/')
@Grab(group='org.restlet', module='org.restlet', version='1.1.6')
Maven Classifiers
Some maven dependencies need classifiers in order to be able to resolve. You can fix that like this:
@Grab(group='net.sf.json-lib', module='json-lib', version='2.2.3', classifier='jdk15')
Excluding Transitive Dependencies
Sometimes you will want to exclude transitive dependencies as you might be already using a slightly different but compatible version of some artifact. You can do this as follows:
@Grab('net.sourceforge.htmlunit:htmlunit:2.8')
@GrabExclude('xml-apis:xml-apis')
JDBC Drivers
Because of the way JDBC drivers are loaded, you’ll need to configure Grape to attach JDBC driver dependencies to the system class loader. I.e:
@GrabConfig(systemClassLoader=true)
@Grab(group='mysql', module='mysql-connector-java', version='5.1.6')
Using Grape From the Groovy Shell
From groovysh use the method call variant:
groovy.grape.Grape.grab(group:'org.springframework', module:'spring', version:'2.5.6')
Proxy settings
If you are behind a firewall and/or need to use Groovy/Grape through a proxy server, you can specify those settings on the command like via the http.proxyHost and http.proxyPort system properties:
groovy -Dhttp.proxyHost=yourproxy -Dhttp.proxyPort=8080 yourscript.groovy
Or you can make this system wide by adding these properties to your JAVA_OPTS environment variable:
JAVA_OPTS = -Dhttp.proxyHost=yourproxy -Dhttp.proxyPort=8080
Logging
If you want to see what Grape is doing set the system property “groovy.grape.report.downloads” to “true” (e.g. add “-Dgroovy.grape.report.downloads=true” to JAVA_OPTS) and Grape will print the following infos to System.error:
-
Starting resolve of a dependency
-
Starting download of an artifact
-
Retrying download of an artifact
-
Download size and time for downloaded artifacts
4.6.2. Detail
Grape (The Groovy Adaptable Packaging Engine or Groovy Advanced Packaging Engine) is the infrastructure enabling the grab() calls in Groovy, a set of classes leveraging Ivy to allow for a repository driven module system for Groovy. This allows a developer to write a script with an essentially arbitrary library requirement, and ship just the script. Grape will, at runtime, download as needed and link the named libraries and all dependencies forming a transitive closure when the script is run from existing repositories such as JCenter, Ibiblio, Codehaus, and java.net.
Grape follows the Ivy conventions for module version identification, with naming change.
-
group
- Which module group the module comes from. Translates directly to a Maven groupId or an Ivy Organization. Any group matching/groovy[x][\..*]^/
is reserved and may have special meaning to the groovy endorsed modules. -
module
- The name of the module to load. Translated directly to a Maven artifactId or an Ivy artifact. -
version
- The version of the module to use. Either a literal version ‘1.1-RC3’ or an Ivy Range ‘[2.2.1,)’ meaning 2.2.1 or any greater version). -
classifier
- The optional classifier to use (for example, jdk15)
The downloaded modules will be stored according to Ivy’s standard
mechanism with a cache root of ~/.groovy/grape
4.6.3. Usage
Annotation
One or more groovy.lang.Grab
annotations can be added at any place that
annotations are accepted to tell the compiler that this code relies on
the specific library. This will have the effect of adding the library to
the classloader of the groovy compiler. This annotation is detected and
evaluated before any other resolution of classes in the script, so
imported classes can be properly resolved by a @Grab
annotation.
import com.jidesoft.swing.JideSplitButton
@Grab(group='com.jidesoft', module='jide-oss', version='[2.2.1,2.3.0)')
public class TestClassAnnotation {
public static String testMethod () {
return JideSplitButton.class.name
}
}
An appropriate grab(...)
call will be added to the static initializer
of the class of the containing class (or script class in the case of an
annotated script element).
Multiple Grape Annotations
In order to use a Grape annotation multiple times on the same node you must use the
@Grapes
annotation, e.g.:
@Grapes([
@Grab(group='commons-primitives', module='commons-primitives', version='1.0'),
@Grab(group='org.ccil.cowan.tagsoup', module='tagsoup', version='0.9.7')])
class Example {
// ...
}
Otherwise you’ll encounter the following error:
Cannot specify duplicate annotation on the same member
Method call
Typically a call to grab will occur early in the script or in class initialization. This is to insure that the libraries are made available to the ClassLoader before the groovy code relies on the code. A couple of typical calls may appear as follows:
import groovy.grape.Grape
// random maven library
Grape.grab(group:'com.jidesoft', module:'jide-oss', version:'[2.2.0,)')
Grape.grab([group:'org.apache.ivy', module:'ivy', version:'2.0.0-beta1', conf:['default', 'optional']],
[group:'org.apache.ant', module:'ant', version:'1.7.0'])
// endorsed Groovy Module
// FUTURE grab('Scriptom')
-
Multiple calls to grab in the same context with the same parameters should be idempotent. However, if the same code is called with a different
ClassLoader
context then resolution may be re-run. -
If the
args
map passed into thegrab
call has an attributenoExceptions
that evaluates true no exceptions will be thrown. -
grab
requires that aRootLoader
orGroovyClassLoader
be specified or be in theClassLoader
chain of the calling class. By default failure to have such aClassLoader
available will result in module resolution and an exception being thrown-
The ClassLoader passed in via the
classLoader:
argument and it’s parent classloaders. -
The ClassLoader of the object passed in as the
referenceObject:
argument, and it’s parent classloaders. -
The ClassLoader of the class issuing the call to
grab
-
grab(HashMap) Parameters
-
group:
- <String> - Which module group the module comes from. Translates directly to a Maven groupId. Any group matching/groovy(|\..|x|x\..)/
is reserved and may have special meaning to the groovy endorsed modules. -
module:
- <String> - The name of the module to load. Translated directly to a Maven artifactId. -
version:
- <String> and possibly <Range> - The version of the module to use. Either a literal version ‘1.1-RC3’ or an Ivy Range ‘[2.2.1,)’ meaning 2.2.1 or any greater version). -
classifier:
- <String> - The Maven classifier to resolve by. -
conf:
- <String>, defaultdefault' - The configuration or scope of the module to download. The default conf is `default:
which maps to the mavenruntime
andmaster
scopes. -
force:
- <boolean>, defaults true - Used to indicate that this revision must be used in case of conflicts, independently of -
conflicts manager
-
changing:
- <boolean>, default false - Whether the artifact can change without it’s version designation changing. -
transitive:
- <boolean>, default true - Whether to resolve other dependencies this module has or not.
There are two principal variants of grab
, one with a single Map and
one with an arguments Map and multiple dependencies map. A call to the
single map grab is the same as calling grab with the same map passed in
twice, so grab arguments and dependencies can be mixed in the same map,
and grab can be called as a single method with named parameters.
There are synonyms for these parameters. Submitting more than one is a runtime exception.
-
group:
,groupId:
,organisation:
,organization:
,org:
-
module:
,artifactId:
,artifact:
-
version:
,revision:
,rev:
-
conf:
,scope:
,configuration:
Arguments Map arguments
-
classLoader:
- <GroovyClassLaoder> or <RootClassLoader> - The ClassLoader to add resolved Jars to -
refObject:
- <Object> - The closest parent ClassLoader for the object’s class will be treated as though it were passed in asclassLoader:
-
validate:
- <boolean>, default false - Should poms or ivy files be validated (true), or should we trust the cache (false). -
noExceptions:
- <boolean>, default false - If ClassLoader resolution or repository querying fails, should we throw an exception (false) or fail silently (true).
Command Line Tool
Grape added a command line executable ‘grape’ that allows for the inspection and management of the local grape cache.
grape install <groupId> <artifactId> [<version>]
This installs the specified groovy module or maven artifact. If a version is specified that specific version will be installed, otherwise the most recent version will be used (as if ‘*’ we passed in).
grape list
Lists locally installed modules (with their full maven name in the case of groovy modules) and versions.
grape resolve (<groupId> <artifactId> <version>)+
This returns the file locations of the jars representing the artifcats for the specified module(s) and the respective transitive dependencies. You may optionally pass in -ant, -dos, or -shell to get the dependencies expressed in a format applicable for an ant script, windows batch file, or unix shell script respectively. -ivy may be passed to see the dependencies expressed in an ivy like format.
Advanced configuration
Repository Directory
If you need to change the directory grape uses for downloading libraries you can specify the grape.root system property to change the default (which is ~/.groovy/grape)
groovy -Dgrape.root=/repo/grape yourscript.groovy
Customize Ivy settings
You can customize the ivy settings that Grape uses by creating a ~/.groovy/grapeConfig.xml file. If no such file exists, here are the default settings used by Grape:
<ivysettings>
<settings defaultResolver="downloadGrapes"/>
<resolvers>
<chain name="downloadGrapes">
<filesystem name="cachedGrapes">
<ivy pattern="${user.home}/.groovy/grapes/[organisation]/[module]/ivy-[revision].xml"/>
<artifact pattern="${user.home}/.groovy/grapes/[organisation]/[module]/[type]s/[artifact]-[revision].[ext]"/>
</filesystem>
<!-- todo add 'endorsed groovy extensions' resolver here -->
<ibiblio name="codehaus" root="http://repository.codehaus.org/" m2compatible="true"/>
<ibiblio name="ibiblio" m2compatible="true"/>
<ibiblio name="java.net2" root="http://download.java.net/maven/2/" m2compatible="true"/>
</chain>
</resolvers>
</ivysettings>
For more information on how to customize these settings, please refer to the Ivy documentation.
Add your local Maven2 repository
If you find yourself wanting to reuse artifacts that you already have locally in your Maven2 repository, then you can add this line to your ~/.groovy/grapeConfig.xml:
<ibiblio name="local" root="file:${user.home}/.m2/repository/" m2compatible="true"/>
And further customize your Grape configuration:
<?xml version="1.0"?>
<ivysettings>
<settings defaultResolver="downloadGrapes"/>
<resolvers>
<chain name="downloadGrapes">
<!-- todo add 'endorsed groovy extensions' resolver here -->
<ibiblio name="local" root="file:${user.home}/.m2/repository/" m2compatible="true"/>
<filesystem name="cachedGrapes">
<ivy pattern="${user.home}/.groovy/grapes/[organisation]/[module]/ivy-[revision].xml"/>
<artifact pattern="${user.home}/.groovy/grapes/[organisation]/[module]/[type]s/[artifact]-[revision].[ext]"/>
</filesystem>
<ibiblio name="codehaus" root="http://repository.codehaus.org/" m2compatible="true"/>
<ibiblio name="ibiblio" m2compatible="true"/>
<ibiblio name="java.net2" root="http://download.java.net/maven/2/" m2compatible="true"/>
</chain>
</resolvers>
</ivysettings>
More Examples
Using Apache Commons Collections:
// create and use a primitive array
import org.apache.commons.collections.primitives.ArrayIntList
@Grab(group='commons-primitives', module='commons-primitives', version='1.0')
def createEmptyInts() { new ArrayIntList() }
def ints = createEmptyInts()
ints.add(0, 42)
assert ints.size() == 1
assert ints.get(0) == 42
Using TagSoup:
// find the PDF links in the Java 1.5.0 documentation
@Grab(group='org.ccil.cowan.tagsoup', module='tagsoup', version='0.9.7')
def getHtml() {
def parser = new XmlParser(new org.ccil.cowan.tagsoup.Parser())
parser.parse("http://java.sun.com/j2se/1.5.0/download-pdf.html")
}
html.body.'**'.a.@href.grep(~/.*\.pdf/).each{ println it }
Using Google Collections:
// Google Collections example
import com.google.common.collect.HashBiMap
@Grab(group='com.google.code.google-collections', module='google-collect', version='snapshot-20080530')
def getFruit() { [grape:'purple', lemon:'yellow', orange:'orange'] as HashBiMap }
assert fruit.lemon == 'yellow'
assert fruit.inverse().yellow == 'lemon'
Launching a Jetty server to serve Groovy templates:
@Grapes([
@Grab(group='org.eclipse.jetty.aggregate', module='jetty-server', version='8.1.7.v20120910'),
@Grab(group='org.eclipse.jetty.aggregate', module='jetty-servlet', version='8.1.7.v20120910'),
@Grab(group='javax.servlet', module='javax.servlet-api', version='3.0.1')])
import org.eclipse.jetty.server.Server
import org.eclipse.jetty.servlet.*
import groovy.servlet.*
def runServer(duration) {
def server = new Server(8080)
def context = new ServletContextHandler(server, "/", ServletContextHandler.SESSIONS);
context.resourceBase = "."
context.addServlet(TemplateServlet, "*.gsp")
server.start()
sleep duration
server.stop()
}
runServer(10000)
Grape will download Jetty and its dependencies on first launch of this script, and cache them. We’re creating a new Jetty Server on port 8080, then expose Groovy’s TemplateServlet at the root of the context — Groovy comes with its own powerful template engine mechanism. We start the server and let it run for a certain duration. Each time someone will hit http://localhost:8080/somepage.gsp, it will display the somepage.gsp template to the user — those template pages should be situated in the same directory as this server script.
4.7. Testing Guide
4.7.1. Introduction
The Groovy programming language comes with great support for writing tests. In addition to the language features and test integration with state-of-the-art testing libraries and frameworks, the Groovy ecosystem has born a rich set of testing libraries and frameworks.
This chapter will start with language specific testing features and continue with a closer look at JUnit integration, Spock for specifications and Geb for functional tests. Finally, we an overview of other testing libraries known to be working with Groovy.
4.7.2. Language Features
Besides integrated support for JUnit, the Groovy programming language comes with features that have proven to be very valuable for test-driven development. This section gives insight on them.
Power Assertions
Writing tests means formulating assumptions by using assertions. In Java this can be done by using the assert
keyword that has been added in J2SE 1.4. In Java, assert
statements can be enabled via the JVM parameters -ea
(or -enableassertions
) and -da
(or -disableassertions
). Assertion statements in Java are disabled by default.
Groovy comes with a rather powerful variant of assert
also known as power assertion statement. Groovy’s power
assert
differs from the Java version in its output given the boolean expression validates to false
:
def x = 1
assert x == 2
// Output: (1)
//
// Assertion failed:
// assert x == 2
// | |
// 1 false
1 | This section shows the std-err output |
The java.lang.AssertionError
that is thrown whenever the assertion can not be validated successfully, contains
an extended version of the original exception message. The power assertion output shows evaluation results from
the outer to the inner expression.
The power assertion statements true power unleashes in complex Boolean statements, or statements with
collections or other toString
-enabled classes:
def x = [1,2,3,4,5]
assert (x << 6) == [6,7,8,9,10]
// Output:
//
// Assertion failed:
// assert (x << 6) == [6,7,8,9,10]
// | | |
// | | false
// | [1, 2, 3, 4, 5, 6]
// [1, 2, 3, 4, 5, 6]
Another important difference from Java is that in Groovy assertions are enabled by default. It has been a language design decision to remove the possibility to deactivate assertions. Or, as Bertrand Meyer stated, ``it makes no sense to take off your swim ring if you put your feet into real water``.
One thing to be aware of are methods with side-effects inside Boolean expressions in power assertion statements. As the internal error message construction mechanism does only store references to instances under target, it happens that the error message text is invalid at rendering time in case of side-effecting methods involved:
assert [[1,2,3,3,3,3,4]].first().unique() == [1,2,3]
// Output:
//
// Assertion failed:
// assert [[1,2,3,3,3,3,4]].first().unique() == [1,2,3]
// | | |
// | | false
// | [1, 2, 3, 4]
// [1, 2, 3, 4] (1)
1 | The error message shows the actual state of the collection, not the state before the unique method was applied |
If you choose to provide a custom assertion error message this can be done by using the Java syntax assert
expression1 : expression2 where expression1 is the Boolean expression and expression2 is the custom error message.
Be aware though that this will disable the power assert and will fully fallback to custom
error messages on assertion errors.
|
Mocking and Stubbing
Groovy has excellent built-in support for a range of mocking and stubbing alternatives. When using Java, dynamic mocking frameworks are very popular. A key reason for this is that it is hard work creating custom hand-crafted mocks using Java. Such frameworks can be used easily with Groovy if you choose but creating custom mocks is much easier in Groovy. You can often get away with simple maps or closures to build your custom mocks.
The following sections show ways to create mocks and stubs with Groovy language features only.
Map Coercion
By using maps or expandos, we can incorporate desired behaviour of a collaborator very easily as shown here:
class TranslationService {
String convert(String key) {
return "test"
}
}
def service = [convert: { String key -> 'some text' }] as TranslationService
assert 'some text' == service.convert('key.text')
The as
operator can be used to coerce a map to a particular class. The given map keys are interpreted as
method names and the values, being groovy.lang.Closure
blocks, are interpreted as method code blocks.
Be aware that map coercion can get into the way if you deal with custom java.util.Map descendant classes in combination
with the as operator. The map coercion mechanism is targeted directly at certain collection classes, it doesn’t take
custom classes into account.
|
Closure Coercion
The as operator can be used with closures in a neat way which is great for developer testing in simple scenarios. We haven’t found this technique to be so powerful that we want to do away with dynamic mocking, but it can be very useful in simple cases none-the-less.
Classes or interfaces holding a single method, including SAM (single abstract method) classes, can be used to coerce a closure block to be an object of the given type. Be aware that for doing this, Groovy internally create a proxy object descending for the given class. So the object will not be a direct instance of the given class. This important if, for example, the generated proxy object’s meta-class is altered afterwards.
Let’s have an example on coercing a closure to be of a specific type:
def service = { String key -> 'some text' } as TranslationService
assert 'some text' == service.convert('key.text')
Groovy supports a feature called implicit SAM coercion. This means that the as
operator is not necessary in situations
where the runtime can infer the target SAM type. This type of coercion might be useful in tests to mock entire SAM
classes:
abstract class BaseService {
abstract void doSomething()
}
BaseService service = { -> println 'doing something' }
service.doSomething()
MockFor and StubFor
The Groovy mocking and stubbing classes can be found in the groovy.mock.interceptor
package.
The MockFor
class supports (typically unit) testing of classes in isolation by allowing a strictly ordered expectation
of the behavior of collaborators to be defined. A typical test scenario involves a class under test and one or more collaborators. In such a scenario it is
often desirable to just test the business logic of the class under test. One strategy for doing that is to replace
the collaborator instances with simplified mock objects to help isolate out the logic in the test target. MockFor
allows such mocks to be created using meta-programming. The desired behavior of collaborators is defined as a behavior
specification. The behavior is enforced and checked automatically.
Let’s assume our target classes looked like this:
class Person {
String first, last
}
class Family {
Person father, mother
def nameOfMother() { "$mother.first $mother.last" }
}
With MockFor
, a mock expectation is always sequence dependent and its use automatically ends with a call to verify
:
def mock = new MockFor(Person) (1)
mock.demand.getFirst{ 'dummy' }
mock.demand.getLast{ 'name' }
mock.use { (2)
def mary = new Person(first:'Mary', last:'Smith')
def f = new Family(mother:mary)
assert f.nameOfMother() == 'dummy name'
}
mock.expect.verify() (3)
1 | a new mock is created by a new instance of MockFor |
2 | a Closure is passed to use which enables the mocking functionality |
3 | a call to verify checks whether the sequence and number of method calls is as expected |
The StubFor
class supports (typically unit) testing of classes in isolation by allowing a loosely-ordered expectation
of the behavior of collaborators to be defined. A typical test scenario involves a class under test and one or more
collaborators. In such a scenario it is often desirable to just test the business logic of the CUT. One strategy for
doing that is to replace the collaborator instances with simplified stub objects to help isolate out the logic
in the target class. StubFor
allows such stubs to be created using meta-programming. The desired behavior of
collaborators is defined as a behavior specification.
In contrast to MockFor
the stub expectation checked with verify
is sequence independent and its use is optional:
def stub = new StubFor(Person) (1)
stub.demand.with { (2)
getLast{ 'name' }
getFirst{ 'dummy' }
}
stub.use { (3)
def john = new Person(first:'John', last:'Smith')
def f = new Family(father:john)
assert f.father.first == 'dummy'
assert f.father.last == 'name'
}
stub.expect.verify() (4)
1 | a new stub is created by a new instance of StubFor |
2 | the with method is used for delegating all calls inside the closure to the StubFor instance |
3 | a Closure is passed to use which enables the stubbing functionality |
4 | a call to verify (optional) checks whether the number of method calls is as expected |
MockFor
and StubFor
can not be used to test statically compiled classes e.g for Java classes or Groovy classes that
make use of @CompileStatic
. To stub and/or mock these classes you can use Spock or one of the Java mocking libraries.
Expando Meta-Class (EMC)
Groovy includes a special MetaClass
the so-called ExpandoMetaClass
(EMC). It allows to dynamically add methods,
constructors, properties and static methods using a neat closure syntax.
Every java.lang.Class
is supplied with a special metaClass
property that will give a reference to an
ExpandoMetaClass
instance. The expando meta-class is not restricted to custom classes, it can be used for
JDK classes like for example java.lang.String
as well:
String.metaClass.swapCase = {->
def sb = new StringBuffer()
delegate.each {
sb << (Character.isUpperCase(it as char) ? Character.toLowerCase(it as char) :
Character.toUpperCase(it as char))
}
sb.toString()
}
def s = "heLLo, worLD!"
assert s.swapCase() == 'HEllO, WORld!'
The ExpandoMetaClass
is a rather good candidate for mocking functionality as it allows for more advanced stuff
like mocking static methods
class Book {
String title
}
Book.metaClass.static.create << { String title -> new Book(title:title) }
def b = Book.create("The Stand")
assert b.title == 'The Stand'
or even constructors
Book.metaClass.constructor << { String title -> new Book(title:title) }
def b = new Book("The Stand")
assert b.title == 'The Stand'
Mocking constructors might seem like a hack that’s better not even to be considered but even there might be valid
use cases. An example can be found in Grails where domain class constructors are added at run-time with the
help of ExpandoMetaClass . This lets the domain object register itself in the Spring application context and allows
for injection of services or other beans controlled by the dependency-injection container.
|
If you want to change the metaClass
property on a per test method level you need to remove the changes that were
done to the meta-class, otherwise those changes would be persistent across test method calls. Changes are removed by
replacing the meta-class in the GroovyMetaClassRegistry
:
GroovySystem.metaClassRegistry.setMetaClass(java.lang.String, null)
Another alternative is to register a MetaClassRegistryChangeEventListener
, track the changed classes and remove
the changes in the cleanup method of your chosen testing runtime. A good example can be found
in the Grails web
development framework.
Besides using the ExpandoMetaClass
on a class-level, there is also support for using the meta-class on a per-object
level:
def b = new Book(title: "The Stand")
b.metaClass.getTitle {-> 'My Title' }
assert b.title == 'My Title'
In this case the meta-class change is related to the instance only. Depending on the test scenario this might be a better fit than the global meta-class change.
GDK Methods
The following section gives a brief overview on GDK methods that can be leveraged in test case scenarios, for example for test data generation.
Iterable#combinations
The combinations
method that is added on java.lang.Iterable
compliant classes can be used to get a list of
combinations from a list containing two or more sub-lists:
void testCombinations() {
def combinations = [[2, 3],[4, 5, 6]].combinations()
assert combinations == [[2, 4], [3, 4], [2, 5], [3, 5], [2, 6], [3, 6]]
}
The method could be used in test case scenarios to generate all possible argument combinations for a specific method call.
Iterable#eachCombination
The eachCombination
method that is added on java.lang.Iterable
can be used to apply a function (or in this
case a groovy.lang.Closure
) to each if the combinations that has been built by the combinations
method:
eachCombination
is a GDK method that is added to all classes conforming to the java.lang.Iterable
interface.
It applies a function on each combination of the input lists:
void testEachCombination() {
[[2, 3],[4, 5, 6]].eachCombination { println it[0] + it[1] }
}
The method could be used in the testing context to call methods with each of the generated combinations.
Tool Support
Test Code Coverage
Code coverage is a useful measure of the effectiveness of (unit) tests. A program with high code coverage has a lower chance to hold critical bugs than a program with no or low coverage. To get code coverage metrics, the generated byte-code usually needs to be instrumented before the tests are executed. One tool with Groovy support for this task is Cobertura.
Various frameworks and build tools come with Cobertura integration. For Grails, there is the code coverage plugin based on Cobertura, for Gradle there is the gradle-cobertura plugin, to name only two of them.
The following code listing shows an example on how to enable Cobertura test coverage reports in a Gradle build script from a Groovy project:
def pluginVersion = '<plugin version>'
def groovyVersion = '<groovy version>'
def junitVersion = '<junit version>'
buildscript {
repositories {
mavenCentral()
}
dependencies {
classpath 'com.eriwen:gradle-cobertura-plugin:${pluginVersion}'
}
}
apply plugin: 'groovy'
apply plugin: 'cobertura'
repositories {
mavenCentral()
}
dependencies {
compile "org.codehaus.groovy:groovy-all:${groovyVersion}"
testCompile "junit:junit:${junitVersion}"
}
cobertura {
format = 'html'
includes = ['**/*.java', '**/*.groovy']
excludes = ['com/thirdparty/**/*.*']
}
Several output formats can be chosen for Cobertura coverage reports and test code coverage reports can be added to continuous integration build tasks.
4.7.3. Unit Tests with JUnit 3 and 4
Groovy simplifies JUnit testing, making it more Groovy. In the following sections we will have a closer look at JUnit 3/4 Groovy integration.
JUnit 3
Maybe one of the most prominent Groovy classes supporting JUnit 3 tests is the GroovyTestCase
class. Being
derived from junit.framework.TestCase
it offers a bunch of additional methods that make testing in Groovy a breeze.
Although GroovyTestCase inherits from TestCase doesn’t mean you can’t use JUnit 4 features in your project. In fact,
the most recent Groovy versions come with a bundled JUnit 4 and that comes with a backwards compatible TestCase
implementation. There have been some discussion on the Groovy mailing-list on whether to use GroovyTestCase or JUnit 4
with the result that it is mostly a matter of taste, but with GroovyTestCase you get a bunch of methods for free that
make certain types of tests easier to write.
|
In this section, we will have a look at some of the methods provided by GroovyTestCase
. A full list of these can be
found in the JavaDoc documentation for groovy.util.GroovyTestCase,
don’t forget it is inherited from junit.framework.TestCase
which inherits all the assert*
methods.
Assertion Methods
GroovyTestCase
is inherited from junit.framework.TestCase
therefore it inherits a large number of assertion methods
being available to be called in every test method:
class MyTestCase extends GroovyTestCase {
void testAssertions() {
assertTrue(1 == 1)
assertEquals("test", "test")
def x = "42"
assertNotNull "x must not be null", x
assertNull null
assertSame x, x
}
}
As can be seen above, in contrast to Java it is possible to leave out the parenthesis in most situations which leads to even more readability of JUnit assertion method call expressions.
An interesting assertion method that is added by GroovyTestCase
is assertScript
. It ensures that the given Groovy
code string succeeds without any exception:
void testScriptAssertions() {
assertScript '''
def x = 1
def y = 2
assert x + y == 3
'''
}
shouldFail Methods
shouldFail
can be used to check whether the given code block fails or not. In case it fails, the assertion does hold,
otherwise the assertion fails:
void testInvalidIndexAccess1() {
def numbers = [1,2,3,4]
shouldFail {
numbers.get(4)
}
}
The example above uses the basic shouldFail
method interface that takes a groovy.lang.Closure
as a single argument.
The Closure
instance holds the code that is supposed to be breaking during run-time.
If we wanted to assert shouldFail
on a specific java.lang.Exception
type we could have done so by using the shouldFail
implementation that takes the Exception
class as first argument and the Closure
as second argument:
void testInvalidIndexAccess2() {
def numbers = [1,2,3,4]
shouldFail IndexOutOfBoundsException, {
numbers.get(4)
}
}
If anything other than IndexOutOfBoundsException
(or a descendant class of it) is thrown, the test case will fail.
A pretty nice feature of shouldFail
hasn’t been visible so far: it returns the exception message. This is really
useful if you want to assert on the exception error message:
void testInvalidIndexAccess3() {
def numbers = [1,2,3,4]
def msg = shouldFail IndexOutOfBoundsException, {
numbers.get(4)
}
assert msg.contains('Index: 4, Size: 4')
}
notYetImplemented Method
The notYetImplemented
method has been greatly influenced by HtmlUnit. It allows to write a test method but mark it
as not yet implemented. As long as the test method fails and is marked with notYetImplemented
the test goes green:
void testNotYetImplemented1() {
if (notYetImplemented()) return (1)
assert 1 == 2 (2)
}
1 | a call to notYetImplemented is necessary for GroovyTestCase to get the current method stack. |
2 | as long as the test evaluates to false the test execution will be successful. |
An alternative to the notYetImplemented
method is the @NotYetImplemented
annotation. It allows for annotating a
method as not yet implemented, with the exact same behavior as GroovyTestCase#notYetImplemented
but without the need
for the notYetImplemented
method call:
@NotYetImplemented
void testNotYetImplemented2() {
assert 1 == 2
}
JUnit 4
Groovy can be used to write JUnit 4 test cases without any restrictions. The groovy.test.GroovyAssert
holds
various static methods that can be used as replacement for the GroovyTestCase
methods in JUnit 4 tests:
import org.junit.Test
import static groovy.test.GroovyAssert.shouldFail
class JUnit4ExampleTests {
@Test
void indexOutOfBoundsAccess() {
def numbers = [1,2,3,4]
shouldFail {
numbers.get(4)
}
}
}
As can be seen in the example above, the static methods found in GroovyAssert
are imported at the beginning of the
class definition thus shouldFail
can be used the same way it can be used in a GroovyTestCase
.
groovy.test.GroovyAssert descends from org.junit.Assert that means it inherits all JUnit assertion methods. However,
with the introduction of the power assertion statement, it turned out to be good practice to rely on assertion statements
instead of using the JUnit assertion methods with the improved message being the main reason.
|
4.7.4. Testing with Spock
Spock is a testing and specification framework for Java and Groovy applications. What makes it stand out from the crowd is its beautiful and highly expressive specification DSL. In practice, Spock specifications are written as Groovy classes. Although written in Groovy they can be used to test Java classes. Spock can be used for unit, integration or BDD (behavior-driven-development) testing, it doesn’t put itself into a specific category of testing frameworks or libraries.
Beside these awesome features Spock is a good example on how to leverage advanced Groovy programming language features in third party libraries, for example, by using Groovy AST transformations. |
This section should not serve as detailed guide on how to use Spock, it should rather give an impression what Spock is about and how it can be leveraged for unit, integration, functional or any other type of testing. |
The next section we will have an first look at the anatomy of a Spock specification. It should give a pretty good feeling on what Spock is up to.
Specifications
Spock lets you write specifications that describe features (properties, aspects) exhibited by a system of interest. The "system" can be anything between a single class and an entire application, a more advanced term for it is system under specification. The feature description starts from a specific snapshot of the system and its collaborators, this snapshot is called the feature’s fixture.
Spock specification classes are derived from spock.lang.Specification
. A concrete specification class might consist
of fields, fixture methods, features methods and helper methods.
Let’s have a look at a simple specification with a single feature method for an imaginary Stack
class:
class StackSpec extends Specification {
def "adding an element leads to size increase"() { (1)
setup: "a new stack instance is created" (2)
def stack = new Stack()
when: (3)
stack.push 42
then: (4)
stack.size() == 1
}
}
1 | Feature method, is by convention named with a String literal. |
2 | Setup block, here is where any setup work for this feature needs to be done. |
3 | When block describes a stimulus, a certain action under target by this feature specification. |
4 | Then block any expressions that can be used to validate the result of the code that was triggered by the when block. |
Spock feature specifications are defined as methods inside a spock.lang.Specification
class. They describe the feature
by using a String literal instead of a method name.
A feature method holds multiple blocks, in our example we used setup
, when
and then
. The setup
block is special
in that it is optional and allows to configure local variables visible inside the feature method. The when
block
defines the stimulus and is a companion of the then
block which describes the response to the stimulus.
Note that the setup
method in the StackSpec
above additionally
has a description String. Description Strings are optional and can be added after block labels (like setup
, when
,
then
).
More Spock
Spock provides much more features like data tables or advanced mocking capabilities. Feel free to consult the Spock GitHub page for more documentation and download information.
4.7.5. Functional Tests with Geb
Geb is a functional web testing and scraper library that integrates with JUnit and Spock. It is based upon the Selenium web drivers and, like Spock, provides a Groovy DSL to write functional tests for web applications.
Geb has great features that make it a good fit for a functional testing library:
-
DOM access via a JQuery-like
$
function -
implements the page pattern
-
support for modularization of certain web components (e.g. menu-bars, etc.) with modules
-
integration with JavaScript via the JS variable
This section should not serve as detailed guide on how to use Geb, it should rather give an impression what Geb is about and how it can be leveraged functional testing. |
The next section will give an example on how Geb can be used to write a functional test for a simple web page with a single search field.
A Geb Script
Although Geb can be used standalone in a Groovy script, in many scenarios it’s used in combination with other testing frameworks. Geb comes with various base classes that can be used in JUnit 3, 4, TestNG or Spock tests. The base classes are part of additional Geb modules that need to be added as a dependency.
For example, the following @Grab
dependencies have to be used to run Geb with the Selenium Firefox driver in
JUnit4 tests. The module that is needed for JUnit 3/4 support is geb-junit
:
@Grapes([
@Grab("org.gebish:geb-core:0.9.2"),
@Grab("org.gebish:geb-junit:0.9.2"),
@Grab("org.seleniumhq.selenium:selenium-firefox-driver:2.26.0"),
@Grab("org.seleniumhq.selenium:selenium-support:2.26.0")
])
The central class in Geb is the geb.Browser
class. As its name implies it is used
to browse pages and access DOM elements:
def browser = new Browser(driver: new FirefoxDriver(), baseUrl: 'http://myhost:8080/myapp') (1)
browser.drive {
go "/login" (2)
$("#username").text = 'John' (3)
$("#password").text = 'Doe'
$("#loginButton").click()
assert title == "My Application - Dashboard"
}
1 | A new Browser instance is created. In this case it uses the Selenium FirefoxDriver and sets the baseUrl . |
2 | go is used to navigate to an URL or relative URI |
3 | $ together with CSS selectors is used to access the username and password DOM fields. |
The Browser
class comes with a drive
method that delegates all method/property calls to the current
browser
instance. The Browser
configuration must not be done inline, it can also be externalized in a
GebConfig.groovy
configuration file for example. In practice, the usage of the Browser
class is mostly hidden
by Geb test base classes. They delegate all missing properties and method calls to the current browser
instance
that exists in the background:
class SearchTests extends geb.junit4.GebTest {
@Test
void executeSeach() {
go 'http://somehost/mayapp/search' (1)
$('#searchField').text = 'John Doe' (2)
$('#searchButton').click() (3)
assert $('.searchResult a').first().text() == 'Mr. John Doe' (4)
}
}
1 | Browser#go takes a relative or absolute link and calls the page. |
2 | Browser#$ is used to access DOM content. Any CSS selectors supported by the underlying Selenium drivers are allowed |
3 | click is used to click a button. |
4 | $ is used to get the first link out of the searchResult block |
The example above shows a simple Geb web test with the JUnit 4 base class geb.junit4.GebTest
. Note that in this case
the Browser
configuration is externalized. GebTest
delegates methods like go
and $
to the underlying browser
instance.
More Geb
In the previous section we only scratched the surface of the available Geb features. More information on Geb can be found at the project homepage.
4.8. Processing JSON
Groovy comes with integrated support for converting between Groovy objects and JSON. The classes dedicated to
JSON serialisation and parsing are found in the groovy.json
package.
4.8.1. JsonSlurper
JsonSlurper
is a class that parses JSON text or reader content into Groovy data structures (objects) such as maps, lists and
primitive types like Integer
, Double
, Boolean
and String
.
The class comes with a bunch of overloaded parse
methods plus some special methods such as parseText
,
parseFile
and others. For the next example we will use the parseText
method. It parses a JSON String
and recursively converts it to a
list or map of objects. The other parse*
methods are similar in that they return a JSON String
but for different parameter
types.
def jsonSlurper = new JsonSlurper()
def object = jsonSlurper.parseText('{ "name": "John Doe" } /* some comment */')
assert object instanceof Map
assert object.name == 'John Doe'
Notice the result is a plain map and can be handled like a normal Groovy object instance. JsonSlurper
parses the
given JSON as defined by the ECMA-404 JSON Interchange Standard
plus support for JavaScript comments and dates.
In addition to maps JsonSlurper
supports JSON arrays which are being converted to lists.
def jsonSlurper = new JsonSlurper()
def object = jsonSlurper.parseText('{ "myList": [4, 8, 15, 16, 23, 42] }')
assert object instanceof Map
assert object.myList instanceof List
assert object.myList == [4, 8, 15, 16, 23, 42]
The JSON standard supports the following primitive data types: string, number, object, true
, false
and null
. JsonSlurper
converts these JSON types into corresponding Groovy types.
def jsonSlurper = new JsonSlurper()
def object = jsonSlurper.parseText '''
{ "simple": 123,
"fraction": 123.66,
"exponential": 123e12
}'''
assert object instanceof Map
assert object.simple.class == Integer
assert object.fraction.class == BigDecimal
assert object.exponential.class == BigDecimal
As JsonSlurper
is returning pure Groovy object instances without any special JSON classes in the back, its usage
is transparent. In fact, JsonSlurper
results conform to GPath expressions. GPath is a powerful expression language
that is supported by multiple slurpers for different data formats (XmlSlurper
for XML being one example).
For more details please have a look at the section on GPath expressions. |
The following table gives an overview of the JSON types and the corresponding Groovy data types:
JSON | Groovy |
---|---|
string |
|
number |
|
object |
|
array |
|
true |
|
false |
|
null |
|
date |
|
Whenever a value in JSON is null , JsonSlurper supplements it with the Groovy null value. This is in contrast to other
JSON parsers that represent a null value with a library-provided singleton object.
|
Parser Variants
JsonSlurper
comes with a couple of parser implementations. Each parser fits different requirements, it could well be that for certain
scenarios the JsonSlurper
default parser is not the best bet for all situations. Here is an overview of the shipped parser implementations:
-
The
JsonParserCharArray
parser basically takes a JSON string and operates on the underlying character array. During value conversion it copies character sub-arrays (a mechanism known as "chopping") and operates on them. -
The
JsonFastParser
is a special variant of theJsonParserCharArray
and is the fastest parser. However, it is not the default parser for a reason.JsonFastParser
is a so-called index-overlay parser. During parsing of the given JSONString
it tries as hard as possible to avoid creating new char arrays orString
instances. It keeps pointers to the underlying original character array only. In addition, it defers object creation as late as possible. If parsed maps are put into long-term caches care must be taken as the map objects might not be created and still consist of pointer to the original char buffer only. However,JsonFastParser
comes with a special chop mode which dices up the char buffer early to keep a small copy of the original buffer. Recommendation is to use theJsonFastParser
for JSON buffers under 2MB and keeping the long-term cache restriction in mind. -
The
JsonParserLax
is a special variant of theJsonParserCharArray
parser. It has similar performance characteristics asJsonFastParser
but differs in that it isn’t exclusively relying on the ECMA-404 JSON grammar. For example it allows for comments, no quote strings etc. -
The
JsonParserUsingCharacterSource
is a special parser for very large files. It uses a technique called "character windowing" to parse large JSON files (large means files over 2MB size in this case) with constant performance characteristics.
The default parser implementation for JsonSlurper
is JsonParserCharArray
. The JsonParserType
enumeration contains constants for
the parser implementations described above:
Implementation | Constant |
---|---|
|
|
|
|
|
|
|
|
Changing the parser implementation is as easy as setting the JsonParserType
with a call to JsonSlurper#setType()
.
def jsonSlurper = new JsonSlurper(type: JsonParserType.INDEX_OVERLAY)
def object = jsonSlurper.parseText('{ "myList": [4, 8, 15, 16, 23, 42] }')
assert object instanceof Map
assert object.myList instanceof List
assert object.myList == [4, 8, 15, 16, 23, 42]
4.8.2. JsonOutput
JsonOutput
is responsible for serialising Groovy objects into JSON strings. It can be seen as companion object to
JsonSlurper, being a JSON parser.
JsonOutput
comes with overloaded, static toJson
methods. Each toJson
implementation takes a different parameter type.
The static method can either be used directly or by importing the methods with a static import statement.
The result of a toJson
call is a String
containing the JSON code.
def json = JsonOutput.toJson([name: 'John Doe', age: 42])
assert json == '{"name":"John Doe","age":42}'
JsonOutput
does not only support primitive, maps or list data types to be serialized to JSON, it goes further and even
has support for serialising POGOs, that is, plain-old Groovy objects.
class Person { String name }
def json = JsonOutput.toJson([ new Person(name: 'John'), new Person(name: 'Max') ])
assert json == '[{"name":"John"},{"name":"Max"}]'
As we saw in previous examples, the JSON output is not pretty printed per default. However, the prettyPrint
method in JsonSlurper
comes
to rescue for this task.
def json = JsonOutput.toJson([name: 'John Doe', age: 42])
assert json == '{"name":"John Doe","age":42}'
assert JsonOutput.prettyPrint(json) == '''\
{
"name": "John Doe",
"age": 42
}'''.stripIndent()
prettyPrint
takes a String
as single parameter. It must not be used in conjunction with the other JsonOutput
methods,
it can be applied on arbitrary JSON String
instances.
Another way to create JSON from Groovy is to use the JsonBuilder
or StreamingJsonBuilder
. Both builders provide a
DSL which allows to formulate an object graph which is then converted to JSON at some point.
For more details on builders, have a look at the builders chapter which covers both JSON builders in great depth. |
4.9. Template engines
4.9.1. Introduction
Groovy supports multiple ways to generate text dynamically including GStrings
, printf
if you are using Java 5, and MarkupBuilder just to name a few. In addition to these, there is a dedicated template framework which is well-suited to applications where the text to be generated follows the form of a static template.
4.9.2. Template framework
The template framework in Groovy consists of a TemplateEngine
abstract base class that engines must implement and a Template
interface that the resulting templates they generate must implement.
Included with Groovy are several template engines:
-
SimpleTemplateEngine
- for basic templates -
GStringTemplateEngine
- stores the template as writable closures (useful for streaming scenarios) -
XmlTemplateEngine
- works well when the template and output are valid XML -
MarkupTemplateEngine
- a very complete, optimized, template engine
4.9.3. SimpleTemplateEngine
Shown here is the SimpleTemplateEngine
that allows you to use JSP-like scriptlets (see example below), script, and EL expressions in your template in order to generate parameterized text. Here is an example of using the system:
def text = 'Dear "$firstname $lastname",\nSo nice to meet you in <% print city %>.\nSee you in ${month},\n${signed}'
def binding = ["firstname":"Sam", "lastname":"Pullara", "city":"San Francisco", "month":"December", "signed":"Groovy-Dev"]
def engine = new groovy.text.SimpleTemplateEngine()
def template = engine.createTemplate(text).make(binding)
def result = 'Dear "Sam Pullara",\nSo nice to meet you in San Francisco.\nSee you in December,\nGroovy-Dev'
assert result == template.toString()
While it is generally not deemed good practice to mix processing logic in your template (or view), sometimes very simple logic can be useful. E.g. in the example above, we could change this:
$firstname
to this (assuming we have set up a static import for capitalize inside the template):
${firstname.capitalize()}
or this:
<% print city %>
to this:
<% print city == "New York" ? "The Big Apple" : city %>
Advanced Usage Note
If you happen to be embedding your template directly in your script (as we did above) you have to be careful about backslash escaping. Because the template string itself will be parsed by Groovy before it is passed to the the templating framework, you have to escape any backslashes inside GString expressions or scriptlet code that are entered as part of a Groovy program. E.g. if we wanted quotes around The Big Apple above, we would use:
<% print city == "New York" ? "\\"The Big Apple\\"" : city %>
Similarly, if we wanted a newline, we would use:
\\n
in any GString expression or scriptlet 'code' that appears inside a Groovy script. A normal "\n
" is fine within the static template text itself or if the entire template itself is in an external template file. Similarly, to represent an actual backslash in your text you would need
\\\\
in an external file or
\\\\
in any GString expression or scriptlet 'code'. (Note: the necessity to have this extra slash may go away in a future version of Groovy if we can find an easy way to support such a change.)
4.9.4. GStringTemplateEngine
As an example of using the GStringTemplateEngine
, here is the example above done again (with a few changes to show some other options). First we will store the template in a file this time:
Dear "$firstname $lastname",
So nice to meet you in <% out << (city == "New York" ? "\\"The Big Apple\\"" : city) %>.
See you in ${month},
${signed}
Note that we used out
instead of print
to support the streaming nature of GStringTemplateEngine
. Because we have the template in a separate file, there is no need to escape the backslashes. Here is how we call it:
def f = new File('test.template')
def engine = new groovy.text.GStringTemplateEngine()
def template = engine.createTemplate(f).make(binding)
println template.toString()
and here is the output:
Dear "Sam Pullara", So nice to meet you in "The Big Apple". See you in December, Groovy-Dev
4.9.5. XmlTemplateEngine
XmlTemplateEngine
for use in templating scenarios where both the template source and the expected output are intended to be XML. Templates may use the normal ${expression}
and $variable
notations to insert an arbitrary expression into the template. In addition, support is also provided for special tags: <gsp:scriptlet>
(for inserting code fragments) and <gsp:expression>
(for code fragments which produce output).
Comments and processing instructions will be removed as part of processing and special XML characters such as <
, >
, "
and '
will be escaped using the respective XML notation. The output will also be indented using standard XML pretty printing.
The xmlns namespace definition for gsp: tags will be removed but other namespace definitions will be preserved (but may change to an equivalent position within the XML tree).
Normally, the template source will be in a file but here is a simple example providing the XML template as a string:
def binding = [firstname: 'Jochen', lastname: 'Theodorou', nickname: 'blackdrag', salutation: 'Dear']
def engine = new groovy.text.XmlTemplateEngine()
def text = '''\
<document xmlns:gsp='http://groovy.codehaus.org/2005/gsp' xmlns:foo='baz' type='letter'>
<gsp:scriptlet>def greeting = "${salutation}est"</gsp:scriptlet>
<gsp:expression>greeting</gsp:expression>
<foo:to>$firstname "$nickname" $lastname</foo:to>
How are you today?
</document>
'''
def template = engine.createTemplate(text).make(binding)
println template.toString()
This example will produce this output:
<document type='letter'>
Dearest
<foo:to xmlns:foo='baz'>
Jochen "blackdrag" Theodorou
</foo:to>
How are you today?
</document>
4.9.6. The MarkupTemplateEngine
This template engine is a template engine primarily aimed at generating XML-like markup (XML, XHTML, HTML5, …), but that can be used to generate any text based content. Unlike traditional template engines, this one relies on a DSL that uses the builder syntax. Here is a sample template:
xmlDeclaration()
cars {
cars.each {
car(make: it.make, model: it.model)
}
}
If you feed it with the following model:
model = [cars: [new Car(make: 'Peugeot', model: '508'), new Car(make: 'Toyota', model: 'Prius')]]
It would be rendered as:
<?xml version='1.0'?>
<cars><car make='Peugeot' model='508'/><car make='Toyota' model='Prius'/></cars>
The key features of this template engine are:
-
a markup builder like syntax
-
templates are compiled into bytecode
-
fast rendering
-
optional type checking of the model
-
includes
-
internationalization support
-
fragments/layouts
The template format
Basics
Templates consist of Groovy code. Let’s explore the first example more thoroughly:
xmlDeclaration() (1)
cars { (2)
cars.each { (3)
car(make: it.make, model: it.model) (4)
} (5)
}
1 | renders the XML declaration string. |
2 | opens a cars tag |
3 | cars is a variable found in the template model, which is a list of Car instances |
4 | for each item, we create a car tag with the attributes from the Car instance |
5 | closes the cars tag |
As you can see, regular Groovy code can be used in the template. Here, we are calling each
on a list (retrieved from the model), allowing us to
render one car
tag per entry.
In a similar fashion, rendering HTML code is as simple as this:
yieldUnescaped '<!DOCTYPE html>' (1)
html(lang:'en') { (2)
head { (3)
meta('http-equiv':'"Content-Type" content="text/html; charset=utf-8"') (4)
title('My page') (5)
} (6)
body { (7)
p('This is an example of HTML contents') (8)
} (9)
} (10)
1 | renders the HTML doctype special tag |
2 | opens the html tag with an attribute |
3 | opens the head tag |
4 | renders a meta tag with one http-equiv attribute |
5 | renders the title tag |
6 | closes the head tag |
7 | opens the body tag |
8 | renders a p tag |
9 | closes the body tag |
10 | closes the html tag |
The output is straightforward:
<!DOCTYPE html><html lang='en'><head><meta http-equiv='"Content-Type" content="text/html; charset=utf-8"'/><title>My page</title></head><body><p>This is an example of HTML contents</p></body></html>
With some configuration, you can have the output pretty printed, with newlines and indent automatically added. |
Support methods
In the previous example, the doctype declaration was rendered using the yieldUnescaped
method. We have also seen the xmlDeclaration
method.
The template engine provides several support methods that will help you render contents appropriately:
Method | Description | Example |
---|---|---|
yield |
Renders contents, but escapes it before rendering |
Template:
Output:
|
yieldUnescaped |
Renders raw contents. The argument is rendered as is, without escaping. |
Template:
Output:
|
xmlDeclaration |
Renders an XML declaration String. If the encoding is specified in the configuration, it is written in the declaration. |
Template:
Output:
If Output:
|
comment |
Renders raw contents inside an XML comment |
Template:
Output:
|
newLine |
Renders a new line. See also |
Template:
Output:
|
pi |
Renders an XML processing instruction. |
Template:
Output:
|
tryEscape |
Returns an escaped string for an object, if it is a |
Template:
Output:
|
Includes
The MarkupTemplateEngine
supports inclusion of contents from another file. Included contents may be:
-
another template
-
raw contents
-
contents to be escaped
Including another template can be done using:
include template: 'other_template.tpl'
Including a file as raw contents, without escaping it, can be done like this:
include unescaped: 'raw.txt'
Eventually, inclusion of text that should be escaped before rendering can be done using:
include escaped: 'to_be_escaped.txt'
Alternatively, you can use the following helper methods instead:
-
includeGroovy(<name>)
to include another template -
includeEscaped(<name>)
to include another file with escaping -
includeUnescaped(<name>)
to include another file without escaping
Calling those methods instead of the include xxx:
syntax can be useful if the name of the file to be included is dynamic (stored in a variable for example).
Files to be included (independently of their type, template or text) are found on classpath. This is one of the reasons why the MarkupTemplateEngine
takes
an optional ClassLoader
as constructor argument (the other reason being that you can include code referencing other classes in a template).
If you don’t want your templates to be on classpath, the MarkupTemplateEngine
accepts a convenient constructor that lets you define the directory where
templates are to be found.
Fragments
Fragments are nested templates. They can be used to provide improved composition in a single template. A fragment consists of a string, the inner template, and a model, used to render this template. Consider the following template:
ul {
pages.each {
fragment "li(line)", line:it
}
}
The fragment
element creates a nested template, and renders it with a model which is specific to this template. Here,
we have the li(line)
fragment, where line
is bound to it
. Since it
corresponds to the iteration of pages
,
we will generate a single li
element for each page in our model:
<ul><li>Page 1</li><li>Page 2</li></ul>
Fragments are interesting to factorize template elements. They come at the price of the compilation of a fragment per template, and they cannot be externalized.
Layouts
Layouts, unlike fragments, refer to other templates. They can be used to compose templates and share common structures. This is often interesting if you have, for example, a common HTML page setup, and that you only want to replace the body. This can be done easily with a layout. First of all, you need to create a layout template:
html {
head {
title(title) (1)
}
body {
bodyContents() (2)
}
}
1 | the title variable (inside the title tag) is a layout variable |
2 | the bodyContents call will render the body |
Then what you need is a template that includes the layout:
layout 'layout-main.tpl', (1)
title: 'Layout example', (2)
bodyContents: contents { p('This is the body') } (3)
1 | use the main-layout.tpl layout file |
2 | set the title variable |
3 | set the bodyContents |
As you can see, bodyContents
will be rendered inside the layout, thanks to the bodyContents()
call in the layout file. As
a result, the template will be rendered as this:
<html><head><title>Layout example</title></head><body><p>This is the body</p></body></html>
The call to the contents
method is used to tell the template engine that the block of code is in fact a specification of a
template, instead of a helper function to be rendered directly. If you don’t add contents
before your specification, then
the contents would be rendered, but you would also see a random string generated, corresponding to the result value of the block.
Layouts are a powerful way to share common elements across multiple templates, without having to rewrite everything or use includes.
Layouts use, by default, a model which is independent from the model of the page where they are used. It is however possible to make them inherit from the parent model. Imagine that the model is defined like this:
model = new HashMap<String,Object>();
model.put('title','Title from main model');
and the following template:
layout 'layout-main.tpl', true, (1)
bodyContents: contents { p('This is the body') }
1 | note the use of true to enable model inheritance |
then it is not necessary to pass the title
value to the layout as in the previous example. The result will be:
<html><head><title>Title from main model</title></head><body><p>This is the body</p></body></html>
But it is also possible to override a value from the parent model:
layout 'layout-main.tpl', true, (1)
title: 'Overriden title', (2)
bodyContents: contents { p('This is the body') }
1 | true means inherit from the parent model |
2 | but title is overriden |
then the output will be:
<html><head><title>Overriden title</title></head><body><p>This is the body</p></body></html>
Rendering contents
Creation of a template engine
On the server side, rendering templates require an instance of groovy.text.markup.MarkupTemplateEngine
and a
groovy.text.markup.TemplateConfiguration
:
TemplateConfiguration config = new TemplateConfiguration(); (1)
MarkupTemplateEngine engine = new MarkupTemplateEngine(config); (2)
Template template = engine.createTemplate("p('test template')"); (3)
Map<String, Object> model = new HashMap<>(); (4)
Writable output = template.make(model); (5)
output.writeTo(writer); (6)
1 | creates a template configuration |
2 | creates a template engine with this configuration |
3 | creates a template instance from a String |
4 | creates a model to be used in the template |
5 | bind the model to the template instance |
6 | render output |
There are several possible options to parse templates:
-
from a
String
, usingcreateTemplate(String)
-
from a
Reader
, usingcreateTemplate(Reader)
-
from a
URL
, usingcreateTemplate(URL)
-
given a template name, using
createTemplateByPath(String)
The last version should in general be preferred:
Template template = engine.createTemplateByPath("main.tpl");
Writable output = template.make(model);
output.writeTo(writer);
Configuration options
The behavior of the engine can be tweaked with several configuration options accessible through the TemplateConfiguration
class:
Option | Default value | Description | Example |
---|---|---|---|
declarationEncoding |
null |
Determines the value of the encoding to be written when |
Template:
Output:
If Output:
|
expandEmptyElements |
false |
If true, empty tags are rendered in their expanded form. |
Template:
Output:
If Output:
|
useDoubleQuotes |
false |
If true, use double quotes for attributes instead of simple quotes |
Template:
Output:
If Output:
|
newLineString |
System default (system property |
Allows to choose what string is used when a new line is rendered |
Template:
If Output:
|
autoEscape |
false |
If true, variables from models are automatically escaped before rendering. |
|
autoIndent |
false |
If true, performs automatic indentation after new lines |
|
autoIndentString |
four (4) spaces |
The string to be used as indent. |
|
autoNewLine |
false |
If true, performs automatic insertion of new lines |
|
baseTemplateClass |
|
Sets the super class of compiled templates. This can be used to provide application specific templates. |
|
locale |
Default locale |
Sets the default locale for templates. |
Once the template engine has been created, it is unsafe to change the configuration. |
Automatic formatting
By default, the template engine will render output without any specific formatting. Some configuration options can improve the situation:
-
autoIndent
is responsible for auto-indenting after a new line is inserted -
autoNewLine
is responsible for automatically inserting new lines based on the original formatting of the template source
In general, it is recommanded to set both autoIndent
and autoNewLine
to true if you want human-readable, pretty printed, output:
config.setAutoNewLine(true);
config.setAutoIndent(true);
Using the following template:
html {
head {
title('Title')
}
}
The output will now be:
<html>
<head>
<title>Title</title>
</head>
</html>
We can slightly change the template so that the title
intruction is found on the same line as the head
one:
html {
head { title('Title')
}
}
And the output will reflect that:
<html>
<head><title>Title</title>
</head>
</html>
New lines are only inserted where curly braces for tags are found, and the insertion corresponds to where the nested content is found. This means that tags in the body of another tag will not trigger new lines unless they use curly braces themselves:
html {
head {
meta(attr:'value') (1)
title('Title') (2)
newLine() (3)
meta(attr:'value2') (4)
}
}
1 | a new line is inserted because meta is not on the same line as head |
2 | no new line is inserted, because we’re on the same depth as the previous tag |
3 | we can force rendering of a new line by explicitly calling newLine |
4 | and this tag will be rendered on a separate line |
This time, the output will be:
<html>
<head>
<meta attr='value'/><title>Title</title>
<meta attr='value2'/>
</head>
</html>
By default, the renderer uses four(4) spaces as indent, but you can change it by setting the TemplateConfiguration#autoIndentString
property.
Automatic escaping
By default, contents which is read from the model is rendered as is. If this contents comes from user input, it can be sensible, and you might
want to escape it by default, for example to avoid XSS injection. For that, the template configuration provides an option which will automatically
escape objects from the model, as long as they inherit from CharSequence
(typically, `String`s).
Let’s imagine the following setup:
config.setAutoEscape(false);
model = new HashMap<String,Object>();
model.put("unsafeContents", "I am an <html> hacker.");
and the following template:
html {
body {
div(unsafeContents)
}
}
Then you wouldn’t want the HTML from unsafeContents
to be rendered as is, because of potential security issues:
<html><body><div>I am an <html> hacker.</div></body></html>
Automatic escaping will fix this:
config.setAutoEscape(true);
And now the output is properly escaped:
<html><body><div>I am an <html> hacker.</div></body></html>
Note that using automatic escaping doesn’t prevent you from including unescaped contents from the model. To do this, your template should then explicitly
mention that a model variable should not be escaped by prefixing it with unescaped.
, like in this example:
html {
body {
div(unescaped.unsafeContents)
}
}
Common gotchas
Say that you want to generate a <p>
tag which contains a string containing markup:
p {
yield "This is a "
a(href:'target.html', "link")
yield " to another page"
}
and generates:
<p>This is a <a href='target.html'>link</a> to another page</p>
Can’t this be written shorter? A naive alternative would be:
p {
yield "This is a ${a(href:'target.html', "link")} to another page"
}
but the result will not look as expected:
<p><a href='target.html'>link</a>This is a to another page</p>
The reason is that the markup template engine is a streaming engine. In the original version, the first yield
call
generates a string which is streamed to the output, then the a
link is generated and streamed, and then the last yield
call is streamed, leading in an execution in order. But with the string version above, the order of execution is different:
-
the
yield
call requires an argument, a string -
that arguments needs to be evaluated before the yield call is generated
so evaluating the string leads to an execution of the a(href:...)
call before yield
is itself called. This is not
what you want to do. Instead, you want to generate a string which contains markup, which is then passed to the yield
call. This can be done this way:
p("This is a ${stringOf {a(href:'target.html', "link")}} to another page")
Note the stringOf
call, which basically tells the markup template engine that the underlying markup needs to be rendered
separately and exported as a string. Note that for simple expressions, stringOf
can be replaced by an alternate tag
notation that starts with a dollar sign:
p("This is a ${$a(href:'target.html', "link")} to another page")
It is worth noting that using stringOf or the special $tag notation triggers the creation of a distinct string writer
which is then used to render the markup. It is slower than using the version with calls to yield which perform direct
streaming of the markup instead.
|
Internationalization
The template engine has native support for internationalization. For that, when you create the TemplateConfiguration
, you can provide
a Locale
which is the default locale to be used for templates. Each template may have different versions, one for each locale. The
name of the template makes the difference:
-
file.tpl
: default template file -
file_fr_FR.tpl
: french version of the template -
file_en_US.tpl
: american english version of the template -
…
When a template is rendered or included, then:
-
if the template name or include name explicitly sets a locale, the specific version is included, or the default version if not found
-
if the template name doesn’t include a locale, the version for the
TemplateConfiguration
locale is used, or the default version if not found
For example, imagine the default locale is set to Locale.ENGLISH
and that the main template includes:
include template: 'locale_include_fr_FR.tpl'
then the template is rendered using the specific template:
Texte en français
Using an include without specifying a locale will make the template engine look for a template with the configured locale, and if not, fallback to the default, like here:
include template: 'locale_include.tpl'
Default text
However, changing the default locale of the template engine to Locale.FRANCE
will change the output, because the template engine will now look for a file
with the fr_FR
locale:
Texte en français
This strategy lets you translate your templates one by one, by relying on default templates, for which no locale is set in the file name.
Custom template classes
By default, templates created inherit the groovy.text.markup.BaseTemplate
class. It may be interesting for an application to provide a different
template class, for example to provide additional helper methods which are aware of the application, or customized rendering primitives (for HTML,
for example).
The template engine provides this ability by setting an alternative baseTemplateClass
in the TemplateConfiguration
:
config.setBaseTemplateClass(MyTemplate.class);
The custom base class has to extend BaseClass
like in this example:
public abstract class MyTemplate extends BaseTemplate {
private List<Module> modules
public MyTemplate(
final MarkupTemplateEngine templateEngine,
final Map model,
final Map<String, String> modelTypes,
final TemplateConfiguration configuration) {
super(templateEngine, model, modelTypes, configuration)
}
List<Module> getModules() {
return modules
}
void setModules(final List<Module> modules) {
this.modules = modules
}
boolean hasModule(String name) {
modules?.any { it.name == name }
}
}
This example shows a class which provides an additional method named hasModule
, which can then be used directly in the template:
if (hasModule('foo')) {
p 'Found module [foo]'
} else {
p 'Module [foo] not found'
}
Type checked templates
Optional type checking
Even if templates are not type checked, they are statically compiled. This means that once the templates are compiled, performance should be very good. For some applications, it might be good to make sure that templates are valid before they are actually rendered. This means failing template compilation, for example, if a method on a model variable doesn’t exist.
The MarkupTemplateEngine
provides such a facility. Templates can be optionally type checked. For that, the developer must provide additional information at
template creation time, which is the types of the variables found in the model. Imagine a model exposing a list of pages, where a page is defined as:
public class Page {
Long id
String title
String body
}
Then a list of pages can be exposed in the model, like this:
Page p = new Page();
p.setTitle("Sample page");
p.setBody("Page body");
List<Page> pages = new LinkedList<>();
pages.add(p);
model = new HashMap<String,Object>();
model.put("pages", pages);
A template can use it easily:
pages.each { page -> (1)
p("Page title: $page.title") (2)
p(page.text) (3)
}
1 | iterate on pages from the model |
2 | page.title is valid |
3 | page.text is not (should be page.body ) |
Without type checking, the compilation of the template succeeds, because the template engine doesn’t know about the model until a page is actually rendered. This means that the problem would only surface at runtime, once the page is rendered:
No such property: text
In some situations, this can be complicated to sort out or even notice. By declaring the type of the pages
to the template engine, we’re now capable of failing at compile time:
modelTypes = new HashMap<String,String>(); (1)
modelTypes.put("pages", "List<Page>"); (2)
Template template = engine.createTypeCheckedModelTemplate("main.tpl", modelTypes) (3)
1 | create a map which will hold the model types |
2 | declare the type of the pages variables (note the use of a string for the type) |
3 | use createTypeCheckedModelTemplate instead of createTemplate |
This time, when the template is compiled at the last line, an error occurs:
[Static type checking] - No such property: text for class: Page
This means that you don’t need to wait for the page to be rendered to see an error. The use of createTypeCheckedModelTemplate
is mandatory.
Alternative declaration of types
Alternatively, if the developer is also the one who writes the templates, it is possible to declare the types of the expected variables
directly in the template. In this case, even if you call createTemplate
, it will be type checked:
modelTypes = { (1)
List<Page> pages (2)
}
pages.each { page ->
p("Page title: $page.title")
p(page.text)
}
1 | types need to be declared in the modelTypes header |
2 | declare one variable per object in the model |
Performance of type checked templates
An additional interest of using type checked models is that performance should improve. By telling the type checker what are the expected types, you also let the compiler generate optimized code for that, so if you are looking for the best performance, consider using type checked templates.
4.9.7. Other solutions
Also, there are other templating solutions that can be used along with Groovy, such as FreeMarker, Velocity, StringTemplate and others.
4.11. Integrating Groovy in a Java application
4.11.1. Groovy integration mechanisms
The Groovy language proposes several ways to integrate itself into applications (Java or even Groovy) at runtime, from the most basic, simple code execution to the most complete, integrating caching and compiler customization.
All the examples written in this section are using Groovy, but the same integration mechanisms can be used from Java. |
Eval
The groovy.util.Eval
class is the simplest way to execute Groovy dynamically at runtime. This can be done by calling the me
method:
import groovy.util.Eval
assert Eval.me('33*3') == 99
assert Eval.me('"foo".toUpperCase()') == 'FOO'
Eval
supports multiple variants that accept parameters for simple evaluation:
assert Eval.x(4, '2*x') == 8 (1)
assert Eval.me('k', 4, '2*k') == 8 (2)
assert Eval.xy(4, 5, 'x*y') == 20 (3)
assert Eval.xyz(4, 5, 6, 'x*y+z') == 26 (4)
1 | Simple evaluation with one bound parameter named x |
2 | Same evaluation, with a custom bound parameter named k |
3 | Simple evaluation with two bound parameters named x and y |
4 | Simple evaluation with three bound parameters named x , y and z |
The Eval
class makes it very easy to evaluate simple scripts, but doesn’t scale: there is no caching of the script, and
it isn’t meant to evaluate more than one liners.
GroovyShell
Multiple sources
The groovy.lang.GroovyShell
class is the preferred way to evaluate scripts with the ability to cache the resulting
script instance. Although the Eval
class returns the result of the execution of the compiled script, the GroovyShell
class offers more options.
def shell = new GroovyShell() (1)
def result = shell.evaluate '3*5' (2)
def result2 = shell.evaluate(new StringReader('3*5')) (3)
assert result == result2
def script = shell.parse '3*5' (4)
assert script instanceof groovy.lang.Script
assert script.run() == 15 (5)
1 | create a new GroovyShell instance |
2 | can be used as Eval with direct execution of the code |
3 | can read from multiple sources (String , Reader , File , InputStream ) |
4 | can defer execution of the script. parse returns a Script instance |
5 | Script defines a run method |
Sharing data between a script and the application
It is possible to share data between the application and the script using a groovy.lang.Binding
:
def sharedData = new Binding() (1)
def shell = new GroovyShell(sharedData) (2)
def now = new Date()
sharedData.setProperty('text', 'I am shared data!') (3)
sharedData.setProperty('date', now) (4)
String result = shell.evaluate('"At $date, $text"') (5)
assert result == "At $now, I am shared data!"
1 | create a new Binding that will contain shared data |
2 | create a GroovyShell using this shared data |
3 | add a string to the binding |
4 | add a date to the binding (you are not limited to simple types) |
5 | evaluate the script |
Note that it is also possible to write from the script into the binding:
def sharedData = new Binding() (1)
def shell = new GroovyShell(sharedData) (2)
shell.evaluate('foo=123') (3)
assert sharedData.getProperty('foo') == 123 (4)
1 | create a new Binding instance |
2 | create a new GroovyShell using that shared data |
3 | use an undeclared variable to store the result into the binding |
4 | read the result from the caller |
It is important to understand that you need to use an undeclared variable if you want to write into the binding. Using
def
or an explicit
type like in the example below would fail because you would then create a local variable:
def sharedData = new Binding()
def shell = new GroovyShell(sharedData)
shell.evaluate('int foo=123')
try {
assert sharedData.getProperty('foo')
} catch (MissingPropertyException e) {
println "foo is defined as a local variable"
}
You must be very careful when using shared data in a multithreaded environment. The Binding instance that
you pass to GroovyShell is not thread safe, and shared by all scripts.
|
It is possible to work around the shared instance of Binding
by leveraging the Script
instance which is returned
by parse
:
def shell = new GroovyShell()
def b1 = new Binding(x:3) (1)
def b2 = new Binding(x:4) (2)
def script = shell.parse('x = 2*x')
script.binding = b1
script.run()
script.binding = b2
script.run()
assert b1.getProperty('x') == 6
assert b2.getProperty('x') == 8
assert b1 != b2
1 | will store the x variable inside b1 |
2 | will store the x variable inside b2 |
However, you must be aware that you are still sharing the same instance of a script. So this technique cannot be used if you have two threads working on the same script. In that case, you must make sure of creating two distinct script instances:
def shell = new GroovyShell()
def b1 = new Binding(x:3)
def b2 = new Binding(x:4)
def script1 = shell.parse('x = 2*x') (1)
def script2 = shell.parse('x = 2*x') (2)
assert script1 != script2
script1.binding = b1 (3)
script2.binding = b2 (4)
def t1 = Thread.start { script1.run() } (5)
def t2 = Thread.start { script2.run() } (6)
[t1,t2]*.join() (7)
assert b1.getProperty('x') == 6
assert b2.getProperty('x') == 8
assert b1 != b2
1 | create an instance of script for thread 1 |
2 | create an instance of script for thread 2 |
3 | assign first binding to script 1 |
4 | assign second binding to script 2 |
5 | start first script in a separate thread |
6 | start second script in a separate thread |
7 | wait for completion |
In case you need thread safety like here, it is more advisable to use the GroovyClassLoader directly instead.
Custom script class
We have seen that the parse
method returns an instance of groovy.lang.Script
, but it is possible to use a custom
class, given that it extends Script
itself. It can be used to provide additional behavior to the script like in
the example below:
abstract class MyScript extends Script {
String name
String greet() {
"Hello, $name!"
}
}
The custom class defines a property called name
and a new method called greet
. This class can be used as the script
base class by using a custom configuration:
import org.codehaus.groovy.control.CompilerConfiguration
def config = new CompilerConfiguration() (1)
config.scriptBaseClass = 'MyScript' (2)
def shell = new GroovyShell(this.class.classLoader, new Binding(), config) (3)
def script = shell.parse('greet()') (4)
assert script instanceof MyScript
script.setName('Michel')
assert script.run() == 'Hello, Michel!'
1 | create a CompilerConfiguration instance |
2 | instruct it to use MyScript as the base class for scripts |
3 | then use the compiler configuration when you create the shell |
4 | the script now has access to the new method greet |
You are not limited to the sole scriptBaseClass configuration. You can use any of the compiler configuration tweaks, including the compilation customizers. |
GroovyClassLoader
In the previous section, we have shown that GroovyShell
was an easy tool to execute scripts, but
it makes it complicated to compile anything but scripts. Internally, it makes use of the groovy.lang.GroovyClassLoader
,
which is at the heart of the compilation and loading of classes at runtime.
By leveraging the GroovyClassLoader
instead of GroovyShell
, you will be able to load classes, instead of instances
of scripts:
import groovy.lang.GroovyClassLoader
def gcl = new GroovyClassLoader() (1)
def clazz = gcl.parseClass('class Foo { void doIt() { println "ok" } }') (2)
assert clazz.name == 'Foo' (3)
def o = clazz.newInstance() (4)
o.doIt() (5)
1 | create a new GroovyClassLoader |
2 | parseClass will return an instance of Class |
3 | you can check that the class which is returns is really the one defined in the script |
4 | and you can create a new instance of the class, which is not a script |
5 | then call any method on it |
A GroovyClassLoader keeps a reference of all the classes it created, so it is easy to create a memory leak. In particular, if you execute the same script twice, if it is a String, then you obtain two distinct classes! |
import groovy.lang.GroovyClassLoader
def gcl = new GroovyClassLoader()
def clazz1 = gcl.parseClass('class Foo { }') (1)
def clazz2 = gcl.parseClass('class Foo { }') (2)
assert clazz1.name == 'Foo' (3)
assert clazz2.name == 'Foo'
assert clazz1 != clazz2 (4)
1 | dynamically create a class named "Foo" |
2 | create an identical looking class, using a separate parseClass call |
3 | make sure both classes have the same name |
4 | but they are actually different! |
The reason is that a GroovyClassLoader
doesn’t keep track of the source text. If you want to have the same instance,
then the source must be a file, like in this example:
def gcl = new GroovyClassLoader()
def clazz1 = gcl.parseClass(file) (1)
def clazz2 = gcl.parseClass(new File(file.absolutePath)) (2)
assert clazz1.name == 'Foo' (3)
assert clazz2.name == 'Foo'
assert clazz1 == clazz2 (4)
1 | parse a class from a File |
2 | parse a class from a distinct file instance, but pointing to the same physical file |
3 | make sure our classes have the same name |
4 | but now, they are the same instance |
Using a File
as input, the GroovyClassLoader
is capable of caching the generated class file, which avoids
creating multiple classes at runtime for the same source.
GroovyScriptEngine
The groovy.util.GroovyScriptEngine
class provides a flexible foundation for applications which rely on script
reloading and script dependencies. While GroovyShell
focuses on standalone Script`s and `GroovyClassLoader
handles
dynamic compilation and loading of any Groovy class, the GroovyScriptEngine
will add a layer on top of GroovyClassLoader
to handle both script dependencies and reloading.
To illustrate this, we will create a script engine and execute code in an infinite loop. First of all, you need to create a directory with the following script inside:
class Greeter {
String sayHello() {
def greet = "Hello, world!"
greet
}
}
new Greeter()
then you can execute this code using a GroovyScriptEngine
:
def binding = new Binding()
def engine = new GroovyScriptEngine([tmpDir.toURI().toURL()] as URL[]) (1)
while (true) {
def greeter = engine.run('ReloadingTest.groovy', binding) (2)
println greeter.sayHello() (3)
Thread.sleep(1000)
}
1 | create a script engine which will look for sources into our source directory |
2 | execute the script, which will return an instance of Greeter |
3 | print the greeting message |
At this point, you should see a message printed every second:
Hello, world! Hello, world! ...
Without interrupting the script execution, now replace the contents of the ReloadingTest
file with:
class Greeter {
String sayHello() {
def greet = "Hello, Groovy!"
greet
}
}
new Greeter()
And the message should change to:
Hello, world! ... Hello, Groovy! Hello, Groovy! ...
But it is also possible to have a dependency on another script. To illustrate this, create the following file into the same directory, without interrupting the executing script:
class Dependency {
String message = 'Hello, dependency 1'
}
and update the ReloadingTest
script like this:
import Dependency
class Greeter {
String sayHello() {
def greet = new Dependency().message
greet
}
}
new Greeter()
And this time, the message should change to:
Hello, Groovy! ... Hello, dependency 1! Hello, dependency 1! ...
And as a last test, you can update the Dependency.groovy
file without touching the ReloadingTest
file:
class Dependency {
String message = 'Hello, dependency 2'
}
And you should observe that the dependent file was reloaded:
Hello, dependency 1! ... Hello, dependency 2! Hello, dependency 2!
CompilationUnit
Ultimately, it is possible to perform more operations during compilation by relying directly on the
org.codehaus.groovy.control.CompilationUnit
class. This class is responsible for determining the various steps of
compilation and would let you introduce new steps or even stop compilation at various phases. This is for example how
stub generation is done, for the joint compiler.
However, overriding CompilationUnit
is not recommanded and should only be done if no other standard solution works.
4.11.2. Bean Scripting Framework
The Bean Scripting Framework is an attempt to create an API to allow calling scripting languages from Java. It hasn’t been updated for long and abandonned in favor of the standard JSR-223 API. |
The BSF engine for Groovy is implemented by the org.codehaus.groovy.bsf.GroovyEngine
class. However, that fact is
normally hidden away by the BSF APIs. You just treat Groovy like any of the other scripting languages via the BSF
API.
Since Groovy has its own native support for integration with Java, you only need to worry about BSF if you also want to also be able to call other languages, e.g. JRuby or if you want to remain very loosely coupled from your scripting language. |
Getting started
Provided you have Groovy and BSF jars in your classpath, you can use the following Java code to run a sample Groovy script:
String myScript = "println('Hello World')\n return [1, 2, 3]";
BSFManager manager = new BSFManager();
List answer = (List) manager.eval("groovy", "myScript.groovy", 0, 0, myScript);
assertEquals(3, answer.size());
Passing in variables
BSF lets you pass beans between Java and your scripting language. You can register/unregister beans which makes them known to BSF. You can then use BSF methods to lookup beans as required. Alternatively, you can declare/undeclare beans. This will register them but also make them available for use directly in your scripting language. This second approach is the normal approach used with Groovy. Here is an example:
BSFManager manager = new BSFManager();
manager.declareBean("xyz", 4, Integer.class);
Object answer = manager.eval("groovy", "test.groovy", 0, 0, "xyz + 1");
assertEquals(5, answer);
Other calling options
The previous examples used the eval method. BSF makes multiple methods available for your use (see the BSF documentation for more details). One of the other available methods is apply. It allows you to define an anonymous function in your scripting language and apply that function to arguments. Groovy supports this function using closures. Here is an example:
BSFManager manager = new BSFManager();
Vector<String> ignoreParamNames = null;
Vector<Integer> args = new Vector<Integer>();
args.add(2);
args.add(5);
args.add(1);
Integer actual = (Integer) manager.apply("groovy", "applyTest", 0, 0,
"def summer = { a, b, c -> a * 100 + b * 10 + c }", ignoreParamNames, args);
assertEquals(251, actual.intValue());
Access to the scripting engine
Although you don’t normally need it, BSF does provide a hook that lets you get directly to the scripting engine. One of the functions which the engine can perform is to invoke a single method call on an object. Here is an example:
BSFManager manager = new BSFManager();
BSFEngine bsfEngine = manager.loadScriptingEngine("groovy");
manager.declareBean("myvar", "hello", String.class);
Object myvar = manager.lookupBean("myvar");
String result = (String) bsfEngine.call(myvar, "reverse", new Object[0]);
assertEquals("olleh", result);
4.11.3. JSR 223 javax.script API (TBD)
JSR-223 is a standard API for calling scripting frameworks in Java. It is available since Java 6 and aims at providing a common framework for calling multiple languages from Java. Groovy provides its own richer integration mechanisms, and if you don’t plan to use multiple languages in the same application, it is recommanded that you use the Groovy integration mechanisms instead of the limited JSR-223 API. |
Here is how you need to initialize the JSR-223 engine to talk to Groovy from Java:
import javax.script.ScriptEngine;
import javax.script.ScriptEngineManager;
import javax.script.ScriptException;
...
ScriptEngineManager factory = new ScriptEngineManager();
ScriptEngine engine = factory.getEngineByName("groovy");
Then you can execute Groovy scripts easily:
Integer sum = (Integer) engine.eval("(1..10).sum()");
assertEquals(new Integer(55), sum);
It is also possible to share variables:
engine.put("first", "HELLO");
engine.put("second", "world");
String result = (String) engine.eval("first.toLowerCase() + ' ' + second.toUpperCase()");
assertEquals("hello WORLD", result);
This next example illustrates calling an invokable function:
import javax.script.Invocable;
...
ScriptEngineManager factory = new ScriptEngineManager();
ScriptEngine engine = factory.getEngineByName("groovy");
String fact = "def factorial(n) { n == 1 ? 1 : n * factorial(n - 1) }";
engine.eval(fact);
Invocable inv = (Invocable) engine;
Object[] params = {5};
Object result = inv.invokeFunction("factorial", params);
assertEquals(new Integer(120), result);
The engine keeps per default hard references to the script functions. To
change this you should set a engine level scoped attribute to the script
context of the name #jsr223.groovy.engine.keep.globals
with a
String being phantom
to use phantom references, weak
to use weak
references or soft
to use soft references - casing is ignored. Any
other string will cause the use of hard references.
4.12. Domain-Specific Languages
4.12.1. Command chains
Groovy lets you omit parentheses around the arguments of a
method call for top-level statements. “command chain” feature extends this by allowing us to chain such
parentheses-free method calls, requiring neither parentheses around arguments, nor dots between the chained calls.
The general idea is that a call like a b c d
will actually be equivalent to a(b).c(d)
. This
also works with multiple arguments, closure arguments, and even named arguments. Furthermore, such command chains can
also appear on the right-hand side of assignments. Let’s have a look at some examples
supported by this new syntax:
// equivalent to: turn(left).then(right)
turn left then right
// equivalent to: take(2.pills).of(chloroquinine).after(6.hours)
take 2.pills of chloroquinine after 6.hours
// equivalent to: paint(wall).with(red, green).and(yellow)
paint wall with red, green and yellow
// with named parameters too
// equivalent to: check(that: margarita).tastes(good)
check that: margarita tastes good
// with closures as parameters
// equivalent to: given({}).when({}).then({})
given { } when { } then { }
It is also possible to use methods in the chain which take no arguments, but in that case, the parentheses are needed:
// equivalent to: select(all).unique().from(names)
select all unique() from names
If your command chain contains an odd number of elements, the chain will be composed of method / arguments, and will finish by a final property access:
// equivalent to: take(3).cookies
// and also this: take(3).getCookies()
take 3 cookies
This command chain approach opens up interesting possibilities in terms of the much wider range of DSLs which can now be written in Groovy.
The above examples illustrate using a command chain based DSL but not how to create one. There are various strategies that you can use, but to illustrate creating such a DSL, we will show a couple of examples - first using maps and Closures:
show = { println it }
square_root = { Math.sqrt(it) }
def please(action) {
[the: { what ->
[of: { n -> action(what(n)) }]
}]
}
// equivalent to: please(show).the(square_root).of(100)
please show the square_root of 100
// ==> 10.0
As a second example, consider how you might write a DSL for simplifying
one of your existing APIs. Maybe you need to put this code in front of
customers, business analysts or testers who might be not hard-core Java
developers. We’ll use the Splitter
from the Google
Guava libraries project as it
already has a nice Fluent API. Here is how we might use it out of the
box:
@Grab('com.google.guava:guava:r09')
import com.google.common.base.*
def result = Splitter.on(',').trimResults(CharMatcher.is('_' as char)).split("_a ,_b_ ,c__").iterator().toList()
It reads fairly well for a Java developer but if that is not your target audience or you have many such statements to write, it could be considered a little verbose. Again, there are many options for writing a DSL. We’ll keep it simple with Maps and Closures. We’ll first write a helper method:
@Grab('com.google.guava:guava:r09')
import com.google.common.base.*
def split(string) {
[on: { sep ->
[trimming: { trimChar ->
Splitter.on(sep).trimResults(CharMatcher.is(trimChar as char)).split(string).iterator().toList()
}]
}]
}
now instead of this line from our original example:
def result = Splitter.on(',').trimResults(CharMatcher.is('_' as char)).split("_a ,_b_ ,c__").iterator().toList()
we can write this:
def result = split "_a ,_b_ ,c__" on ',' trimming '_\'
4.12.2. Operator overloading
Various operators in Groovy are mapped onto regular method calls on objects.
This allows you to provide your own Java or Groovy objects which can take advantage of operator overloading. The following table describes the operators supported in Groovy and the methods they map to.
Operator | Method |
---|---|
|
a.plus(b) |
|
a.minus(b) |
|
a.multiply(b) |
|
a.power(b) |
|
a.div(b) |
|
a.mod(b) |
|
a.or(b) |
|
a.and(b) |
|
a.xor(b) |
|
a.next() |
|
a.previous() |
|
a.getAt(b) |
|
a.putAt(b, c) |
|
a.leftShift(b) |
|
a.rightShift(b) |
|
a.rightShiftUnsigned(b) |
|
b.isCase(a) |
|
a.asBoolean() |
|
a.bitwiseNegate() |
|
a.negative() |
|
a.positive() |
|
a.asType(b) |
|
a.equals(b) |
|
! a.equals(b) |
|
a.compareTo(b) |
|
a.compareTo(b) > 0 |
|
a.compareTo(b) >= 0 |
|
a.compareTo(b) < 0 |
|
a.compareTo(b) <= 0 |
4.12.3. Script base classes
The Script class
Groovy scripts are always compiled to classes. For example, a script as simple as:
println 'Hello from Groovy'
is compiled to a class extending the abstract groovy.lang.Script
class. This class contains a single abstract
method called run. When a script is compiled, then its body will become the run method, while the other methods
found in the script are found in the implementing class. The Script
class provides base support for integration
with your application through the Binding
object, as illustrated in this example:
def binding = new Binding() (1)
def shell = new GroovyShell(binding) (2)
binding.setVariable('x',1) (3)
binding.setVariable('y',3)
shell.evaluate 'z=2*x+y' (4)
assert binding.getVariable('z') == 5 (5)
1 | a binding is used to share data between the script and the calling class |
2 | a GroovyShell can be used with this binding |
3 | input variables are set from the calling class inside the binding |
4 | then the script is evaluated |
5 | and the z variable has been "exported" into the binding |
This is a very practical way to share data between the caller and the script, however it may be insufficient or not
practical in some cases. For that purpose, Groovy allows you to set your own base script class. A base script class
has to extend groovy.lang.Script
and be a single abstract method type:
abstract class MyBaseClass extends Script {
String name
public void greet() { println "Hello, $name!" }
}
Then the custom script base class can be declared in the compiler configuration, for example:
def config = new CompilerConfiguration() (1)
config.scriptBaseClass = 'MyBaseClass' (2)
def b = new Binding()
def shell = new GroovyShell(this.class.classLoader, b, config) (3)
shell.evaluate """
setName 'Judith' (4)
greet()
"""
1 | create a custom compiler configuration |
2 | set the base script class to our custom base script class |
3 | then create a GroovyShell using that configuration |
4 | the script will then extend the base script class, giving direct access to the name property and greet method |
The @BaseScript annotation
As an alternative, it is also possible to use the @BaseScript
annotation directly into a script:
import groovy.transform.BaseScript
@BaseScript MyBaseClass baseScript
setName 'Judith'
greet()
where @BaseScript
should annotate a variable which type is the class of the base script. Alternatively, you can set
the base script class as a member of the @BaseScript
annotation itself:
@BaseScript(MyBaseClass)
import groovy.transform.BaseScript
setName 'Judith'
greet()
Alternate abstract method
We have seen that the base script class is a single abstract method type that needs to implement the run
method. The
run
method is executed by the script engine automatically. In some circumstances it may be interesting to have a base
class which implements the run
method, but provides an alternative abstract method to be used for the script body.
For example, the base script run
method might perform some initialization before the run
method is executed. This
is possible by doing this:
abstract class MyBaseClass extends Script {
int count
abstract void scriptBody() (1)
def run() {
count++ (2)
scriptBody() (3)
count (4)
}
}
1 | the base script class should define one (and only one) abstract method |
2 | the run method can be overriden and perform a task before executing the script body |
3 | run calls the abstract scriptBody method which will delegate to the user script |
4 | then it can return something else than the value from the script |
If you execute this code:
def result = shell.evaluate """
println 'Ok'
"""
assert result == 1
Then you will see that the script is executed, but the result of the evaluation is 1
as returned by the run
method of the base class. It is even clearer if you use parse
instead of evaluate
, because it would allow you to
execute the run
method several times on the same script instance:
def script = shell.parse("println 'Ok'")
assert script.run() == 1
assert script.run() == 2
4.12.4. Adding properties to numbers
In Groovy number types are considered equal to any other types. As such, it is possible to enhance numbers by adding properties or methods to them. This can be very handy when dealing with measurable quantities for example. Details about how existing classes can be enhanced in Groovy are found in the extension modules section or the categories section.
An illustration of this can be found in Groovy using the TimeCategory
:
use(TimeCategory) {
println 1.minute.from.now (1)
println 10.hours.ago
def someDate = new Date() (2)
println someDate - 3.months
}
1 | using the TimeCategory , a property minute is added to the Integer class |
2 | similarily, the months method returns a groovy.time.DatumDependentDuration which can be used in calculus |
Categories are lexically bound, making them a great fit for internal DSLs.
4.12.5. @DelegatesTo
Explaining delegation strategy at compile time
@groovy.lang.DelegatesTo
is a documentation and compile-time annotation aimed at:
-
documenting APIs that use closures as arguments
-
providing type information for the static type checker and compiler
The Groovy language is a platform of choice for building DSLs. Using closures, it’s quite easy to create custom control structures, as well as it is simple to create builders. Imagine that you have the following code:
email {
from 'dsl-guru@mycompany.com'
to 'john.doe@waitaminute.com'
subject 'The pope has resigned!'
body {
p 'Really, the pope has resigned!'
}
}
One way of implementing this is using the builder strategy, which
implies a method, named email
which accepts a closure as an argument.
The method may delegate subsequent calls to an object that implements
the from
, to
, subject
and body
methods. Again, body
is a
method which accepts a closure as an argument and that uses the builder
strategy.
Implementing such a builder is usually done the following way:
def email(Closure cl) {
def email = new EmailSpec()
def code = cl.rehydrate(email, this, this)
code.resolveStrategy = Closure.DELEGATE_ONLY
code()
}
the EmailSpec
class implements the from
, to
, … methods. By
calling rehydrate
, we’re creating a copy of the closure for which we
set the delegate
, owner
and thisObject
values. Setting the owner
and the this
object is not very important here since we will use the
DELEGATE_ONLY
strategy which says that the method calls will be
resolved only against the delegate of the closure.
class EmailSpec {
void from(String from) { println "From: $from"}
void to(String... to) { println "To: $to"}
void subject(String subject) { println "Subject: $subject"}
void body(Closure body) {
def bodySpec = new BodySpec()
def code = body.rehydrate(bodySpec, this, this)
code.resolveStrategy = Closure.DELEGATE_ONLY
code()
}
}
The EmailSpec
class has itself a body
method accepting a closure that is cloned and executed. This is what
we call the builder pattern in Groovy.
One of the problems with the code that we’ve shown is that the user of
the email
method doesn’t have any information about the methods that
he’s allowed to call inside the closure. The only possible information
is from the method documentation. There are two issues with this: first
of all, documentation is not always written, and if it is, it’s not
always available (javadoc not downloaded, for example). Second, it
doesn’t help IDEs. What would be really interesting, here, is for IDEs
to help the developer by suggesting, once they are in the closure body,
methods that exist on the email
class.
Moreover, if the user calls a method in the closure which is not defined
by the EmailSpec
class, the IDE should at least issue a warning (because
it’s very likely that it will break at runtime).
One more problem with the code above is that it is not compatible with static type checking. Type checking would let the user know if a method call is authorized at compile time instead of runtime, but if you try to perform type checking on this code:
email {
from 'dsl-guru@mycompany.com'
to 'john.doe@waitaminute.com'
subject 'The pope has resigned!'
body {
p 'Really, the pope has resigned!'
}
}
Then the type checker will know that there’s an email
method accepting
a Closure
, but it will complain for every method call inside the
closure, because from
, for example, is not a method which is defined
in the class. Indeed, it’s defined in the EmailSpec
class and it has
absolutely no hint to help it knowing that the closure delegate will, at
runtime, be of type EmailSpec
:
@groovy.transform.TypeChecked
void sendEmail() {
email {
from 'dsl-guru@mycompany.com'
to 'john.doe@waitaminute.com'
subject 'The pope has resigned!'
body {
p 'Really, the pope has resigned!'
}
}
}
will fail compilation with errors like this one:
[Static type checking] - Cannot find matching method MyScript#from(java.lang.String). Please check if the declared type is right and if the method exists. @ line 31, column 21. from 'dsl-guru@mycompany.com'
@DelegatesTo
For those reasons, Groovy 2.1 introduced a new annotation
named @DelegatesTo
. The goal of this annotation is to solve both the
documentation issue, that will let your IDE know about the expected
methods in the closure body, and it will also solve the type checking
issue, by giving hints to the compiler about what are the potential
receivers of method calls in the closure body.
The idea is to annotate the Closure
parameter of the email
method:
def email(@DelegatesTo(EmailSpec) Closure cl) {
def email = new EmailSpec()
def code = cl.rehydrate(email, this, this)
code.resolveStrategy = Closure.DELEGATE_ONLY
code()
}
What we’ve done here is telling the compiler (or the IDE) that when the
method will be called with a closure, the delegate of this closure will
be set to an object of type email
. But there is still a problem: the
defaut delegation strategy is not the one which is used in our method.
So we will give more information and tell the compiler (or the IDE) that
the delegation strategy is also changed:
def email(@DelegatesTo(strategy=Closure.DELEGATE_ONLY, value=EmailSpec) Closure cl) {
def email = new EmailSpec()
def code = cl.rehydrate(email, this, this)
code.resolveStrategy = Closure.DELEGATE_ONLY
code()
}
Now, both the IDE and the type checker (if you are using @TypeChecked
)
will be aware of the delegate and the delegation strategy. This is very
nice because it will both allow the IDE to provide smart completion, but
it will also remove errors at compile time that exist only because the
behaviour of the program is normally only known at runtime!
The following code will now pass compilation:
@TypeChecked
void doEmail() {
email {
from 'dsl-guru@mycompany.com'
to 'john.doe@waitaminute.com'
subject 'The pope has resigned!'
body {
p 'Really, the pope has resigned!'
}
}
}
DelegatesTo modes
@DelegatesTo
supports multiple modes that we will describe with examples
in this section.
Simple delegation
In this mode, the only mandatory parameter is the value which says to
which class we delegate calls. Nothing more. We’re telling the compiler
that the type of the delegate will always be of the type documented
by @DelegatesTo
(note that it can be a subclass, but if it is, the
methods defined by the subclass will not be visible to the type
checker).
void body(@DelegatesTo(BodySpec) Closure cl) {
// ...
}
Delegation strategy
In this mode, you must specify both the delegate class and a
delegation strategy. This must be used if the closure will not be called
with the default delegation strategy, which is Closure.OWNER_FIRST
.
void body(@DelegatesTo(strategy=Closure.DELEGATE_ONLY, value=BodySpec) Closure cl) {
// ...
}
Delegate to parameter
In this variant, we will tell the compiler that we are delegating to another parameter of the method. Take the following code:
def exec(Object target, Closure code) {
def clone = code.rehydrate(target, this, this)
clone()
}
Here, the delegate which will be used is not created inside the exec
method. In fact, we take an argument of the method and delegate to it.
Usage may look like this:
def email = new Email()
exec(email) {
from '...'
to '...'
send()
}
Each of the method calls are delegated to the email
parameter. This is
a widely used pattern which is also supported by @DelegatesTo
using a
companion annotation:
def exec(@DelegatesTo.Target Object target, @DelegatesTo Closure code) {
def clone = code.rehydrate(target, this, this)
clone()
}
A closure is annotated with @DelegatesTo
, but this time, without
specifying any class. Instead, we’re annotating another parameter
with @DelegatesTo.Target
. The type of the delegate is then determined
at compile time. One could think that we are using the parameter type,
which in this case is Object
but this is not true. Take this code:
class Greeter {
void sayHello() { println 'Hello' }
}
def greeter = new Greeter()
exec(greeter) {
sayHello()
}
Remember that this works out of the box without having to annotate
with @DelegatesTo
. However, to make the IDE aware of the delegate
type, or the type checker aware of it, we need to add @DelegatesTo
.
And in this case, it will now that the Greeter
variable is of
type Greeter
, so it will not report errors on the sayHello
method even if the exec method doesn’t explicitely define the target as
of type Greeter. This is a very powerful feature, because it prevents
you from writing multiple versions of the same exec
method for
different receiver types!
In this mode, the @DelegatesTo
annotation also supports the strategy
parameter that we’ve described upper.
Multiple closures
In the previous example, the exec
method accepted only one closure,
but you may have methods that take multiple closures:
void fooBarBaz(Closure foo, Closure bar, Closure baz) {
...
}
Then nothing prevents you from annotating each closure
with @DelegatesTo
:
class Foo { void foo(String msg) { println "Foo ${msg}!" } }
class Bar { void bar(int x) { println "Bar ${x}!" } }
class Baz { void baz(Date d) { println "Baz ${d}!" } }
void fooBarBaz(@DelegatesTo(Foo) Closure foo, @DelegatesTo(Bar) Closure bar, @DelegatesTo(Baz) Closure baz) {
...
}
But more importantly, if you have multiple closures and multiple arguments, you can use several targets:
void fooBarBaz(
@DelegatesTo.Target('foo') foo,
@DelegatesTo.Target('bar') bar,
@DelegatesTo.Target('baz') baz,
@DelegatesTo(target='foo') Closure cl1,
@DelegatesTo(target='bar') Closure cl2,
@DelegatesTo(target='baz') Closure cl3) {
cl1.rehydrate(foo, this, this).call()
cl2.rehydrate(bar, this, this).call()
cl3.rehydrate(baz, this, this).call()
}
def a = new Foo()
def b = new Bar()
def c = new Baz()
fooBarBaz(
a, b, c,
{ foo('Hello') },
{ bar(123) },
{ baz(new Date()) }
)
At this point, you may wonder why we don’t use the parameter names as references. The reason is that the information (the parameter name) is not always available (it’s a debug-only information), so it’s a limitation of the JVM. |
Delegating to a generic type
In some situations, it is interesting to instruct the IDE or the compiler that the delegate type will not be a parameter but a generic type. Imagine a configurator that runs on a list of elements:
public <T> void configure(List<T> elements, Closure configuration) {
elements.each { e->
def clone = configuration.rehydrate(e, this, this)
clone.resolveStrategy = Closure.DELEGATE_FIRST
clone.call()
}
}
Then this method can be called with any list like this:
@groovy.transform.ToString
class Realm {
String name
}
List<Realm> list = []
3.times { list << new Realm() }
configure(list) {
name = 'My Realm'
}
assert list.every { it.name == 'My Realm' }
To let the type checker and the IDE know that the configure
method calls the closure on each element of the list, you
need to use @DelegatesTo
differently:
public <T> void configure(
@DelegatesTo.Target List<T> elements,
@DelegatesTo(strategy=Closure.DELEGATE_FIRST, genericTypeIndex=0) Closure configuration) {
def clone = configuration.rehydrate(e, this, this)
clone.resolveStrategy = Closure.DELEGATE_FIRST
clone.call()
}
@DelegatesTo
takes an optional genericTypeIndex
argument that tells what is the index of the generic type that will
be used as the delegate type. This must be used in conjunction with @DelegatesTo.Target
and the index starts at 0. In
the example above, that means that the delegate type is resolved against List<T>
, and since the generic type at index
0 is T
and inferred as a Realm
, the type checker infers that the delegate type will be of type Realm
.
We’re using a genericTypeIndex instead of a placeholder (T ) because of JVM limitations.
|
4.12.6. Compilation customizers
Introduction
Whether you are using groovyc
to compile classes or a GroovyShell
,
for example, to execute scripts, under the hood, a compiler configuration is used. This configuration holds information
like the source encoding or the classpath but it can also be used to perform more operations like adding imports by
default, applying AST transformations transparently or disabling global AST transformations.
The goal of compilation customizers is to make those common tasks easy to implement. For that, the CompilerConfiguration
class is the entry point. The general schema will always be based on the following code:
import org.codehaus.groovy.control.CompilerConfiguration
// create a configuration
def config = new CompilerConfiguration()
// tweak the configuration
config.addCompilationCustomizers(...)
// run your script
def shell = new GroovyShell(config)
shell.evaluate(script)
Compilation customizers must extend the org.codehaus.groovy.control.customizers.CompilationCustomizer class. A customizer works:
-
on a specific compilation phase
-
on every class node being compiled
You can implement your own compilation customizer but Groovy includes some of the most common operations.
Import customizer
Using this compilation customizer, your code will have imports added transparently. This is in particular useful for scripts implementing a DSL where you want to avoid users from having to write imports. The import customizer will let you add all the variants of imports the Groovy language allows, that is:
-
class imports, optionally aliased
-
star imports
-
static imports, optionally aliased
-
static star imports
import org.codehaus.groovy.control.customizers.ImportCustomizer
def icz = new ImportCustomizer()
// "normal" import
icz.addImports('java.util.concurrent.atomic.AtomicInteger', 'java.util.concurrent.ConcurrentHashMap')
// "aliases" import
icz.addImport('CHM', 'java.util.concurrent.ConcurrentHashMap')
// "static" import
icz.addStaticImport('java.lang.Math', 'PI') // import static java.lang.Math.Pi
// "aliased static" import
icz.addStaticImport('pi', 'java.lang.Math', 'PI') // import static java.lang.Math.PI as pi
// "star" import
icz.addStarImports 'java.util.concurrent' // import java.util.concurrent.*
// "static star" import
icz.addStaticStars 'java.lang.Math' // import static java.lang.Math.*
A detailed description of all shortcuts can be found in org.codehaus.groovy.control.customizers.ImportCustomizer
AST transformation customizer
The AST transformation customizer is meant to apply AST transformations transparently. Unlike global AST transformations that apply on every class beeing compiled as long as the transform is found on classpath (which has drawbacks like increasing the compilation time or side effects due to transformations applied where they should not), the customizer will allow you to selectively apply a transform only for specific scripts or classes.
As an example, let’s say you want to be able to use @Log
in a script.
The problem is that @Log
is normally applied on a class node and a
script, by definition, doesn’t require one. But implementation wise,
scripts are classes, it’s just that you cannot annotate this implicit
class node with @Log
. Using the AST customizer, you have a workaround
to do it:
import org.codehaus.groovy.control.customizers.ASTTransformationCustomizer
import groovy.util.logging.Log
def acz = new ASTTransformationCustomizer(Log)
config.addCompilationCustomizers(acz)
That’s all! Internally, the @Log
AST transformation is applied to
every class node in the compilation unit. This means that it will be
applied to the script, but also to classes defined within the script.
If the AST transformation that you are using accepts parameters, you can use parameters in the constructor too:
def acz = new ASTTransformationCustomizer(Log, value: 'LOGGER')
// use name 'LOGGER' instead of the default 'log'
config.addCompilationCustomizers(acz)
As the AST transformation customizers works with objects instead of AST
nodes, not all values can be converted to AST transformation parameters.
For example, primitive types are converted to ConstantExpression
(that
is LOGGER
is converted to new ConstantExpression('LOGGER')
, but if
your AST transformation takes a closure as an argument, then you have to
give it a ClosureExpression
, like in the following example:
def configuration = new CompilerConfiguration()
def expression = new AstBuilder().buildFromCode(CompilePhase.CONVERSION) { -> true }.expression[0]
def customizer = new ASTTransformationCustomizer(ConditionalInterrupt, value: expression, thrown: SecurityException)
configuration.addCompilationCustomizers(customizer)
def shell = new GroovyShell(configuration)
shouldFail(SecurityException) {
shell.evaluate("""
// equivalent to adding @ConditionalInterrupt(value={true}, thrown: SecurityException)
class MyClass {
void doIt() { }
}
new MyClass().doIt()
""")
}
For a complete list of options, please refer to org.codehaus.groovy.control.customizers.ASTTransformationCustomizer
Secure AST customizer
This customizer will allow the developer of a DSL to restrict the grammar of the language, to prevent users from using some constructs, for example. It is only “secure” in that sense only and it is very important to understand that it does not replace a security manager. The only reason for it to exist is to limit the expressiveness of the language. This customizer only works at the AST (abstract syntax tree) level, not at runtime! It can be strange at first glance, but it makes much more sense if you think of Groovy as a platform to build DSLs. You may not want a user to have a complete language at hand. In the example below, we will demonstrate it using an example of language that only allows arithmetic operations, but this customizer allows you to:
-
allow/disallow creation of closures
-
allow/disallow imports
-
allow/disallow package definition
-
allow/disallow definition of methods
-
restrict the receivers of method calls
-
restrict the kind of AST expressions a user can use
-
restrict the tokens (grammar-wise) a user can use
-
restrict the types of the constants that can be used in code
For all those features, the secure AST customizer works using either a whitelist (list of elements that are allowed) or a blacklist (list of elements that are disallowed). For each type of feature (imports, tokens, …) you have the choice to use either a whitelist or a blacklist, but you can mix whitelists and blacklists for distinct features. In general, you will choose whitelists (disallow all, allow selected).
import org.codehaus.groovy.control.customizers.SecureASTCustomizer
import static org.codehaus.groovy.syntax.Types.* (1)
def scz = new SecureASTCustomizer()
scz.with {
closuresAllowed = false // user will not be able to write closures
methodDefinitionAllowed = false // user will not be able to define methods
importsWhitelist = [] // empty whitelist means imports are disallowed
staticImportsWhitelist = [] // same for static imports
staticStarImportsWhitelist = ['java.lang.Math'] // only java.lang.Math is allowed
// the list of tokens the user can find
// constants are defined in org.codehaus.groovy.syntax.Types
tokensWhitelist = [ (1)
PLUS,
MINUS,
MULTIPLY,
DIVIDE,
MOD,
POWER,
PLUS_PLUS,
MINUS_MINUS,
COMPARE_EQUAL,
COMPARE_NOT_EQUAL,
COMPARE_LESS_THAN,
COMPARE_LESS_THAN_EQUAL,
COMPARE_GREATER_THAN,
COMPARE_GREATER_THAN_EQUAL,
].asImmutable()
// limit the types of constants that a user can define to number types only
constantTypesClassesWhiteList = [ (2)
Integer,
Float,
Long,
Double,
BigDecimal,
Integer.TYPE,
Long.TYPE,
Float.TYPE,
Double.TYPE
].asImmutable()
// method calls are only allowed if the receiver is of one of those types
// be careful, it's not a runtime type!
receiversClassesWhiteList = [ (2)
Math,
Integer,
Float,
Double,
Long,
BigDecimal
].asImmutable()
}
1 | use for token types from org.codehaus.groovy.syntax.Types |
2 | you can use class literals here |
If what the secure AST customizer provides out of the box isn’t enough
for your needs, before creating your own compilation customizer, you
might be interested in the expression and statement checkers that the
AST customizer supports. Basically, it allows you to add custom checks
on the AST tree, on expressions (expression checkers) or statements
(statement checkers). For this, you must
implement org.codehaus.groovy.control.customizers.SecureASTCustomizer.StatementChecker
or org.codehaus.groovy.control.customizers.SecureASTCustomizer.ExpressionChecker
.
Those interfaces define a single method called isAuthorized
, returning
a boolean, and taking a Statement
(or Expression
) as a parameter. It
allows you to perform complex logic over expressions or statements to
tell if a user is allowed to do it or not.
For example, there’s no predefined configuration flag in the customizer which will let you prevent people from using an attribute expression. Using a custom checker, it is trivial:
def scz = new SecureASTCustomizer()
def checker = { expr ->
!(expr instanceof AttributeExpression)
} as SecureASTCustomizer.ExpressionChecker
scz.addExpressionCheckers(checker)
Then we can make sure that this works by evaluating a simple script:
new GroovyShell(config).evaluate '''
class A {
int val
}
def a = new A(val: 123)
a.@val (1)
'''
1 | will fail compilation |
Statements can be checked using org.codehaus.groovy.control.customizers.SecureASTCustomizer.StatementChecker
Expressions can be checked using org.codehaus.groovy.control.customizers.SecureASTCustomizer.ExpressionChecker
Source aware customizer
This customizer may be used as a filter on other customizers. The
filter, in that case, is the org.codehaus.groovy.control.SourceUnit
.
For this, the source aware customizer takes another customizer as a
delegate, and it will apply customization of that delegate only and only
if predicates on the source unit match.
SourceUnit
gives you access to multiple things but in particular the
file being compiled (if compiling from a file, of course). It gives
you the potential to perform operation based on the file name, for
example. Here is how you would create a source aware customizer:
import org.codehaus.groovy.control.customizers.SourceAwareCustomizer
import org.codehaus.groovy.control.customizers.ImportCustomizer
def delegate = new ImportCustomizer()
def sac = new SourceAwareCustomizer(delegate)
Then you can use predicates on the source aware customizer:
// the customizer will only be applied to classes contained in a file name ending with 'Bean'
sac.baseNameValidator = { baseName ->
baseName.endsWith 'Bean'
}
// the customizer will only be applied to files which extension is '.spec'
sac.extensionValidator = { ext -> ext == 'spec' }
// source unit validation
// allow compilation only if the file contains at most 1 class
sac.sourceUnitValidator = { SourceUnit sourceUnit -> sourceUnit.AST.classes.size() == 1 }
// class validation
// the customizer will only be applied to classes ending with 'Bean'
sac.classValidator = { ClassNode cn -> cn.endsWith('Bean') }
Customizer builder
If you are using compilation customizers in Groovy code (like the
examples above) then you can use an alternative syntax to customize compilation.
A builder (org.codehaus.groovy.control.customizers.builder.CompilerCustomizationBuilder
)
simplifies the creation of customizers using a hierarchical DSL.
import org.codehaus.groovy.control.CompilerConfiguration
import static org.codehaus.groovy.control.customizers.builder.CompilerCustomizationBuilder.withConfig (1)
def conf = new CompilerConfiguration()
withConfig(conf) {
// ... (2)
}
1 | static import of the builder method |
2 | configuration goes here |
The code sample above shows how to use the builder. A static method, withConfig, takes a closure corresponding to the builder code, and automatically registers compilation customizers to the configuration. Every compilation customizer available in the distribution can be configured this way:
Import customizer
withConfig(configuration) {
imports { // imports customizer
normal 'my.package.MyClass' // a normal import
alias 'AI', 'java.util.concurrent.atomic.AtomicInteger' // an aliased import
star 'java.util.concurrent' // star imports
staticMember 'java.lang.Math', 'PI' // static import
staticMember 'pi', 'java.lang.Math', 'PI' // aliased static import
}
}
AST transformation customizer
withConfig(conf) {
ast(Log) (1)
}
withConfig(conf) {
ast(Log, value: 'LOGGER') (2)
}
1 | apply @Log transparently |
2 | apply @Log with a different name for the logger |
Secure AST customizer
withConfig(conf) {
secureAst {
closuresAllowed = false
methodDefinitionAllowed = false
}
}
Source aware customizer
withConfig(configuration){
source(extension: 'sgroovy') {
ast(CompileStatic) (1)
}
}
withConfig(configuration){
source(extensions: ['sgroovy','sg']) {
ast(CompileStatic) (2)
}
}
withConfig(configuration) {
source(extensionValidator: { it.name in ['sgroovy','sg']}) {
ast(CompileStatic) (2)
}
}
withConfig(configuration) {
source(basename: 'foo') {
ast(CompileStatic) (3)
}
}
withConfig(configuration) {
source(basenames: ['foo', 'bar']) {
ast(CompileStatic) (4)
}
}
withConfig(configuration) {
source(basenameValidator: { it in ['foo', 'bar'] }) {
ast(CompileStatic) (4)
}
}
withConfig(configuration) {
source(unitValidator: { unit -> !unit.AST.classes.any { it.name == 'Baz' } }) {
ast(CompileStatic) (5)
}
}
1 | apply CompileStatic AST annotation on .sgroovy files |
2 | apply CompileStatic AST annotation on .sgroovy or .sg files |
3 | apply CompileStatic AST annotation on files whose name is foo |
4 | apply CompileStatic AST annotation on files whose name is foo or bar |
5 | apply CompileStatic AST annotation on files that do not contain a class named Baz |
Inlining a customizer
Inlined customizer allows you to write a compilation customizer directly, without having to create a class for it.
withConfig(configuration) {
inline(phase:'CONVERSION') { source, context, classNode -> (1)
println "visiting $classNode" (2)
}
}
1 | define an inlined customizer which will execute at the CONVERSION phase |
2 | prints the name of the class node being compiled |
Config script flag
So far, we have described how you can customize compilation using
a CompilationConfiguration
class, but this is only possible if you
embed Groovy and that you create your own instances
of CompilerConfiguration
(then use it to create a
GroovyShell
, GroovyScriptEngine
, …).
If you want it to be applied on the classes you compile with the normal
Groovy compiler (that is to say with groovyc
, ant
or gradle
,
for example), it is possible to use a compilation flag named configscript
that takes a Groovy configuration script as argument.
This script gives you access to the CompilerConfiguration
instance before
the files are compiled (exposed into the configuration script as a variable named configuration
),
so that you can tweak it.
It also transparently integrates the compiler configuration builder above. As an example, let’s see how you would activate static compilation by default on all classes.
Static compilation by default
Normally, classes in Groovy are compiled with a dynamic runtime. You can activate static compilation
by placing an annotation named @CompileStatic
on any class. Some people would like to have this
mode activated by default, that is to say not having to annotated classes. Using configscript
,
this is possible. First of all, you need to create a file named config.groovy
into src/conf
with
the following contents:
withConfig(configuration) { (1)
ast(groovy.transform.CompileStatic)
}
1 | configuration references a CompilerConfiguration instance |
That is actually all you need. You don’t have to import the builder, it’s automatically exposed in the script. Then, compile your files using the following command line:
groovyc -configscript src/conf/config.groovy src/main/groovy/MyClass.groovy
We strongly recommand you to separate configuration files from classes,
hence why we suggest using the src/main
and src/conf
directories above.
4.12.7. Custom type checking extensions
It may be interesting, in some circumstances, to provide feedback about wrong code to the user as soon as possible, that is to say when the DSL script is compiled, rather than having to wait for the execution of the script. However, this is not often possible with dynamic code. Groovy actually provides a practical answer to this known as type checking extensions.
4.13. Working with JMX
4.13.1. Introduction
Given that Groovy sits directly on top of Java, Groovy can leverage the tremendous amount of work already done for JMX with Java. In addition, Groovy provides a GroovyMBean
class which makes an MBean look like a normal Groovy object. This simplifies Groovy code for interacting with MBeans. For example, the following code:
println server.getAttribute(beanName, 'Age')
server.setAttribute(beanName, new Attribute('Name', 'New name'))
Object[] params = [5, 20]
String[] signature = [Integer.TYPE, Integer.TYPE]
println server.invoke(beanName, 'add', params, signature)
can be simplified to:
def mbean = new GroovyMBean(server, beanName)
println mbean.Age
mbean.Name = 'New name'
println mbean.add(5, 20)
The remainder of this page shows you how to:
-
Monitor the JVM using MXBeans
-
Monitor Apache Tomcat and display statistics
-
Monitor Oracle OC4J and display information
-
Monitor BEA WebLogic and display information
-
Leverage Spring’s MBean annotation support to export your Groovy beans as MBeans
Note: many of the examples on this page use Java 5 which incorporates JMX 1.2 (more recent versions if JMX or Java will also work). In some cases, you can run some of these examples using Java 1.4 by including a version of JMX on your CLASSPATH
. MX4J is bundled with the full distribution of Groovy. In most cases, you can delete this jar from your distribution lib
directory if you are running with Java 5 or above (in fact you might have to - see the Troubleshooting section below).
4.13.2. Monitoring the JVM
MBeans are not accessed directly by an application but are managed by a repository called an MBean server. Java 5 and above includes a special MBean server called the platform MBean server, which is built into the JVM. Platform MBeans are registered in this server using unique names.
You can monitor the JVM through its platform MBeans with the following code:
import java.lang.management.*
def os = ManagementFactory.operatingSystemMXBean
println """OPERATING SYSTEM:
\tarchitecture = $os.arch
\tname = $os.name
\tversion = $os.version
\tprocessors = $os.availableProcessors
"""
def rt = ManagementFactory.runtimeMXBean
println """RUNTIME:
\tname = $rt.name
\tspec name = $rt.specName
\tvendor = $rt.specVendor
\tspec version = $rt.specVersion
\tmanagement spec version = $rt.managementSpecVersion
"""
def cl = ManagementFactory.classLoadingMXBean
println """CLASS LOADING SYSTEM:
\tisVerbose = ${cl.isVerbose()}
\tloadedClassCount = $cl.loadedClassCount
\ttotalLoadedClassCount = $cl.totalLoadedClassCount
\tunloadedClassCount = $cl.unloadedClassCount
"""
def comp = ManagementFactory.compilationMXBean
println """COMPILATION:
\ttotalCompilationTime = $comp.totalCompilationTime
"""
def mem = ManagementFactory.memoryMXBean
def heapUsage = mem.heapMemoryUsage
def nonHeapUsage = mem.nonHeapMemoryUsage
println """MEMORY:
HEAP STORAGE:
\tcommitted = $heapUsage.committed
\tinit = $heapUsage.init
\tmax = $heapUsage.max
\tused = $heapUsage.used
NON-HEAP STORAGE:
\tcommitted = $nonHeapUsage.committed
\tinit = $nonHeapUsage.init
\tmax = $nonHeapUsage.max
\tused = $nonHeapUsage.used
"""
ManagementFactory.memoryPoolMXBeans.each { mp ->
println "\tname: " + mp.name
String[] mmnames = mp.memoryManagerNames
mmnames.each{ mmname ->
println "\t\tManager Name: $mmname"
}
println "\t\tmtype = $mp.type"
println "\t\tUsage threshold supported = " + mp.isUsageThresholdSupported()
}
println()
def td = ManagementFactory.threadMXBean
println "THREADS:"
td.allThreadIds.each { tid ->
println "\tThread name = ${td.getThreadInfo(tid).threadName}"
}
println()
println "GARBAGE COLLECTION:"
ManagementFactory.garbageCollectorMXBeans.each { gc ->
println "\tname = $gc.name"
println "\t\tcollection count = $gc.collectionCount"
println "\t\tcollection time = $gc.collectionTime"
String[] mpoolNames = gc.memoryPoolNames
mpoolNames.each { mpoolName ->
println "\t\tmpool name = $mpoolName"
}
}
When run, you will see something like this:
OPERATING SYSTEM: architecture = x86 name = Windows XP version = 5.1 processors = 2 RUNTIME: name = 620@LYREBIRD spec name = Java Virtual Machine Specification vendor = Sun Microsystems Inc. spec version = 1.0 management spec version = 1.0 CLASS LOADING SYSTEM: isVerbose = false loadedClassCount = 919 totalLoadedClassCount = 919 unloadedClassCount = 0 COMPILATION: totalCompilationTime = 91 MEMORY: HEAP STORAGE: committed = 3108864 init = 0 max = 66650112 used = 1994728 NON-HEAP STORAGE: committed = 9240576 init = 8585216 max = 100663296 used = 5897880 name: Code Cache Manager Name: CodeCacheManager mtype = Non-heap memory Usage threshold supported = true name: Eden Space Manager Name: MarkSweepCompact Manager Name: Copy mtype = Heap memory Usage threshold supported = false name: Survivor Space Manager Name: MarkSweepCompact Manager Name: Copy mtype = Heap memory Usage threshold supported = false name: Tenured Gen Manager Name: MarkSweepCompact mtype = Heap memory Usage threshold supported = true name: Perm Gen Manager Name: MarkSweepCompact mtype = Non-heap memory Usage threshold supported = true THREADS: Thread name = Monitor Ctrl-Break Thread name = Signal Dispatcher Thread name = Finalizer Thread name = Reference Handler Thread name = main GARBAGE COLLECTION: name = Copy collection count = 60 collection time = 141 mpool name = Eden Space mpool name = Survivor Space name = MarkSweepCompact collection count = 0 collection time = 0 mpool name = Eden Space mpool name = Survivor Space mpool name = Tenured Gen mpool name = Perm Gen
4.13.3. Monitoring Tomcat
First start up Tomcat with JMX monitoring enabled by setting the following:
set JAVA_OPTS=-Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.port=9004\
-Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false
You can do this in your startup script and may choose any available port, we used 9004.
The following code uses JMX to discover the available MBeans in the running Tomcat, determine which are web modules, extract the processing time for each web module and displays the result in a graph using JFreeChart:
import groovy.swing.SwingBuilder
import javax.management.ObjectName
import javax.management.remote.JMXConnectorFactory as JmxFactory
import javax.management.remote.JMXServiceURL as JmxUrl
import javax.swing.WindowConstants as WC
import org.jfree.chart.ChartFactory
import org.jfree.data.category.DefaultCategoryDataset as Dataset
import org.jfree.chart.plot.PlotOrientation as Orientation
def serverUrl = 'service:jmx:rmi:///jndi/rmi://localhost:9004/jmxrmi'
def server = JmxFactory.connect(new JmxUrl(serverUrl)).MBeanServerConnection
def serverInfo = new GroovyMBean(server, 'Catalina:type=Server').serverInfo
println "Connected to: $serverInfo"
def query = new ObjectName('Catalina:*')
String[] allNames = server.queryNames(query, null)
def modules = allNames.findAll { name ->
name.contains('j2eeType=WebModule')
}.collect{ new GroovyMBean(server, it) }
println "Found ${modules.size()} web modules. Processing ..."
def dataset = new Dataset()
modules.each { m ->
println m.name()
dataset.addValue m.processingTime, 0, m.path
}
def labels = ['Time per Module', 'Module', 'Time']
def options = [false, true, true]
def chart = ChartFactory.createBarChart(*labels, dataset,
Orientation.VERTICAL, *options)
def swing = new SwingBuilder()
def frame = swing.frame(title:'Catalina Module Processing Time', defaultCloseOperation:WC.EXIT_ON_CLOSE) {
panel(id:'canvas') { rigidArea(width:600, height:250) }
}
frame.pack()
frame.show()
chart.draw(swing.canvas.graphics, swing.canvas.bounds)
When run, we will see a trace of progress being made:
Connected to: Apache Tomcat/6.0.13 Found 5 web modules. Processing ... Catalina:j2eeType=WebModule,name=//localhost/,J2EEApplication=none,J2EEServer=none Catalina:j2eeType=WebModule,name=//localhost/host-manager,J2EEApplication=none,J2EEServer=none Catalina:j2eeType=WebModule,name=//localhost/docs,J2EEApplication=none,J2EEServer=none Catalina:j2eeType=WebModule,name=//localhost/examples,J2EEApplication=none,J2EEServer=none Catalina:j2eeType=WebModule,name=//localhost/manager,J2EEApplication=none,J2EEServer=none
The output will look like this:
Note: if you get errors running this script, see the Troubleshooting section below.
4.13.4. OC4J Example
Here is a script to access OC4J and print out some information about the server, its runtime and (as an example) the configured JMS destinations:
import javax.management.remote.*
import oracle.oc4j.admin.jmx.remote.api.JMXConnectorConstant
def serverUrl = new JMXServiceURL('service:jmx:rmi://localhost:23791')
def serverPath = 'oc4j:j2eeType=J2EEServer,name=standalone'
def jvmPath = 'oc4j:j2eeType=JVM,name=single,J2EEServer=standalone'
def provider = 'oracle.oc4j.admin.jmx.remote'
def credentials = [
(JMXConnectorConstant.CREDENTIALS_LOGIN_KEY): 'oc4jadmin',
(JMXConnectorConstant.CREDENTIALS_PASSWORD_KEY): 'admin'
]
def env = [
(JMXConnectorFactory.PROTOCOL_PROVIDER_PACKAGES): provider,
(JMXConnector.CREDENTIALS): credentials
]
def server = JmxFactory.connect(serverUrl, env).MBeanServerConnection
def serverInfo = new GroovyMBean(server, serverPath)
def jvmInfo = new GroovyMBean(server, jvmPath)
println """Connected to $serverInfo.node. \
Server started ${new Date(serverInfo.startTime)}.
OC4J version: $serverInfo.serverVersion from $serverInfo.serverVendor
JVM version: $jvmInfo.javaVersion from $jvmInfo.javaVendor
Memory usage: $jvmInfo.freeMemory bytes free, \
$jvmInfo.totalMemory bytes total
"""
def query = new javax.management.ObjectName('oc4j:*')
String[] allNames = server.queryNames(query, null)
def dests = allNames.findAll { name ->
name.contains('j2eeType=JMSDestinationResource')
}.collect { new GroovyMBean(server, it) }
println "Found ${dests.size()} JMS destinations. Listing ..."
dests.each { d -> println "$d.name: $d.location" }
Here is the result of running this script:
Connected to LYREBIRD. Server started Thu May 31 21:04:54 EST 2007. OC4J version: 11.1.1.0.0 from Oracle Corp. JVM version: 1.6.0_01 from Sun Microsystems Inc. Memory usage: 8709976 bytes free, 25153536 bytes total Found 5 JMS destinations. Listing ... Demo Queue: jms/demoQueue Demo Topic: jms/demoTopic jms/Oc4jJmsExceptionQueue: jms/Oc4jJmsExceptionQueue jms/RAExceptionQueue: jms/RAExceptionQueue OracleASRouter_store: OracleASRouter_store
As a slight variation, this script displays a pie chart of memory usage using JFreeChart:
import org.jfree.chart.ChartFactory
import javax.swing.WindowConstants as WC
import javax.management.remote.*
import oracle.oc4j.admin.jmx.remote.api.JMXConnectorConstant
def url = 'service:jmx:rmi://localhost:23791'
def credentials = [:]
credentials[JMXConnectorConstant.CREDENTIALS_LOGIN_KEY] = "oc4jadmin"
credentials[JMXConnectorConstant.CREDENTIALS_PASSWORD_KEY] = "password"
def env = [:]
env[JMXConnectorFactory.PROTOCOL_PROVIDER_PACKAGES] = "oracle.oc4j.admin.jmx.remote"
env[JMXConnector.CREDENTIALS] = credentials
def server = JMXConnectorFactory.connect(new JMXServiceURL(url), env).MBeanServerConnection
def jvmInfo = new GroovyMBean(server, 'oc4j:j2eeType=JVM,name=single,J2EEServer=standalone')
def piedata = new org.jfree.data.general.DefaultPieDataset()
piedata.setValue "Free", jvmInfo.freeMemory
piedata.setValue "Used", jvmInfo.totalMemory - jvmInfo.freeMemory
def options = [true, true, true]
def chart = ChartFactory.createPieChart('OC4J Memory Usage', piedata, *options)
chart.backgroundPaint = java.awt.Color.white
def swing = new groovy.swing.SwingBuilder()
def frame = swing.frame(title:'OC4J Memory Usage', defaultCloseOperation:WC.EXIT_ON_CLOSE) {
panel(id:'canvas') { rigidArea(width:350, height:250) }
}
frame.pack()
frame.show()
chart.draw(swing.canvas.graphics, swing.canvas.bounds)
Which looks like:
4.13.5. WebLogic Example
This script prints out information about the server followed by information about JMS Destinations (as an example). Many other mbeans are available.
import javax.management.remote.*
import javax.management.*
import javax.naming.Context
def urlRuntime = '/jndi/weblogic.management.mbeanservers.runtime'
def urlBase = 'service:jmx:t3://localhost:7001'
def serviceURL = new JMXServiceURL(urlBase + urlRuntime)
def h = new Hashtable()
h.put(Context.SECURITY_PRINCIPAL, 'weblogic')
h.put(Context.SECURITY_CREDENTIALS, 'weblogic')
h.put(JMXConnectorFactory.PROTOCOL_PROVIDER_PACKAGES, 'weblogic.management.remote')
def server = JMXConnectorFactory.connect(serviceURL, h).MBeanServerConnection
def domainName = new ObjectName('com.bea:Name=RuntimeService,Type=weblogic.management.mbeanservers.runtime.RuntimeServiceMBean')
def rtName = server.getAttribute(domainName, 'ServerRuntime')
def rt = new GroovyMBean(server, rtName)
println "Server: name=$rt.Name, state=$rt.State, version=$rt.WeblogicVersion"
def destFilter = Query.match(Query.attr('Type'), Query.value('JMSDestinationRuntime'))
server.queryNames(new ObjectName('com.bea:*'), destFilter).each { name ->
def jms = new GroovyMBean(server, name)
println "JMS Destination: name=$jms.Name, type=$jms.DestinationType, messages=$jms.MessagesReceivedCount"
}
Here is the output:
Server: name=examplesServer, state=RUNNING, version=WebLogic Server 10.0 Wed May 9 18:10:27 EDT 2007 933139 JMS Destination: name=examples-jms!exampleTopic, type=Topic, messages=0 JMS Destination: name=examples-jms!exampleQueue, type=Queue, messages=0 JMS Destination: name=examples-jms!jms/MULTIDATASOURCE_MDB_QUEUE, type=Queue, messages=0 JMS Destination: name=examplesJMSServer!examplesJMSServer.TemporaryQueue0, type=Queue, messages=68 JMS Destination: name=examples-jms!quotes, type=Topic, messages=0 JMS Destination: name=examples-jms!weblogic.wsee.wseeExamplesDestinationQueue, type=Queue, messages=0 JMS Destination: name=examples-jms!weblogic.examples.ejb30.ExampleQueue, type=Queue, messages=0
4.13.6. Spring Example
You can also use Spring to automatically register beans as JMX aware.
Here is an example class (Calculator.groovy):
import org.springframework.jmx.export.annotation.*
@ManagedResource(objectName="bean:name=calcMBean", description="Calculator MBean")
public class Calculator {
private int invocations
@ManagedAttribute(description="The Invocation Attribute")
public int getInvocations() {
return invocations
}
private int base = 10
@ManagedAttribute(description="The Base to use when adding strings")
public int getBase() {
return base
}
@ManagedAttribute(description="The Base to use when adding strings")
public void setBase(int base) {
this.base = base
}
@ManagedOperation(description="Add two numbers")
@ManagedOperationParameters([
@ManagedOperationParameter(name="x", description="The first number"),
@ManagedOperationParameter(name="y", description="The second number")])
public int add(int x, int y) {
invocations++
return x + y
}
@ManagedOperation(description="Add two strings representing numbers of a particular base")
@ManagedOperationParameters([
@ManagedOperationParameter(name="x", description="The first number"),
@ManagedOperationParameter(name="y", description="The second number")])
public String addStrings(String x, String y) {
invocations++
def result = Integer.valueOf(x, base) + Integer.valueOf(y, base)
return Integer.toString(result, base)
}
}
Here is the Spring configuration file (beans.xml):
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="
http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd">
<bean id="mbeanServer"
class="org.springframework.jmx.support.MBeanServerFactoryBean">
<property name="locateExistingServerIfPossible" value="true"/>
</bean>
<bean id="exporter"
class="org.springframework.jmx.export.MBeanExporter">
<property name="assembler" ref="assembler"/>
<property name="namingStrategy" ref="namingStrategy"/>
<property name="beans">
<map>
<entry key="bean:name=defaultCalcName" value-ref="calcBean"/>
</map>
</property>
<property name="server" ref="mbeanServer"/>
<property name="autodetect" value="true"/>
</bean>
<bean id="jmxAttributeSource"
class="org.springframework.jmx.export.annotation.AnnotationJmxAttributeSource"/>
<!-- will create management interface using annotation metadata -->
<bean id="assembler"
class="org.springframework.jmx.export.assembler.MetadataMBeanInfoAssembler">
<property name="attributeSource" ref="jmxAttributeSource"/>
</bean>
<!-- will pick up the ObjectName from the annotation -->
<bean id="namingStrategy"
class="org.springframework.jmx.export.naming.MetadataNamingStrategy">
<property name="attributeSource" ref="jmxAttributeSource"/>
</bean>
<bean id="calcBean"
class="Calculator">
<property name="base" value="10"/>
</bean>
</beans>
Here is a script which uses this bean and configuration:
import org.springframework.context.support.ClassPathXmlApplicationContext
import java.lang.management.ManagementFactory
import javax.management.ObjectName
import javax.management.Attribute
// get normal bean
def ctx = new ClassPathXmlApplicationContext("beans.xml")
def calc = ctx.getBean("calcBean")
Thread.start {
// access bean via JMX, use a separate thread just to
// show that we could access remotely if we wanted
def server = ManagementFactory.platformMBeanServer
def mbean = new GroovyMBean(server, 'bean:name=calcMBean')
sleep 1000
assert 8 == mbean.add(7, 1)
mbean.Base = 8
assert '10' == mbean.addStrings('7', '1')
mbean.Base = 16
sleep 2000
println "Number of invocations: $mbean.Invocations"
println mbean
}
assert 15 == calc.add(9, 6)
assert '11' == calc.addStrings('10', '1')
sleep 2000
assert '20' == calc.addStrings('1f', '1')
And here is the resulting output:
Number of invocations: 5 MBean Name: bean:name=calcMBean Attributes: (rw) int Base (r) int Invocations Operations: int add(int x, int y) java.lang.String addStrings(java.lang.String x, java.lang.String y) int getInvocations() int getBase() void setBase(int p1)
You can even attach to the process while it is running with jconsole. It will look something like:
We started the Groovy application with the -Dcom.sun.management.jmxremote
JVM argument using a Java 5 JVM.
See also:
4.13.7. Troubleshooting
groovy.lang.MissingMethodException or groovy.lang.GroovyRuntimeException
If you get an error like this:
groovy.lang.MissingMethodException: No signature of method: javax.management.remote.rmi.RMIConnector$RemoteMBeanServerConnection.queryMBeans() is applicable for argument types: (javax.management.ObjectName, null) values: {Catalina:*, null}
or like this:
Caught: groovy.lang.GroovyRuntimeException: Could not find matching constructor for: groovy.util.GroovyMBean(javax.management.remote.rmi.RMIConnector$RemoteMBeanServerConnection, java.lang.String)
you have to move away or delete "mx4j-*.jar" from $GROOVY_HOME/lib
. MX4J is designed to add javax.management
classes to 1.4 JVMs. If you already have a newer JMX jar on your classpath or are using a Java 5 or higher JVM, the MX4J classes will be incompatible with the ones from the newer Sun JVMs or newer versions of JMX.
java.lang.SecurityException
If you get the following error, your container’s JMX access is password protected:
java.lang.SecurityException: Authentication failed! Credentials required
To fix that, add an environment with the credentials when connecting, like this (password has to be set before that):
def jmxEnv = null
if (password != null) {
jmxEnv = [(JMXConnector.CREDENTIALS): (String[])["monitor", password]]
}
def connector = JMXConnectorFactory.connect(new JMXServiceURL(serverUrl), jmxEnv)
Details for the software you are trying to monitor/manage may differ slightly. Check out the other examples using credentials above if appropriate (e.g. OC4J and WebLogic). If you still have troubles, you will have to consult the documentation for the software you are trying to monitor/manage for details on how to provide credentials.
4.13.8. JmxBuilder
JmxBuilder is a Groovy-based domain specific language for the Java Management Extension (JMX) API. It uses the builder pattern (FactoryBuilder) to create an internal DSL that facilitates the exposure of POJO’s and Groovy beans as management components via the MBean server. JmxBuilder hides the complexity of creating and exporting management beans via the JMX API and provides a set of natural Groovy constructs to interact with the JMX infrastructure.
Instantiating JmxBuilder
To start using JmxBuilder, simply make sure the jar file is on your class path. Then you can do the following in your code:
def jmx = new JmxBuilder()
That’s it! You are now ready to use the JmxBuilder.
NOTE
-
You can pass in an instance of your own MBeanServer to the builder (JmxBuilder(MBeanServer))
-
If no MBeanServer is specified, the builder instance will default to the underlying platform MBeanServer.
Once you have an instance of JmxBuilder, you are now ready to invoke any of its builder nodes.
JMX Connectors
Remote connectivity is a crucial part of the JMX architecture. JmxBuilder facilitates the creation of connector servers and connector clients with nimimal amount of coding.
Connector Server
JmxBuilder.connectoServer() supports the full Connector api syntax and will let you specify properties, override the URL, specify your own host, etc.
Syntax
jmx.connectorServer( protocol:"rmi", host:"...", port:1099, url:"...", properties:[ "authenticate":true|false, "passwordFile":"...", "accessFile":"...", "sslEnabled" : true | false // any valid connector property ] )
Note that the serverConnector node will accept four ServerConnector property aliases (authenticate, passwordFile,accessFile, and sslEnabled). You can use these aliases or provided any of the RMI-supported properties.
Example - Connector Server (see correction below)
jmx.connectorServer(port: 9000).start()
The snippet above returns an RMI connector that will start listening on port 9000. By default, the builder will internally generate URL "service:jmx:rmi:///jndi/rmi://localhost:9000/jmxrmi".
NOTE: Sadly you are as likely to get something like the following when attempting to run the previous snippet of code (example is incomplete, see below):
Caught: java.io.IOException: Cannot bind to URL [rmi://localhost:9000/jmxrmi]: javax.naming.ServiceUnavailableException [Root exception is java.rmi.ConnectException: Connection refused to host: localhost; nested exception is: ?????? java.net.ConnectException: Connection refused] ??
This occurs on Mac and Linux (CentOS 5) with Groovy 1.6 installed. Perhaps there were assumptions made about the configuration of the /etc/hosts file?
The correct example is shown below. |
Connector Example (Corrected) - Connector Server
The example above does not create the RMI registry. So, in order to export, you have to first export the RMI object registry (make sure to import java.rmi.registry.LocateRegistry
).
import java.rmi.registry.LocateRegistry
//...
LocateRegistry.createRegistry(9000)
jmx.connectorServer(port: 9000).start()
Connector Client
JmxBuilder.connectorClient() node lets you create JMX connector client object to connect to a JMX MBean Server.
Syntax
jmx.connectorClient ( protocol:"rmi", host:"...", port:1099, url:"...", )
Example - Client Connector
Creating a connector client can be done just as easily. With one line of code, you can create an instance of a JMX Connector Client as shown below.
def client = jmx.connectorClient(port: 9000)
client.connect()
You can then access the MBeanServerConnection associated with the connector using:
client.getMBeanServerConnection()
JmxBuilder MBean Export
You can export a Java object or a Groovy object with minimal coding. JmxBuilder will even find and export dynamic Groovy methods injected at runtime.
Implicit vs Explicit Descriptors
When using the builder, you can let JmxBuilder implicitly generate all of your MBean descriptor info. This is useful when you want to write minimal code to quickly export your beans. You can also explicitly declare all descriptor info for the bean. This gives you total control on how you want to describe every piece of information that you want to export for the underlying bean.
The JmxBuilder.export() Node
The JmxBuilder.export() node provides a container where all management entities to be exported to the MBeanServer are placed. You can place one or more bean() or timer() nodes as children of the export() node. JmxBuilder will automatically batch export the entities described by the nodes to the MBean server for management (see example below).
def beans = jmx.export {
bean(new Foo())
bean(new Bar())
bean(new SomeBar())
}
In the code snippet above, JmxBuilder.export() will export three management beans to the MBean server.
JmxBuilder.export() Syntax
JmxBuilder.export() node supports the registrationPolicy parameter to specify how JmxBuilder will behave to resolve bean name collision during MBean registration:
jmx.export(policy:"replace|ignore|error") or jmx.export(regPolicy:"replace|ignore|error")
-
replace - JmxBuilder.export() will replance any bean already registered with the MBean during export.
-
ignore - The bean being exported will be ignored if the same bean is already registered.
-
error - JmxBuilder.export() throws an error upon bean name collision during registration.
Integration with GroovyMBean Class
When you export an MBean to the MBeanServer, JmxBuilder will return an instance of GroovyMBean representing the management bean that have been exported by the builder. Nodes such as bean() and timer() will return an instances of GroovyMBean when they are invoked. The export() node returns an array of all of GroovyMBean[] representing all managed objects exported to the MBean server.
MBean Registration with JmxBuilder.bean()
This portion of this reference uses class RequestController to illustrate how to use JmxBuilder to export runtime management beans. The class is for illustration purpose and can be a POJO or a Groovy bean.
RequestController
class RequestController {
// constructors
RequestController() { super() }
RequestController(Map resource) { }
// attributes
boolean isStarted() { true }
int getRequestCount() { 0 }
int getResourceCount() { 0 }
void setRequestLimit(int limit) { }
int getRequestLimit() { 0 }
// operations
void start() { }
void stop() { }
void putResource(String name, Object resource) { }
void makeRequest(String res) { }
void makeRequest() { }
}
As mentioned earlier, you can use JmxBuilder’s flexible syntax to export any POJO/POGO with no descriptor. The builder can automatically describe all aspects of the management beans using implicit defaults. These default values can easily be overridden as we’ll see in this in the next section.
The simplest way to export a POJO or POGO is listed below.
jmx.export {
bean(new RequestController(resource: "Hello World"))
}
What this does:
-
First, the JmxBuilder.export() node will export an MBean to the MBeanServer representing the declared POJO instance.
-
The builder will generate a default ObjectName for the MBean and all other MBean descriptor information.
-
JmxBuilder will automatically export all declared attributes (MBean getter/setters), constructors, and operations on the instance.
-
The exported attributes will have read-only visibility.
Remember, JmxBuilder.export() returns an array of GroovyMBean[] objects for all exported instances. So, once you call JmxBuilder.export(), you have immediate access to the underlying MBean proxy (via GroovyMBean).
JmxBuilder.bean() Syntax
The JmxBuilder.bean() node supports an extensive set of descriptors to describe your bean for management. The JMX MBeanServer uses these descriptors to expose meta data about the bean exposed for management.
jmx.export { bean( target:bean instance, name:ObjectName, desc:"...", attributes:"*", attributes:[] attributes:[ "AttrubuteName1","AttributeName2",...,"AttributeName_n" ] attributes:[ "AttributeName":"*", "AttributeName":[ desc:"...", defaultValue:value, writable:true|false, editable:true|false, onChange:{event-> // event handler} ] ], constructors:"*", constructors:[ "Constructor Name":[], "Constructor Name":[ "ParamType1","ParamType2,...,ParamType_n" ], "Constructor Name":[ desc:"...", params:[ "ParamType1":"*", "ParamType2":[desc:"...", name:"..."],..., "ParamType_n":[desc:"...", name:"..."] ] ] ], operations:"*", operations:[ "OperationName1", "OperationName2",...,"OperationNameN" ], operations:[ "OperationName1":"*", "OperationName2":[ "type1","type2,"type3" ] "OperationName3":[ desc:"...", params:[ "ParamType1":"*" "ParamType2":[desc:"...", name:"..."],..., "ParamType_n":[desc:"...", name:"..."] ], onInvoked:{event-> JmxBuilder.send(event:"", to:"")} ] ], listeners:[ "ListenerName1":[event: "...", from:ObjectName, call:{event->}], "ListenerName2":[event: "...", from:ObjectName, call:&methodPointer] ] ) }
Instead of describing the entire node, the following section explore each attribute separately.
Bean() Node - Specifying MBean ObjectName
Using the bean() node descriptors, you can specify your own MBean ObjectName.
def ctrl = new RequestController(resource:"Hello World")
def beans = jmx.export {
bean(target: ctrl, name: "jmx.tutorial:type=Object")
}
The ObjectName can be specified as a String or an instance of the ObjectName.
Bean() Node - Attribute Export
JMX attributes are the setters and getters on the underlying bean. The JmxBuilder.bean() node provides several ways to flexibly describe and export MBean attributes. You can combine them however you want to achieve any level of attribute visibility. Let’s take a look.
Export All Attributes with Wildcard "*"
The following code snippet will describe and export all attributes on the bean as read-only. JmxBuilder will use default values to describe the attributes that exported for management.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(target: new RequestController(),
name: objName,
attributes: "*")
}
Export Attribute List
JmxBuilder will let you specify a list of attributes to export.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
attributes: ["Resource", "RequestCount"]
)
}
In the snippet above, only the "Resource" and "RequestCount" attributes will be exported. Again, since no descriptors are provided, JmxBuilder will use sensible defaults to describe the exported attributes.
Export Attribute with Explicit Descriptors
One of the strengths of JmxBuilder is its flexibility in describing MBean. With the builder you can describe all aspects of the MBeans attribute that you want to export to the MBeanServer (see syntax above).
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
attributes: [
"Resource": [desc: "The resource to request.", readable: true, writable: true, defaultValue: "Hello"],
"RequestCount": "*"
]
)
}
In the snippet above, attribute "Resource" is fully-described using all supported descriptors (i.e. desc, readable, writable, defaultValue) for a JMX attribute. However, we use the wildcard to describe attribute RequestCount and it will be exported and described using defaults.
Bean() Node - Constructor Export
JmxBuilder supports the explicit description and export of constructors defined in the underlying bean. There are several options available when exporting constructors. You can combine them however you want to achieve the desired level of manageability.
Export all Constructors with "*"
You can use the builder’s special "" notation to *export all constructors declared on the underlying bean. The builder will use default values to describe the MBean constructors.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
constructors: "*"
)
}
Export Constructors using Parameter Descriptor
JmxBuilder lets you target specific constructor to export by describing the parameter signature. This is useful when you have several constructors with different parameter signature and you want to export specific constructors.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
constructors: [
"RequestController": ["Object"]
]
)
}
Here, JmxBuilder will export a constructor that takes one parameter of type "Object". Again, JmxBuilder will use default values to fill in the description of the constructor and the parameters.
Export Constructor with Explicit Descriptors
JmxBuilder allows you to fully-describe the constructor that you want to target for export (see syntax above).
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(target: new RequestController(), name: objName,
constructors: [
"RequestController": [
desc: "Constructor takes param",
params: ["Object" : [name: "Resource", desc: "Resource for controller"]]
]
]
)
}
In the code above, JmxBuilder will target a constructor that takes one parameter for export to the MBeanServer. Notice how the constructor can be fully-described using all optional descriptor keys including parameter descriptors.
Bean() Node - Operation Export
Similar to constructors, JmxBuilder supports the description and export of MBean operations using a flexible notation (see above for syntax). You can combine these notations however you want to achieve the level of operation manageability desired.
Export All Operations with "*"
You can use the builder’s special ""' notation to *export all operations defined on the bean to be exposed for management. The builder will use default descriptor values for the operations being exported.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
operations: "*"
)
}
In this snippet, JmxBuilder will export all bean operations and will use default values to describe them in the MBeanServer.
Export Operation List
JmxBuilder has a shorthand notation that lets you quickly target operations to be exported by providing a list of methods to export.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
operations: ["start", "stop"]
)
}
In the snippet above, the builder will only export methods start() and stop(). All other methods will be ignored. JmxBuilder will use default descriptor values to describe the operations being exported.
Export Operations by Signature
Using JmxBuilder, you can target methods to export for management using the methods’s parameter signature. This is useful when you want to distinguish methods with the same name that you want to export (i.e. stop() instead of stop(boolean)).
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(
target: new RequestController(),
name: objName,
operations: [
"makeRequest": ["String"]
]
)
}
In the snipet above, JmxBuilder would select method makeRequest(String) to be exported instead of the other version makeRequest() which takes no parameter. In this shorthand context, the signature is specified as a list of type (i.e. "String").
Export Operations with Explicit Descriptors
JmxBuilder supports detailed descriptors for bean operations. You can supply deep descriptor info about any operation on your bean including a name, description, method parameters, parameter type, and parameter description.
def objName = new ObjectName("jmx.tutorial:type=Object")
def beans = jmx.export {
bean(target: new RequestController(), name: objName,
operations: [
"start": [desc: "Starts request controller"],
"stop": [desc: "Stops the request controller"],
"setResource": [params: ["Object"]],
"makeRequest": [
desc: "Executes the request.",
params: [
"String": [name: "Resource", desc: "The resource to request"]
]
]
]
)
}
The snippet above shows all of the ways JmxBuilder allows you to describe an operation targeted for management:
-
Operations start() and stop() are described by the "desc" key (this is enough since there are no params).
-
In operation setResource() uses of a shorthand version of params: to describe the parameters for the method.
-
makeRequest() uses the the extended descriptor syntax to describe all aspects of the operation.
Embedding Descriptor
JmxBuilder supports the ability to embed descriptors directly in your Groovy class. So, instead of wrapping your description around the declared object (as we’ve seen here), you can ebmed your JMX descriptors directly in your class.
RequestControllerGroovy
class RequestControllerGroovy {
// attributes
boolean started
int requestCount
int resourceCount
int requestLimit
Map resources
// operations
void start() { }
void stop(){ }
void putResource(String name, Object resource) { }
void makeRequest(String res) { }
void makeRequest() { }
static descriptor = [
name: "jmx.builder:type=EmbeddedObject",
operations: ["start", "stop", "putResource"],
attributes: "*"
]
}
// export
jmx.export(
bean(new RequestControllerGroovy())
)
There are two things going on in the code above:
-
Groovy class RequestControllerGroovy is defined and includes a static descriptor member. That member is used to declare a JmxBuilder descriptor to describe member of the class targeted for JMX export.
-
The second part of the code shows how to use JmxBuilder to export that class for management.
Timer Export
JMX standards mandate that the implementation of the API makes available a timer service. Since JMX is a component-based architecture, timers provide an excellent signaling mechanism to communicate to registered listener components in the MBeanServer. JmxBuilder supports the creation and export of timers using the same easy syntax we’ve seen so far.
Timer Node Syntax
timer( name:ObjectName, event:"...", message:"...", data:dataValue startDate:"now"|dateValue period:"99d"|"99h"|"99m"|"99s"|99 occurences:long )
The timer() node supports several attributes:
-
name: - Required The qualified JMX ObjectName instance (or String) for the timer.
-
event: - The JMX event type string that will be broadcast with every timing signal (default "jmx.builder.event").
-
message: - An optional string value that can be sent to listneners.
-
data: - An optional object that can be sent to listeners of timing signal.
-
startDate: - When to start timer. Set of valid values [ "now", date object ]. Default is "now"
-
period: - A timer’s period expressed as either a number of millisecond or time unit (day, hour, minute, second). See description below.
-
occurences: - A number indicating the number of time to repeat timer. Default is forever.
Exporting a Timer
def timer = jmx.timer(name: "jmx.builder:type=Timer", event: "heartbeat", period: "1s")
timer.start()
This snippet above describes, creates, and exports a standard JMX Timer component. Here, the timer() node returns a GroovyMBean that represents the registered timer MBean in the MBeanServer.
An alternative way of exporting timers is within the JmxBuilder.export() node.
def beans = jmx.export {
timer(name: "jmx.builder:type=Timer1", event: "event.signal", period: "1s")
timer(name: "jmx.builder:type=Timer2", event: "event.log", period: "1s")
}
beans[0].start()
beans[1].start()
Timer Period
The timer() node supports a flexible notation for specifying the timer period values. You can specify the time in second, minutes, hour, and day. The default is millisecond.
-
timer(period: 100) = 100 millisecond
-
timer(period: "1s") = 1 second
-
timer(period: "1m") = 1 minute
-
timer(period: "1h") = 1 hour
-
timer(period: "1d") = 1 day
The node will automatically translate.
JmxBuilder and Events
An integral part of JMX is its event model. Registered management beans can communicate with each other by broadcasting events on the MBeanServer’s event bus. JmxBuilder provides several ways to easily listen and react to events broadcasted on the MBeanServer’s event bus. Developers can capture any event on the bus or throw their own to be consumed by other components registered on the MBeanServer.
Event Handling Closures
JmxBuilder leverages Groovy’s use of closures to provide simple, yet elegant, mean of reacting to JMX events. JmxBuilder supports two closure signatures:
callback = { ->
// event handling code here.
}
JmxBuilder executes the closure and passes no information about the event that was captured on the bus.
callback = { event ->
// event handling code
}
JmxBuilder will pass an "event" object to the closure using this format. The event object contains information about the event was intercepted so that it can be handled by the handler. The parameter will contain different set of info depending on the event that was captured.
Handling Attribute onChange Event
When describing attributes (see bean() node section above), you can provide a closure (or method pointer) for callback to be executed when the value of the attribute is updated on the exported MBean. This gives developers an opportunity to listen to and react to state changes on the MBean.
jmx.export {
bean(
target: new RequestController(), name: "jmx.tutorial:type=Object",
attributes: [
"Resource": [
readable: true, writable: true,
onChange: { e ->
println e.oldValue
println e.newValue
}
]
]
)
}
The sample snippet above shows how to specify an "onChange" callback closure when describing MBean attributes. In this sample code, whenever attribute "Resource" is updated via the exported MBean, the onChange event will be executed.
Attribute onChange Event Object
When handling the attribute onChange event, the handler closure will receive an event object with the following info:
-
event.oldValue - the previous attribute value before the change event.
-
event.newValue - the new value of the attribute after the change.
-
event.attribute - the name of the attribute on which the event occured.
-
event.attributeType - the data type of the attribute that causes the event.
-
event.sequenceNumber - a numeric value representing the sequence number of event.
-
event.timeStamp - a time stamp for the event occurence.
Handling Operation onCall Event
Similar to mbean attributes, JmxBuilder affords developers the ability to listen for operation invokation on an MBean registered in the MBeaServer. JmxBuilder accepts a callback closure that will be executed after the MBean method has invoked.
class EventHandler {
void handleStart(e){
println e
}
}
def handler = new EventHandler()
def beans = jmx.export {
bean(target: new RequestController(), name: "jmx.tutorial:type=Object",
operations: [
"start": [
desc:"Starts request controller",
onCall:handler.&handleStart
]
]
)
}
The snippet above shows how to declare an "onCall" closure to be used as listener when operation "start()" is invoked on the MBean. This sample uses the method pointer syntax to illustrate the versatility of JmxBuilder.
Operation onCall Event Object
When handling the operation onCall event, the callback closure will receive an event object with the following info:
-
event.event - the event type string that was broadcasted.
-
event.source - The object on which the method was invoked.
-
event.data - the data type of the attribute that causes the event.
-
event.sequenceNumber - a numeric value representing the sequence number of event.
-
event.timeStamp - a time stamp for the event occurence.
Listener MBean
When you export an MBean with the bean() node, you can define events the MBean can listen and react to. The bean() node provides a "listeners:" attribute that lets you define event listeners that your bean can react to.
def beans = jmx.export {
timer(name: "jmx.builder:type=Timer", event: "heartbeat", period: "1s").start()
bean(target: new RequestController(), name: "jmx.tutorial:type=Object",
operations: "*",
listeners: [
heartbeat: [
from: "jmx.builder:type=Timer",
call: { e ->
println e
}
]
]
)
}
In the sample above, we see the syntax for adding listeners to an exported MBean.
-
Fist, a timer is exported and started.
-
Then an MBean is declared that will listen to the timer event and do something meaningful.
-
The "heartbeat:" name is arbitrary and has no correlation to the timer declared above.
-
The source of the event is specified using the "from:" attribute.
You can also specify an event type you are interested in receiving from a broadcaster (since a broadcaster can be emitting multiple events).
Listening to JMX Events
In some cases, you will want to create stand-alone event listensers (not attached to exported MBeans). JmxBuilder provides the Listener() node to let you create JMX listeners that can listen to MBeanServer events. This is useful when creating JMX client applications to monitor/manage JMX agents on remote JMX MBeanServers.
Listener Node Syntax
jmx.listener( event: "...", from: "object name" | ObjectName, call: { event-> } )
Here is the description of the lisetener() node attributes:
-
event: An optional string that identifies the JMX event type to listen for.
-
from (required): The JMX ObjectName of the component to listen to. This can be specified as a string or an instance of ObjectName
-
call: The closure to execute when the event is captured. This can also be specified as a Groovy method pointer.
Here is an example of JmxBuilder’s listener node:
jmx.timer(name: "jmx.builder:type=Timer", period: "1s").start()
jmx.listener(
from: "jmx.builder:type=Timer",
call: { e ->
println "beep..."
}
)
This example shows how you can use a stand alone listener (outside of an MBean export). Here, we export a timer with a 1 second resolution. Then, we specify a listener to that timer that will print "beep" every second.
Emitting JMX Events
JmxBuilder provides the tools needed to broadcast your own events on the MBeanServer’s event bus. There are no restrictions on the event type you can broadcast. You simply declare your emitter and the event type that you want to send, then broadcast your event at any time. Any registered component in the MBeanServer can register themselves to listen to your events.
Emitter Syntax
jmx.emitter(name:"Object:Name", event:"type")
The attributes for the node Emitter() can be summarized as follows:
-
name: an optional JMX ObjectName used to register your emitter in the MBeanServer. Default is jmx.builder:type=Emitter,name=Emitter@OBJECT_HASH_VALUE
-
event: an option string value that describes the JMX event type. Default is "jmx.builder.event.emitter".
Declare the Emitter
def emitter = jmx.emitter()
The snippet declares the emitter using implicit descriptor syntax. JmxBuilder will do the followings:
-
Create and register an emitter MBean with a default ObjectName.
-
Setup a default event type with value "jmx.builder.event.emitter".
-
Return a GroovyMBean representing the emitter.
As with other nodes in the builder, you can override all keys in the emitter() node. You can specify the ObjectName and the event type.
4.16. Design patterns in Groovy
Using design patterns with Java is a well-established topic. Design patterns also apply to Groovy:
-
some patterns carry over directly (and can make use of normal Groovy syntax improvements for greater readability)
-
some patterns are no longer required because they are built right into the language or because Groovy supports a better way of achieving the intent of the pattern
-
some patterns that have to be expressed at the design level in other languages can be implemented directly in Groovy (due to the way Groovy can blur the distinction between design and implementation)
4.16.1. Patterns
Abstract Factory Pattern
The Abstract Factory Pattern provides a way to encapsulate a group of individual factories that have a common theme. It embodies the intent of a normal factory, i.e. remove the need for code using an interface to know the concrete implementation behind the interface, but applies to a set of interfaces and selects an entire family of concrete classes which implement those interfaces.
As an example, I might have interfaces Button, TextField and Scrollbar. I might have WindowsButton, MacButton, FlashButton as concrete classes for Button. I might have WindowsScrollBar, MacScrollBar and FlashScrollBar as concrete implementations for ScrollBar. Using the Abstract Factory Pattern should allow me to select which windowing system (i.e. Windows, Mac, Flash) I want to use once and from then on should be able to write code that references the interfaces but is always using the appropriate concrete classes (all from the one windowing system) under the covers.
Example
Suppose we want to write a game system. We might note that many games have very similar features and control.
We decide to try to split the common and game-specific code into separate classes.
First let’s look at the game-specific code for a Two-up game:
class TwoupMessages {
def welcome = 'Welcome to the twoup game, you start with $1000'
def done = 'Sorry, you have no money left, goodbye'
}
class TwoupInputConverter {
def convert(input) { input.toInteger() }
}
class TwoupControl {
private money = 1000
private random = new Random()
private tossWasHead() {
def next = random.nextInt()
return next % 2 == 0
}
def moreTurns() {
if (money > 0) {
println "You have $money, how much would you like to bet?"
return true
}
false
}
def play(amount) {
def coin1 = tossWasHead()
def coin2 = tossWasHead()
if (coin1 && coin2) {
money += amount
println 'You win'
} else if (!coin1 && !coin2) {
money -= amount
println 'You lose'
} else {
println 'Draw'
}
}
}
Now, let’s look at the game-specific code for a number guessing game:
class GuessGameMessages {
def welcome = 'Welcome to the guessing game, my secret number is between 1 and 100'
def done = 'Correct'
}
class GuessGameInputConverter {
def convert(input) { input.toInteger() }
}
class GuessGameControl {
private lower = 1
private upper = 100
private guess = new Random().nextInt(upper - lower) + lower
def moreTurns() {
def done = (lower == guess || upper == guess)
if (!done) {
println "Enter a number between $lower and $upper"
}
!done
}
def play(nextGuess) {
if (nextGuess <= guess) {
lower = [lower, nextGuess].max()
}
if (nextGuess >= guess) {
upper = [upper, nextGuess].min()
}
}
}
Now, let’s write our factory code:
def guessFactory = [messages: GuessGameMessages, control: GuessGameControl, converter: GuessGameInputConverter]
def twoupFactory = [messages: TwoupMessages, control: TwoupControl, converter: TwoupInputConverter]
class GameFactory {
def static factory
def static getMessages() { return factory.messages.newInstance() }
def static getControl() { return factory.control.newInstance() }
def static getConverter() { return factory.converter.newInstance() }
}
The important aspect of this factory is that it allows selection of an entire family of concrete classes.
Here is how we would use the factory:
GameFactory.factory = twoupFactory
def messages = GameFactory.messages
def control = GameFactory.control
def converter = GameFactory.converter
println messages.welcome
def reader = new BufferedReader(new InputStreamReader(System.in))
while (control.moreTurns()) {
def input = reader.readLine().trim()
control.play(converter.convert(input))
}
println messages.done
Note that the first line configures which family of concrete game classes we will use. It’s not important that we selected which family to use by using the factory property as shown in the first line. Other ways would be equally valid examples of this pattern. For example, we may have asked the user which game they wanted to play or determined which game from an environment setting.
With the code as shown, the game might look like this when run:
Welcome to the twoup game, you start with $1000 You have 1000, how much would you like to bet? 300 Draw You have 1000, how much would you like to bet? 700 You win You have 1700, how much would you like to bet? 1700 You lose Sorry, you have no money left, goodbye
If we change the first line of the script to GameFactory.factory = guessFactory
, then the sample run might look like this:
Welcome to the guessing game, my secret number is between 1 and 100 Enter a number between 1 and 100 75 Enter a number between 1 and 75 35 Enter a number between 1 and 35 15 Enter a number between 1 and 15 5 Enter a number between 5 and 15 10 Correct
Adapter Pattern
The Adapter Pattern (sometimes called the wrapper pattern) allows objects satisfying one interface to be used where another type of interface is expected. There are two typical flavours of the pattern: the delegation flavour and the inheritance flavour.
Delegation Example
Suppose we have the following classes:
class SquarePeg {
def width
}
class RoundPeg {
def radius
}
class RoundHole {
def radius
def pegFits(peg) {
peg.radius <= radius
}
String toString() { "RoundHole with radius $radius" }
}
We can ask the RoundHole
class if a RoundPeg
fits in it, but if we ask the same question for a SquarePeg
, then it will fail because the SquarePeg
class doesn’t have a radius
property (i.e. doesn’t satisfy the required interface).
To get around this problem, we can create an adapter to make it appear to have the correct interface. It would look like this:
class SquarePegAdapter {
def peg
def getRadius() {
Math.sqrt(((peg.width / 2) ** 2) * 2)
}
String toString() {
"SquarePegAdapter with peg width $peg.width (and notional radius $radius)"
}
}
We can use the adapter like this:
def hole = new RoundHole(radius: 4.0)
(4..7).each { w ->
def peg = new SquarePegAdapter(peg: new SquarePeg(width: w))
if (hole.pegFits(peg)) {
println "peg $peg fits in hole $hole"
} else {
println "peg $peg does not fit in hole $hole"
}
}
Which results in the following output:
peg SquarePegAdapter with peg width 4 (and notional radius 2.8284271247461903) fits in hole RoundHole with radius 4.0 peg SquarePegAdapter with peg width 5 (and notional radius 3.5355339059327378) fits in hole RoundHole with radius 4.0 peg SquarePegAdapter with peg width 6 (and notional radius 4.242640687119285) does not fit in hole RoundHole with radius 4.0 peg SquarePegAdapter with peg width 7 (and notional radius 4.949747468305833) does not fit in hole RoundHole with radius 4.0
Inheritance Example
Let’s consider the same example again using inheritance. First, here are the original classes (unchanged):
class SquarePeg {
def width
}
class RoundPeg {
def radius
}
class RoundHole {
def radius
def pegFits(peg) {
peg.radius <= radius
}
String toString() { "RoundHole with radius $radius" }
}
An adapter using inheritance:
class SquarePegAdapter extends SquarePeg {
def getRadius() {
Math.sqrt(((width / 2) ** 2) * 2)
}
String toString() {
"SquarePegAdapter with width $width (and notional radius $radius)"
}
}
Using the adapter:
def hole = new RoundHole(radius: 4.0)
(4..7).each { w ->
def peg = new SquarePegAdapter(peg: new SquarePeg(width: w))
if (hole.pegFits(peg)) {
println "peg $peg fits in hole $hole"
} else {
println "peg $peg does not fit in hole $hole"
}
}
The output:
peg SquarePegAdapter with width 4 (and notional radius 2.8284271247461903) fits in hole RoundHole with radius 4.0 peg SquarePegAdapter with width 5 (and notional radius 3.5355339059327378) fits in hole RoundHole with radius 4.0 peg SquarePegAdapter with width 6 (and notional radius 4.242640687119285) does not fit in hole RoundHole with radius 4.0 peg SquarePegAdapter with width 7 (and notional radius 4.949747468305833) does not fit in hole RoundHole with radius 4.0
Adapting using Closures
As a variation of the previous examples, we could instead define the following interface:
interface RoundThing {
def getRadius()
}
We can then define an adapter as a closure as follows:
def adapter = {
p -> [getRadius: { Math.sqrt(((p.width / 2) ** 2) * 2) }] as RoundThing
}
And use it like this:
def peg = new SquarePeg(width: 4)
if (hole.pegFits(adapter(peg))) {
// ... as before
}
Adapting using the ExpandoMetaClass
As of Groovy 1.1, there is a built-in MetaClass which can automatically add properties and methods dynamically.
Here is how the example would work using that feature:
def peg = new SquarePeg(width: 4)
peg.metaClass.radius = Math.sqrt(((peg.width / 2) ** 2) * 2)
After you create a peg object, you can simply add a property to it on the fly. No need to change the original class and no need for an adapter class.
Bouncer Pattern
The Bouncer Pattern describes usage of a method whose sole purpose is to either throw an exception (when particular conditions hold) or do nothing. Such methods are often used to defensively guard pre-conditions of a method.
When writing utility methods, you should always guard against faulty input arguments. When writing internal methods, you may be able to ensure that certain pre-conditions always hold by having sufficient unit tests in place. Under such circumstances, you may reduce the desirability to have guards on your methods.
Groovy differs from other languages in that you frequently use the assert
method within your methods rather than having a large number of utility checker methods or classes.
Null Checking Example
We might have a utility method such as:
class NullChecker {
static check(name, arg) {
if (arg == null) {
throw new IllegalArgumentException(name + ' is null')
}
}
}
And we would use it like this:
void doStuff(String name, Object value) {
NullChecker.check('name', name)
NullChecker.check('value', value)
// do stuff
}
But a more Groovy way to do this would simply be like this:
void doStuff(String name, Object value) {
assert name != null, 'name should not be null'
assert value != null, 'value should not be null'
// do stuff
}
Validation Example
As an alternative example, we might have this utility method:
class NumberChecker {
static final String NUMBER_PATTERN = "\\\\d+(\\\\.\\\\d+(E-?\\\\d+)?)?"
static isNumber(str) {
if (!str ==~ NUMBER_PATTERN) {
throw new IllegalArgumentException("Argument '$str' must be a number")
}
}
static isNotZero(number) {
if (number == 0) {
throw new IllegalArgumentException('Argument must not be 0')
}
}
}
And we would use it like this:
def stringDivide(String dividendStr, String divisorStr) {
NumberChecker.isNumber(dividendStr)
NumberChecker.isNumber(divisorStr)
def dividend = dividendStr.toDouble()
def divisor = divisorStr.toDouble()
NumberChecker.isNotZero(divisor)
dividend / divisor
}
println stringDivide('1.2E2', '3.0')
// => 40.0
But with Groovy we could just as easily use:
def stringDivide(String dividendStr, String divisorStr) {
assert dividendStr =~ NumberChecker.NUMBER_PATTERN
assert divisorStr =~ NumberChecker.NUMBER_PATTERN
def dividend = dividendStr.toDouble()
def divisor = divisorStr.toDouble()
assert divisor != 0, 'Divisor must not be 0'
dividend / divisor
}
Chain of Responsibility Pattern
In the Chain of Responsibility Pattern, objects using and implementing an interface (one or more methods) are intentionally loosely coupled. A set of objects that implement the interface are organised in a list (or in rare cases a tree). Objects using the interface make requests from the first implementor object. It will decide whether to perform any action itself and whether to pass the request further down the line in the list (or tree). Sometimes a default implementation for some request is also coded into the pattern if none of the implementors respond to the request.
Example
In this example, the script sends requests to the lister
object. The lister
points to a UnixLister
object. If it can’t handle the request, it sends the request to the WindowsLister
. If it can’t handle the request, it sends the request to the DefaultLister
.
class UnixLister {
private nextInLine
UnixLister(next) { nextInLine = next }
def listFiles(dir) {
if (System.getProperty('os.name') == 'Linux') {
println "ls $dir".execute().text
} else {
nextInLine.listFiles(dir)
}
}
}
class WindowsLister {
private nextInLine
WindowsLister(next) { nextInLine = next }
def listFiles(dir) {
if (System.getProperty('os.name') == 'Windows XP') {
println "cmd.exe /c dir $dir".execute().text
} else {
nextInLine.listFiles(dir)
}
}
}
class DefaultLister {
def listFiles(dir) {
new File(dir).eachFile { f -> println f }
}
}
def lister = new UnixLister(new WindowsLister(new DefaultLister()))
lister.listFiles('Downloads')
The output will be a list of files (with slightly different format depending on the operating system).
Here is a UML representation:
Variations to this pattern:
-
we could have an explicit interface, e.g.
Lister
, to statically type the implementations but because of duck-typing this is optional -
we could use a chain tree instead of a list, e.g.
if (animal.hasBackbone())
delegate toVertebrateHandler
else delegate toInvertebrateHandler
-
we could always pass down the chain even if we processed a request
-
we could decide at some point to not respond and not pass down the chain
-
we could use Groovy’s meta-programming capabilities to pass unknown methods down the chain
Composite Pattern
The Composite Pattern allows you to treat single instances of an object the same way as a group of objects. The pattern is often used with hierarchies of objects. Typically, one or more methods should be callable in the same way for either leaf or composite nodes within the hierarchy. In such a case, composite nodes typically invoke the same named method for each of their children nodes.
Example
Consider this usage of the composite pattern where we want to call toString()
on either Leaf
or Composite
objects.
In Java, the Component
class is essential as it provides the type used for both leaf and composite nodes. In Groovy, because of duck-typing, we don’t need it for that purpose, however, it can still server as a useful place to place common behaviour between the leaf and composite nodes.
For our purposes, we will assemble the following hierarchy of components.
Here is the code:
abstract class Component {
def name
def toString(indent) {
("-" * indent) + name
}
}
class Composite extends Component {
private children = []
def toString(indent) {
def s = super.toString(indent)
children.each { child ->
s += "\\n" + child.toString(indent + 1)
}
s
}
def leftShift(component) {
children << component
}
}
class Leaf extends Component { }
def root = new Composite(name: "root")
root << new Leaf(name: "leaf A")
def comp = new Composite(name: "comp B")
root << comp
root << new Leaf(name: "leaf C")
comp << new Leaf(name: "leaf B1")
comp << new Leaf(name: "leaf B2")
println root.toString(0)
Here is the resulting output:
root -leaf A -comp B --leaf B1 --leaf B2 -leaf C
Decorator Pattern
The Decorator Pattern provides a mechanism to embellish the behaviour of an object without changing its essential interface. A decorated object should be able to be substituted wherever the original (non-decorated) object was expected. Decoration typically does not involve modifying the source code of the original object and decorators should be able to be combined in flexible ways to produce objects with several embellishments.
Traditional Example
Suppose we have the following Logger
class.
class Logger {
def log(String message) {
println message
}
}
There might be times when it is useful to timestamp a log message, or times when we might want to change the case of the message. We could try to build all of this functionality into our Logger
class. If we did that, the Logger
class would start to be very complex. Also, everyone would obtain all of features even when they might not want a small subset of the features. Finally, feature interaction would become quite difficult to control.
To overcome these drawbacks, we instead define two decorator classes. Uses of the Logger
class are free to embellish their base logger with zero or more decorator classes in whatever order they desire. The classes look like this:
class TimeStampingLogger extends Logger {
private Logger logger
TimeStampingLogger(logger) {
this.logger = logger
}
def log(String message) {
def now = Calendar.instance
logger.log("$now.time: $message")
}
}
class UpperLogger extends Logger {
private Logger logger
UpperLogger(logger) {
this.logger = logger
}
def log(String message) {
logger.log(message.toUpperCase())
}
}
We can use the decorators like so:
def logger = new UpperLogger(new TimeStampingLogger(new Logger()))
logger.log("G'day Mate")
// => Tue May 22 07:13:50 EST 2007: G'DAY MATE
You can see that we embellish the logger behaviour with both decorators. Because of the order we chose to apply the decorators, our log message comes out capitalised and the timestamp is in normal case. If we swap the order around, let’s see what happens:
logger = new TimeStampingLogger(new UpperLogger(new Logger()))
logger.log('Hi There')
// => TUE MAY 22 07:13:50 EST 2007: HI THERE
Now the timestamp itself has also been changed to be uppercase.
A touch of dynamic behaviour
Our previous decorators were specific to Logger
objects. We can use Groovy’s Meta-Object Programming capabilities to create a decorator which is far more general purpose in nature. Consider this class:
class GenericLowerDecorator {
private delegate
GenericLowerDecorator(delegate) {
this.delegate = delegate
}
def invokeMethod(String name, args) {
def newargs = args.collect { arg ->
if (arg instanceof String) {
return arg.toLowerCase()
} else {
return arg
}
}
delegate.invokeMethod(name, newargs)
}
}
It takes any class and decorates it so that any String
method parameter will automatically be changed to lower case.
logger = new GenericLowerDecorator(new TimeStampingLogger(new Logger()))
logger.log('IMPORTANT Message')
// => Tue May 22 07:27:18 EST 2007: important message
Just be careful with ordering here. The original decorators were restricted to decorating Logger
objects. This decorator work with any object type, so we can’t swap the ordering around, i.e. this won’t work:
// Can't mix and match Interface-Oriented and Generic decorators // logger = new TimeStampingLogger(new GenericLowerDecorator(new Logger()))
We could overcome this limitation be generating an appropriate Proxy type at runtime but we won’t complicate the example here.
Runtime behaviour embellishment
You can also consider using the ExpandoMetaClass
from Groovy 1.1 to dynamically embellish a class with behaviour. This isn’t the normal style of usage of the decorator pattern (it certainly isn’t nearly as flexible) but may help you to achieve similar results in some cases without creating a new class.
Here’s what the code looks like:
// current mechanism to enable ExpandoMetaClass
GroovySystem.metaClassRegistry.metaClassCreationHandle = new ExpandoMetaClassCreationHandle()
def logger = new Logger()
logger.metaClass.log = { String m -> println 'message: ' + m.toUpperCase() }
logger.log('x')
// => message: X
This achieves a similar result to applying a single decorator but we have no way to easily apply and remove embellishments on the fly.
More dynamic decorating
Suppose we have a calculator class (Actually any class would do).
class Calc {
def add(a, b) { a + b }
}
We might be interested in observing usage of the class over time. If it is buried deep within our codebase, it might be hard to determine when it is being called and with what parameters. Also, it might be hard to know if it is performing well. We can easily make a generic tracing decorator that prints out tracing information whenever any method on the Calc
class is called and also provide timing information about how long it took to execute. Here is the code for the tracing decorator:
class TracingDecorator {
private delegate
TracingDecorator(delegate) {
this.delegate = delegate
}
def invokeMethod(String name, args) {
println "Calling $name$args"
def before = System.currentTimeMillis()
def result = delegate.invokeMethod(name, args)
println "Got $result in ${System.currentTimeMillis()-before} ms"
result
}
}
Here is how to use the class in a script:
def tracedCalc = new TracingDecorator(new Calc())
assert 15 == tracedCalc.add(3, 12)
And here is what you would see after running this script:
Calling add{3, 12} Got 15 in 31 ms
Decorating with an Interceptor
The above timing example hooks into the lifecycle of Groovy objects (via invokeMethod
). This is such an important style performing meta-programming that Groovy has special support for this style of decorating using interceptors.
Groovy even comes with a built-in TracingInterceptor
. We can extend the built-in class like this:
class TimingInterceptor extends TracingInterceptor {
private beforeTime
def beforeInvoke(object, String methodName, Object[] arguments) {
super.beforeInvoke(object, methodName, arguments)
beforeTime = System.currentTimeMillis()
}
Object afterInvoke(Object object, String methodName, Object[] arguments, Object result) {
super.afterInvoke(object, methodName, arguments, result)
def duration = System.currentTimeMillis() - beforeTime
writer.write("Duration: $duration ms\\n")
writer.flush()
result
}
}
Here is an example of using this new class:
def proxy = ProxyMetaClass.getInstance(Calc)
proxy.interceptor = new TimingInterceptor()
proxy.use {
assert 7 == new Calc().add(1, 6)
}
And here is the output:
before Calc.ctor() after Calc.ctor() Duration: 0 ms before Calc.add(java.lang.Integer, java.lang.Integer) after Calc.add(java.lang.Integer, java.lang.Integer) Duration: 2 ms
Decorating with java.lang.reflect.Proxy
If you are trying to decorate an object (i.e. just a particular instance of the class, not the class generally), then you can use Java’s java.lang.reflect.Proxy
. Groovy makes working with this easier than just Java. Below is a code sample taken out of a grails project that wraps a java.sql.Connection
so that it’s close method is a no-op:
protected Sql getGroovySql() {
final Connection con = session.connection()
def invoker = { object, method, args ->
if (method.name == "close") {
log.debug("ignoring call to Connection.close() for use by groovy.sql.Sql")
} else {
log.trace("delegating $method")
return con.invokeMethod(method.name, args)
}
} as InvocationHandler;
def proxy = Proxy.newProxyInstance( getClass().getClassLoader(), [Connection] as Class[], invoker )
return new Sql(proxy)
}
If there were many methods to intercept, then this approach could be modified to look up closure in a map by method name and invoke it.
Decorating with Spring
The Spring Framework allows decorators to be applied with interceptors (you may have heard the terms advice or aspect). You can leverage this mechanism from Groovy as well.
First define a class that you want to decorate (we’ll also use an interface as is normal Spring practice):
Here’s the interface:
interface Calc {
def add(a, b)
}
Here’s the class:
class CalcImpl implements Calc {
def add(a, b) { a + b }
}
Now, we define our wiring in a file called beans.xml
as follows:
<?xml version="1.0" encoding="UTF-8"?>
<beans xmlns="http://www.springframework.org/schema/beans"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xmlns:lang="http://www.springframework.org/schema/lang"
xsi:schemaLocation="
http://www.springframework.org/schema/beans http://www.springframework.org/schema/beans/spring-beans.xsd
http://www.springframework.org/schema/lang http://www.springframework.org/schema/lang/spring-lang.xsd">
<bean id="performanceInterceptor" autowire="no"
class="org.springframework.aop.interceptor.PerformanceMonitorInterceptor">
<property name="loggerName" value="performance"/>
</bean>
<bean id="calc" class="util.CalcImpl"/>
<bean class="org.springframework.aop.framework.autoproxy.BeanNameAutoProxyCreator">
<property name="beanNames" value="calc"/>
<property name="interceptorNames" value="performanceInterceptor"/>
</bean>
</beans>
Now, our script looks like this:
@Grab('org.springframework:spring-context:3.2.2.RELEASE')
import org.springframework.context.support.ClassPathXmlApplicationContext
def ctx = new ClassPathXmlApplicationContext('beans.xml')
def calc = ctx.getBean('calc')
println calc.add(3, 25)
And when we run it, we see the results:
21/05/2007 23:02:35 org.springframework.aop.interceptor.PerformanceMonitorInterceptor invokeUnderTrace FINEST: StopWatch 'util.Calc.add': running time (millis) = 16
You may have to adjust your logging.properties
file for messages at log level FINEST
to be displayed.
Asynchronous Decorators using GPars
Using the example code in Panini for inspiration. Here is a Groovy version that avoids using an @AddedBehavior
annotation at the expense of not having as general an algorithm for selecting the methods to decorate. This isn’t a limitation of the particular approach chosen but just a simplification for illustrative purposes (but don’t assume below is an exact equivalent).
@Grab('org.codehaus.gpars:gpars:0.10')
import static groovyx.gpars.GParsPool.withPool
interface Document {
void print()
String getText()
}
class DocumentImpl implements Document {
def document
void print() { println document }
String getText() { document }
}
def words(String text) {
text.replaceAll('[^a-zA-Z]', ' ').trim().split("\\\\s+")*.toLowerCase()
}
def avgWordLength = {
def words = words(it.text)
sprintf "Avg Word Length: %4.2f", words*.size().sum() / words.size()
}
def modeWord = {
def wordGroups = words(it.text).groupBy {it}.collectEntries { k, v -> [k, v.size()] }
def maxSize = wordGroups*.value.max()
def maxWords = wordGroups.findAll { it.value == maxSize }
"Mode Word(s): ${maxWords*.key.join(', ')} ($maxSize occurrences)"
}
def wordCount = { d -> "Word Count: " + words(d.text).size() }
def asyncDecorator(Document d, Closure c) {
ProxyGenerator.INSTANCE.instantiateDelegate([print: {
withPool {
def result = c.callAsync(d)
d.print()
println result.get()
}
}], [Document], d)
}
Document d = asyncDecorator(asyncDecorator(asyncDecorator(
new DocumentImpl(document:"This is the file with the words in it\\n\\t\\nDo you see the words?\\n"),
// new DocumentImpl(document: new File('AsyncDecorator.groovy').text),
wordCount), modeWord), avgWordLength)
d.print()
Delegation Pattern
The Delegation Pattern is a technique where an object’s behavior (public methods) is implemented by delegating responsibility to one or more associated objects.
Groovy allows the traditional style of applying the delegation pattern, e.g. see Replace Inheritance with Delegation.
Implement Delegation Pattern using ExpandoMetaClass
The ExpandoMetaClass allows usage of this pattern to be encapsulated in a library. This allows Groovy to emulate similar libraries available for the Ruby language.
Consider the following library class:
class Delegator {
private targetClass
private delegate
Delegator(targetClass, delegate) {
this.targetClass = targetClass
this.delegate = delegate
}
def delegate(String methodName) {
delegate(methodName, methodName)
}
def delegate(String methodName, String asMethodName) {
targetClass.metaClass."$asMethodName" = delegate.&"$methodName"
}
def delegateAll(String[] names) {
names.each { delegate(it) }
}
def delegateAll(Map names) {
names.each { k, v -> delegate(k, v) }
}
def delegateAll() {
delegate.class.methods*.name.each { delegate(it) }
}
}
With this in your classpath, you can now apply the delegation pattern dynamically as shown in the following examples. First, consider we have the following classes:
class Person {
String name
}
class MortgageLender {
def borrowAmount(amount) {
"borrow \\$$amount"
}
def borrowFor(thing) {
"buy \\$thing"
}
}
def lender = new MortgageLender()
def delegator = new Delegator(Person, lender)
We can now use the delegator to automatically borrow methods from the lender object to extend the Person class. We can borrow the methods as is or with a rename:
delegator.delegate 'borrowFor'
delegator.delegate 'borrowAmount', 'getMoney'
def p = new Person()
println p.borrowFor('present') // => buy present
println p.getMoney(50)
The first line above, adds the borrowFor method to the Person class by delegating to the lender object. The second line adds a getMoney method to the Person class by delegating to the lender object’s borrowAmount method.
Alternatively, we could borrow multiple methods like this:
delegator.delegateAll 'borrowFor', 'borrowAmount'
Which adds these two methods to the Person class.
Or if we want all the methods, like this:
delegator.delegateAll()
Which will make all the methods in the delegate object available in the Person class.
Alternatively, we can use a map notation to rename multiple methods:
delegator.delegateAll borrowAmount:'getMoney', borrowFor:'getThing'
Implement Delegation Pattern using @Delegate annotation
Since version 1.6 you can use the built-in delegation mechanism which is based on AST transformation.
This make delegation even easier:
class Person {
def name
@Delegate MortgageLender mortgageLender = new MortgageLender()
}
class MortgageLender {
def borrowAmount(amount) {
"borrow \\$$amount"
}
def borrowFor(thing) {
"buy $thing"
}
}
def p = new Person()
assert "buy present" == p.borrowFor('present')
assert "borrow \\$50" == p.borrowAmount(50)
Flyweight Pattern
The Flyweight Pattern is a pattern for greatly reducing memory requirements by not requiring that heavy-weight objects be created in large numbers when dealing with systems that contain many things that are mostly the same. If for instance, a document was modeled using a complex character class that knew about unicode, fonts, positioning, etc., then the memory requirements could be quite large for large documents if each physical character in the document required its own character class instance. Instead, characters themselves might be kept within Strings and we might have one character class (or a small number such as one character class for each font type) that knew the specifics of how to deal with characters.
In such circumstances, we call the state that is shared with many other things (e.g. the character type) instrinsic state. It is captured within the heavy-weight class. The state which distinguishes the physical character (maybe just its ASCII code or Unicode) is called its extrinsic state.
Example
First we are going to model some complex aircraft (the first being a hoax competitor of the second - not that is relevant to the example).
class Boeing797 {
def wingspan = '80.8 m'
def capacity = 1000
def speed = '1046 km/h'
def range = '14400 km'
// ...
}
class Airbus380 {
def wingspan = '79.8 m'
def capacity = 555
def speed = '912 km/h'
def range = '10370 km'
// ...
}
If we want to model our fleet, our first attempt might involve using many instances of these heavy-weight objects. It turns out though that only a few small pieces of state (our extrinsic state) change for each aircraft, so we will have singletons for the heavy-weight objects and capture the extrinsic state (bought date and asset number in the code below) separately.
class FlyweightFactory {
static instances = [797: new Boeing797(), 380: new Airbus380()]
}
class Aircraft {
private type // instrinsic state
private assetNumber // extrinsic state
private bought // extrinsic state
Aircraft(typeCode, assetNumber, bought) {
type = FlyweightFactory.instances[typeCode]
this.assetNumber = assetNumber
this.bought = bought
}
def describe() {
println """
Asset Number: $assetNumber
Capacity: $type.capacity people
Speed: $type.speed
Range: $type.range
Bought: $bought
"""
}
}
def fleet = [
new Aircraft(380, 1001, '10-May-2007'),
new Aircraft(380, 1002, '10-Nov-2007'),
new Aircraft(797, 1003, '10-May-2008'),
new Aircraft(797, 1004, '10-Nov-2008')
]
fleet.each { p -> p.describe() }
So here, even if our fleet contained hundreds of planes, we would only have one heavy-weight object for each type of aircraft.
As a further efficiency measure, we might use lazy creation of the flyweight objects rather than create the initial map up front as in the above example.
Running this script results in:
Asset Number: 1001 Capacity: 555 people Speed: 912 km/h Range: 10370 km Bought: 10-May-2007 Asset Number: 1002 Capacity: 555 people Speed: 912 km/h Range: 10370 km Bought: 10-Nov-2007 Asset Number: 1003 Capacity: 1000 people Speed: 1046 km/h Range: 14400 km Bought: 10-May-2008 Asset Number: 1004 Capacity: 1000 people Speed: 1046 km/h Range: 14400 km Bought: 10-Nov-2008
Iterator Pattern
The Iterator Pattern allows sequential access to the elements of an aggregate object without exposing its underlying representation.
Groovy has the iterator pattern built right in to many of its closure operators, e.g. each
and eachWithIndex
as well as the for .. in
loop.
For example:
def printAll(container) {
for (item in container) { println item }
}
def numbers = [ 1,2,3,4 ]
def months = [ Mar:31, Apr:30, May:31 ]
def colors = [ java.awt.Color.BLACK, java.awt.Color.WHITE ]
printAll numbers
printAll months
printAll colors
Results in the output:
1 2 3 4 May=31 Mar=31 Apr=30 java.awt.Color[r=0,g=0,b=0] java.awt.Color[r=255,g=255,b=255]
Another example:
colors.eachWithIndex { item, pos ->
println "Position $pos contains '$item'"
}
Results in:
Position 0 contains 'java.awt.Color[r=0,g=0,b=0]' Position 1 contains 'java.awt.Color[r=255,g=255,b=255]'
The iterator pattern is also built in to other special operators such as the eachByte
, eachFile
, eachDir
, eachLine
, eachObject
, eachMatch
operators for working with streams, URLs, files, directories and regular expressions matches.
Loan my Resource Pattern
The Loan my Resource pattern ensures that a resource is deterministically disposed of once it goes out of scope.
This pattern is built in to many Groovy helper methods. You should consider using it yourself if you need to work with resources in ways beyond what Groovy supports.
Example
Consider the following code which works with a file. First we might write some line to the file and then print its size:
def f = new File('junk.txt')
f.withPrintWriter { pw ->
pw.println(new Date())
pw.println(this.class.name)
}
println f.size()
// => 42
We could also read back the contents of the file a line at a time and print each line out:
f.eachLine { line ->
println line
}
// =>
// Mon Jun 18 22:38:17 EST 2007
// RunPattern
Note that normal Java Reader
and PrintWriter
objects were used under the covers by Groovy but the code writer did not have to worry about explicitly creating or closing those resources. The built-in Groovy methods loan the respective reader or writer to the closure code and then tidy up after themselves. So, you are using this pattern without having to do any work.
Sometimes however, you wish to do things slightly differently to what you can get for free using Groovy’s built-in mechanisms. You should consider utilising this pattern within your own resource-handling operations.
Consider how you might process the list of words on each line within the file. We could actually do this one too using Groovy’s built-in functions, but bear with us and assume we have to do some resource handling ourselves. Here is how we might write the code without using this pattern:
def reader = f.newReader()
reader.splitEachLine(' ') { wordList ->
println wordList
}
reader.close()
// =>
// [ "Mon", "Jun", "18", "22:38:17", "EST", "2007" ]
// [ "RunPattern" ]
Notice that we now have an explicit call to close()
in our code. If we didn’t code it just right (here we didn’t surround the code in a try … finally
block, we run the risk of leaving the file handle open.
Let’s now apply the loan pattern. First, we’ll write a helper method:
def withListOfWordsForEachLine(File f, Closure c) {
def r = f.newReader()
try {
r.splitEachLine(' ', c)
} finally {
r?.close()
}
}
Now, we can re-write our code as follows:
withListOfWordsForEachLine(f) { wordList ->
println wordList
}
// =>
// [ "Mon", "Jun", "18", "22:38:17", "EST", "2007" ]
// [ "RunPattern" ]
This is much simpler and has removed the explicit close()
. This is now catered for in one spot so we can apply the appropriate level of testing or reviewing in just one spot to be sure we have no problems.
Null Object Pattern
The Null Object Pattern involves using a special object place-marker object representing null. Typically, if you have a reference to null, you can’t invoke reference.field
or reference.method()
. You receive the dreaded NullPointerException
. The null object pattern uses a special object representing null, instead of using an actual null
. This allows you to invoke field and method references on the null object. The result of using the null object should semantically be equivalent to doing nothing.
Simple Example
Suppose we have the following system:
class Job {
def salary
}
class Person {
def name
def Job job
}
def people = [
new Person(name: 'Tom', job: new Job(salary: 1000)),
new Person(name: 'Dick', job: new Job(salary: 1200)),
]
def biggestSalary = people.collect { p -> p.job.salary }.max()
println biggestSalary
When run, this prints out 1200
. Suppose now that we now invoke:
people << new Person(name: 'Harry')
If we now try to calculate biggestSalary
again, we receive a null pointer exception.
To overcome this problem, we can introduce a NullJob
class and change the above statement to become:
class NullJob extends Job { def salary = 0 }
people << new Person(name: 'Harry', job: new NullJob())
biggestSalary = people.collect { p -> p.job.salary }.max()
println biggestSalary
This works as we require but it’s not always the best way to do this with Groovy. Groovy’s safe-dereference operator (?.
) operator and null aware closures often allow Groovy to avoid the need to create a special null object or null class. This is illustrated by examining a groovier way to write the above example:
people << new Person(name:'Harry')
biggestSalary = people.collect { p -> p.job?.salary }.max()
println biggestSalary
Two things are going on here to allow this to work. First of all, max()
is 'null aware’ so that [300, null, 400].max() == 400
. Secondly, with the ?.
operator, an expression like p?.job?.salary
will be equal to null if salary
is equal to null, or if job
is equal to null or if p
is equal to null. You don’t need to code a complex nested if … then … else
to avoid a NullPointerException
.
Tree Example
Consider the following example where we want to calculate size, cumulative sum and cumulative product of all the values in a tree structure.
Our first attempt has special logic within the calculation methods to handle null values.
class NullHandlingTree {
def left, right, value
def size() {
1 + (left ? left.size() : 0) + (right ? right.size() : 0)
}
def sum() {
value + (left ? left.sum() : 0) + (right ? right.sum() : 0)
}
def product() {
value * (left ? left.product() : 1) * (right ? right.product() : 1)
}
}
def root = new NullHandlingTree(
value: 2,
left: new NullHandlingTree(
value: 3,
right: new NullHandlingTree(value: 4),
left: new NullHandlingTree(value: 5)
)
)
println root.size()
println root.sum()
println root.product()
If we introduce the null object pattern (here by defining the NullTree
class), we can now simplify the logic in the size()
, sum()
and product()
methods. These methods now much more clearly represent the logic for the normal (and now universal) case. Each of the methods within NullTree
returns a value which represents doing nothing.
class Tree {
def left = new NullTree(), right = new NullTree(), value
def size() {
1 + left.size() + right.size()
}
def sum() {
value + left.sum() + right.sum()
}
def product() {
value * left.product() * right.product()
}
}
class NullTree {
def size() { 0 }
def sum() { 0 }
def product() { 1 }
}
def root = new Tree(
value: 2,
left: new Tree(
value: 3,
right: new Tree(value: 4),
left: new Tree(value: 5)
)
)
println root.size()
println root.sum()
println root.product()
The result of running either of these examples is:
4 14 120
Note: a slight variation with the null object pattern is to combine it with the singleton pattern. So, we wouldn’t write new NullTree()
wherever we needed a null object as shown above. Instead we would have a single null object instance which we would place within our data structures as needed.
Pimp my Library Pattern
The Pimp my Library Pattern suggests an approach for extending a library that nearly does everything that you need but just needs a little more. It assumes that you do not have source code for the library of interest.
Example
Suppose we want to make use of the built-in Integer facilities in Groovy (which build upon the features already in Java). Those libraries have nearly all of the features we want but not quite everything. We may not have all of the source code to the Groovy and Java libraries so we can’t just change the library. Instead we augment the library. Groovy has a number of ways to do this. One way is to use a Category.
First, we’ll define a suitable category.
class EnhancedInteger {
static boolean greaterThanAll(Integer self, Object[] others) {
greaterThanAll(self, others)
}
static boolean greaterThanAll(Integer self, others) {
others.every { self > it }
}
}
We have added two methods which augment the Integer methods by providing the greaterThanAll
method. Categories follow conventions where they are defined as static methods with a special first parameter representing the class we wish to extend. The greaterThanAll(Integer self, others)
static method becomes the greaterThanAll(other)
instance method.
We defined two versions of greaterThanAll
. One which works for collections, ranges etc. The other which works with a variable number of Integer
arguments.
Here is how you would use the category.
use(EnhancedInteger) {
assert 4.greaterThanAll(1, 2, 3)
assert !5.greaterThanAll(2, 4, 6)
assert 5.greaterThanAll(-4..4)
assert 5.greaterThanAll([])
assert !5.greaterThanAll([4, 5])
}
As you can see, using this technique you can effectively enrich an original class without having access to its source code. Moreover, you can apply different enrichments in different parts of the system as well as work with un-enriched objects if we need to.
Proxy Pattern
The Proxy Pattern allows one object to act as a pretend replacement for some other object. In general, whoever is using the proxy, doesn’t realise that they are not using the real thing. The pattern is useful when the real object is hard to create or use: it may exist over a network connection, or be a large object in memory, or be a file, database or some other resource that is expensive or impossible to duplicate.
Example
One common use of the proxy pattern is when talking to remote objects in a different JVM. Here is the client code for creating a proxy that talks via sockets to a server object as well as an example usage:
class AccumulatorProxy {
def accumulate(args) {
def result
def s = new Socket("localhost", 54321)
s.withObjectStreams { ois, oos ->
oos << args
result = ois.readObject()
}
s.close()
return result
}
}
println new AccumulatorProxy().accumulate([1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
// => 55
Here is what your server code might look like (start this first):
class Accumulator {
def accumulate(args) {
args.inject(0) { total, arg -> total += arg }
}
}
def port = 54321
def accumulator = new Accumulator()
def server = new ServerSocket(port)
println "Starting server on port $port"
while(true) {
server.accept() { socket ->
socket.withObjectStreams { ois, oos ->
def args = ois.readObject()
oos << accumulator.accumulate(args)
}
}
}
Singleton Pattern
The Singleton Pattern is used to make sure only one object of a particular class is ever created. This can be useful when when exactly one object is needed to coordinate actions across a system; perhaps for efficiency where creating lots of identical objects would be wasteful, perhaps because a particular algorithm needing a single point of control is required or perhaps when an object is used to interact with a non-shareable resource.
Weaknesses of the Singleton pattern include:
-
It can reduce reuse. For instance, there are issues if you want to use inheritance with Singletons. If
SingletonB
extendsSingletonA
, should there be exactly (at most) one instance of each or should the creation of an object from one of the classes prohibit creation from the other. Also, if you decide both classes can have an instance, how do you override thegetInstance()
method which is static? -
It is also hard to test singletons in general because of the static methods but Groovy can support that if required.
Example: The Classic Java Singleton
Suppose we wish to create a class for collecting votes. Because getting the right number of votes may be very important, we decide to use the singleton pattern. There will only ever be one VoteCollector
object, so it makes it easier for us to reason about that objects creation and use.
class VoteCollector {
def votes = 0
private static final INSTANCE = new VoteCollector()
static getInstance() { return INSTANCE }
private VoteCollector() { }
def display() { println "Collector:${hashCode()}, Votes:$votes" }
}
Some points of interest about this code:
-
it has a private constructor, so no
VoteCollector
objects can be created in our system (except for theINSTANCE
we create) -
the
INSTANCE
is also private, so it can’t be changed once set -
we haven’t made the updating of votes thread-safe at this point (it doesn’t add to this example)
-
the vote collector instance is not lazyily created (if we never reference the class, the instance won’t be created; however, as soon as we reference the class, the instance will be created even if not needed initially)
We can use this singleton class in some script code as follows:
def collector = VoteCollector.instance
collector.display()
collector.votes++
collector = null
Thread.start{
def collector2 = VoteCollector.instance
collector2.display()
collector2.votes++
collector2 = null
}.join()
def collector3 = VoteCollector.instance
collector3.display()
Here we used the instance 3 times. The second usage was even in a different thread (but don’t try this in a scenario with a new class loader).
Running this script yields (your hashcode value will vary):
Collector:15959960, Votes:0 Collector:15959960, Votes:1 Collector:15959960, Votes:2
Variations to this pattern:
-
To support lazy-loading and multi-threading, we could just use the
synchronized
keyword with thegetInstance()
method. This has a performance hit but will work. -
We can consider variations involving double-checked locking and the
volatile
keyword (for Java 5 and above), but see the limitations of this approach here.
Example: Singleton via MetaProgramming
Groovy’s meta-programming capabilities allow concepts like the singleton pattern to be enacted in a far more fundamental way. This example illustrates a simple way to use Groovy’s meta-programming capabilities to achieve the singleton pattern but not necessarily the most efficient way.
Suppose we want to keep track of the total number of calculations that a calculator performs. One way to do that is to use a singleton for the calculator class and keep a variable in the class with the count.
First we define some base classes. A Calculator
class which performs calculations and records how many such calculations it performs and a Client
class which acts as a facade to the calculator.
class Calculator {
private total = 0
def add(a, b) { total++; a + b }
def getTotalCalculations() { 'Total Calculations: ' + total }
String toString() { 'Calc: ' + hashCode() }
}
class Client {
def calc = new Calculator()
def executeCalc(a, b) { calc.add(a, b) }
String toString() { 'Client: ' + hashCode() }
}
Now we can define and register a MetaClass which intercepts all attempts to create a Calculator
object and always provides a pre-created instance instead. We also register this MetaClass with the Groovy system:
class CalculatorMetaClass extends MetaClassImpl {
private static final INSTANCE = new Calculator()
CalculatorMetaClass() { super(Calculator) }
def invokeConstructor(Object[] arguments) { return INSTANCE }
}
def registry = GroovySystem.metaClassRegistry
registry.setMetaClass(Calculator, new CalculatorMetaClass())
Now we use instances of our Client
class from within a script. The client class will attempt to create new instances of the calculator but will always get the singleton.
def client = new Client()
assert 3 == client.executeCalc(1, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
client = new Client()
assert 4 == client.executeCalc(2, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
Here is the result of running this script (your hashcode values may vary):
Client: 7306473, Calc: 24230857, Total Calculations: 1 Client: 31436753, Calc: 24230857, Total Calculations: 2
Guice Example
We can also implement the Singleton Pattern using Guice. This example relies on annotations. Annotations are a Groovy 1.1 feature and will need to be run on a Java 5 or above JVM.
Consider the Calculator example again.
Guice is a Java-oriented framework that supports Interface-Oriented design. Hence we create a Calculator
interface first. We can then create our CalculatorImpl
implementation and a Client
object which our script will interact with. The Client
class isn’t strictly needed for this example but allows us to show that non-singleton instances are the default. Here is the code:
@Grapes([@Grab('aopalliance:aopalliance:1.0'), @Grab('com.google.code.guice:guice:1.0')])
import com.google.inject.*
interface Calculator {
def add(a, b)
}
class CalculatorImpl implements Calculator {
private total = 0
def add(a, b) { total++; a + b }
def getTotalCalculations() { 'Total Calculations: ' + total }
String toString() { 'Calc: ' + hashCode() }
}
class Client {
@Inject Calculator calc
def executeCalc(a, b) { calc.add(a, b) }
String toString() { 'Client: ' + hashCode() }
}
def injector = Guice.createInjector (
[configure: { binding ->
binding.bind(Calculator)
.to(CalculatorImpl)
.asEagerSingleton() } ] as Module
)
def client = injector.getInstance(Client)
assert 3 == client.executeCalc(1, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
client = injector.getInstance(Client)
assert 4 == client.executeCalc(2, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
Note the @Inject
annotation in the Client
class. We can always tell right in the source code which fields will be injected.
In this example we chose to use an explicit binding. All of our dependencies (ok, only one in this example at the moment) are configured in the binding. The Guide injector knows about the binding and injects the dependencies as required when we create objects. For the singleton pattern to hold, you must always use Guice to create your instances. Nothing shown so far would stop you creating another instance of the calculator manually using new CalculatorImpl()
which would of course violate the desired singleton behaviour.
In other scenarios (though probably not in large systems), we could choose to express dependencies using annotations, such as the following example shows:
@Grapes([@Grab('aopalliance:aopalliance:1.0'), @Grab('com.google.code.guice:guice:1.0')])
import com.google.inject.*
@ImplementedBy(CalculatorImpl)
interface Calculator {
// as before ...
}
@Singleton
class CalculatorImpl implements Calculator {
// as before ...
}
class Client {
// as before ...
}
def injector = Guice.createInjector()
// ...
Note the @Singleton
annotation on the CalculatorImpl
class and the @ImplementedBy
annotation in the Calculator
interface.
When run, the above example (using either approach) yields (your hashcode values will vary):
Client: 8897128, Calc: 17431955, Total Calculations: 1 Client: 21145613, Calc: 17431955, Total Calculations: 2
You can see that we obtained a new client object whenever we asked for an instance but it was injected with the same calculator object.
Spring Example
We can do the Calculator example again using Spring as follows:
@Grapes([@Grab('org.springframework:spring-core:3.2.2.RELEASE'), @Grab('org.springframework:spring-beans:3.2.2.RELEASE')])
import org.springframework.beans.factory.support.*
interface Calculator {
def add(a, b)
}
class CalculatorImpl implements Calculator {
private total = 0
def add(a, b) { total++; a + b }
def getTotalCalculations() { 'Total Calculations: ' + total }
String toString() { 'Calc: ' + hashCode() }
}
class Client {
Client(Calculator calc) { this.calc = calc }
def calc
def executeCalc(a, b) { calc.add(a, b) }
String toString() { 'Client: ' + hashCode() }
}
// Here we 'wire' up our dependencies through the API. Alternatively,
// we could use XML-based configuration or the Grails Bean Builder DSL.
def factory = new DefaultListableBeanFactory()
factory.registerBeanDefinition('calc', new RootBeanDefinition(CalculatorImpl))
def beanDef = new RootBeanDefinition(Client, false)
beanDef.setAutowireMode(AbstractBeanDefinition.AUTOWIRE_AUTODETECT)
factory.registerBeanDefinition('client', beanDef)
def client = factory.getBean('client')
assert 3 == client.executeCalc(1, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
client = factory.getBean('client')
assert 4 == client.executeCalc(2, 2)
println "$client, $client.calc, $client.calc.totalCalculations"
And here is the result (your hashcode values will vary):
Client: 29418586, Calc: 10580099, Total Calculations: 1 Client: 14800362, Calc: 10580099, Total Calculations: 2
State Pattern
The State Pattern provides a structured approach to partitioning the behaviour within complex systems. The overall behaviour of a system is partitioned into well-defined states. Typically, each state is implemented by a class. The overall system behaviour can be determined firstly by knowing the current state of the system; secondly, by understanding the behaviour possible while in that state (as embodied in the methods of the class corresponding to that state).
Example
Here is an example:
class Client {
def context = new Context()
def connect() {
context.state.connect()
}
def disconnect() {
context.state.disconnect()
}
def send_message(message) {
context.state.send_message(message)
}
def receive_message() {
context.state.receive_message()
}
}
class Context {
def state = new Offline(this)
}
class ClientState {
def context
ClientState(context) {
this.context = context
inform()
}
}
class Offline extends ClientState {
Offline(context) {
super(context)
}
def inform() {
println "offline"
}
def connect() {
context.state = new Online(context)
}
def disconnect() {
println "error: not connected"
}
def send_message(message) {
println "error: not connected"
}
def receive_message() {
println "error: not connected"
}
}
class Online extends ClientState {
Online(context) {
super(context)
}
def inform() {
println "connected"
}
def connect() {
println "error: already connected"
}
def disconnect() {
context.state = new Offline(context)
}
def send_message(message) {
println "\"$message\" sent"
}
def receive_message() {
println "message received"
}
}
client = new Client()
client.send_message("Hello")
client.connect()
client.send_message("Hello")
client.connect()
client.receive_message()
client.disconnect()
Here is the output:
offline error: not connected connected "Hello" sent error: already connected message received offline
One of the great things about a dynamic language like Groovy though is that we can take this example and express it in many different ways depending on our particular needs. Some potential variations for this example are shown below.
Variation 1: Leveraging Interface-Oriented Design
One approach we could take is to leverage Interface-Oriented Design. To do this, we could introduce the following interface:
interface State {
def connect()
def disconnect()
def send_message(message)
def receive_message()
}
Then our Client
, Online
and Offline
classes could be modified to implement that interface, e.g.:
class Client implements State {
// ... as before ...
}
class Online implements State {
// ... as before ...
}
class Offline implements State {
// ... as before ...
}
You might ask: Haven’t we just introduced additional boilerplate code? Can’t we rely on duck-typing for this? The answer is yes and no. We can get away with duck-typing but one of the key intentions of the state pattern is to partition complexity. If we know that the client class and each state class all satisfy one interface, then we have placed some key boundaries around the complexity. We can look at any state class in isolation and know the bounds of behaviour possible for that state.
We don’t have to use interfaces for this, but it helps express the intent of this particular style of partitioning and it helps reduce the size of our unit tests (we would have to have additional tests in place to express this intent in languages which have less support for interface-oriented design).
Variation 2: Extract State Pattern Logic
Alternatively, or in combination with other variations, we might decide to extract some of our State Pattern logic into helper classes. For example, we could define the following classes in a state pattern package/jar/script:
abstract class InstanceProvider {
static def registry = GroovySystem.metaClassRegistry
static def create(objectClass, param) {
registry.getMetaClass(objectClass).invokeConstructor([param] as Object[])
}
}
abstract class Context {
private context
protected setContext(context) {
this.context = context
}
def invokeMethod(String name, Object arg) {
context.invokeMethod(name, arg)
}
def startFrom(initialState) {
setContext(InstanceProvider.create(initialState, this))
}
}
abstract class State {
private client
State(client) { this.client = client }
def transitionTo(nextState) {
client.setContext(InstanceProvider.create(nextState, client))
}
}
This is all quite generic and can be used wherever we want to introduce the state pattern. Here is what our code would look like now:
class Client extends Context {
Client() {
startFrom(Offline)
}
}
class Offline extends State {
Offline(client) {
super(client)
println "offline"
}
def connect() {
transitionTo(Online)
}
def disconnect() {
println "error: not connected"
}
def send_message(message) {
println "error: not connected"
}
def receive_message() {
println "error: not connected"
}
}
class Online extends State {
Online(client) {
super(client)
println "connected"
}
def connect() {
println "error: already connected"
}
def disconnect() {
transitionTo(Offline)
}
def send_message(message) {
println "\"$message\" sent"
}
def receive_message() {
println "message received"
}
}
client = new Client()
client.send_message("Hello")
client.connect()
client.send_message("Hello")
client.connect()
client.receive_message()
client.disconnect()
You can see here the startFrom
and transitionTo
methods begin to give our example code a DSL feel.
Variation 3: Bring on the DSL
Alternatively, or in combination with other variations, we might decide to fully embrace a Domain Specific Language (DSL) approach to this example.
We can define the following generic helper functions (first discussed here):
class Grammar {
def fsm
def event
def fromState
def toState
Grammar(a_fsm) {
fsm = a_fsm
}
def on(a_event) {
event = a_event
this
}
def on(a_event, a_transitioner) {
on(a_event)
a_transitioner.delegate = this
a_transitioner.call()
this
}
def from(a_fromState) {
fromState = a_fromState
this
}
def to(a_toState) {
assert a_toState, "Invalid toState: $a_toState"
toState = a_toState
fsm.registerTransition(this)
this
}
def isValid() {
event && fromState && toState
}
public String toString() {
"$event: $fromState=>$toState"
}
}
class FiniteStateMachine {
def transitions = [:]
def initialState
def currentState
FiniteStateMachine(a_initialState) {
assert a_initialState, "You need to provide an initial state"
initialState = a_initialState
currentState = a_initialState
}
def record() {
Grammar.newInstance(this)
}
def reset() {
currentState = initialState
}
def isState(a_state) {
currentState == a_state
}
def registerTransition(a_grammar) {
assert a_grammar.isValid(), "Invalid transition ($a_grammar)"
def transition
def event = a_grammar.event
def fromState = a_grammar.fromState
def toState = a_grammar.toState
if (!transitions[event]) {
transitions[event] = [:]
}
transition = transitions[event]
assert !transition[fromState], "Duplicate fromState $fromState for transition $a_grammar"
transition[fromState] = toState
}
def fire(a_event) {
assert currentState, "Invalid current state '$currentState': passed into constructor"
assert transitions.containsKey(a_event), "Invalid event '$a_event', should be one of ${transitions.keySet()}"
def transition = transitions[a_event]
def nextState = transition[currentState]
assert nextState, "There is no transition from '$currentState' to any other state"
currentState = nextState
currentState
}
}
Now we can define and test our state machine like this:
class StatePatternDslTest extends GroovyTestCase {
private fsm
protected void setUp() {
fsm = FiniteStateMachine.newInstance('offline')
def recorder = fsm.record()
recorder.on('connect').from('offline').to('online')
recorder.on('disconnect').from('online').to('offline')
recorder.on('send_message').from('online').to('online')
recorder.on('receive_message').from('online').to('online')
}
void testInitialState() {
assert fsm.isState('offline')
}
void testOfflineState() {
shouldFail{
fsm.fire('send_message')
}
shouldFail{
fsm.fire('receive_message')
}
shouldFail{
fsm.fire('disconnect')
}
assert 'online' == fsm.fire('connect')
}
void testOnlineState() {
fsm.fire('connect')
fsm.fire('send_message')
fsm.fire('receive_message')
shouldFail{
fsm.fire('connect')
}
assert 'offline' == fsm.fire('disconnect')
}
}
This example isn’t an exact equivalent of the others. It doesn’t use predefined Online
and Offline
classes. Instead it defines the entire state machine on the fly as needed. See the previous reference for more elaborate examples of this style.
See also: Model-based testing using ModelJUnit
Strategy Pattern
The Strategy Pattern allows you to abstract away particular algorithms from their usage. This allows you to easily swap the algorithm being used without having to change the calling code. The general form of the pattern is:
In Groovy, because of its ability to treat code as a first class object using anonymous methods (which we loosely call Closures), the need for the strategy pattern is greatly reduced. You can simply place algorithms inside Closures.
Example
First let’s look at the traditional way of encapsulating the Strategy Pattern.
interface Calc {
def execute(n, m)
}
class CalcByMult implements Calc {
def execute(n, m) { n * m }
}
class CalcByManyAdds implements Calc {
def execute(n, m) {
def result = 0
n.times{
result += m
}
result
}
}
def sampleData = [
[3, 4, 12],
[5, -5, -25]
]
Calc[] multiplicationStrategies = [
new CalcByMult(),
new CalcByManyAdds()
]
sampleData.each{ data ->
multiplicationStrategies.each { calc ->
assert data[2] == calc.execute(data[0], data[1])
}
}
Here we have defined an interface Calc
which our concrete strategy classes will implement (we could also have used an abstract class). We then defined two algorithms for doing simple multiplication: CalcByMult
the normal way, and CalcByManyAdds
using only addition (don’t try this one using negative numbers - yes we could fix this but it would just make the example longer). We then use normal polymorphism to invoke the algorithms.
Here is the Groovier way to achieve the same thing using Closures:
def multiplicationStrategies = [
{ n, m -> n * m },
{ n, m -> def result = 0; n.times{ result += m }; result }
]
def sampleData = [
[3, 4, 12],
[5, -5, -25]
]
sampleData.each{ data ->
multiplicationStrategies.each { calc ->
assert data[2] == calc(data[0], data[1])
}
}
Template Method Pattern
The Template Method Pattern abstracts away the details of several algorithms. The generic part of an algorithm is contained within a base class. Particular implementation details are captured within base classes. The generic pattern of classes involved looks like this:
Example
In this example, Accumulator
captures the essence of the accumulation algorithm. The base classes Sum
and Product
provide particular customised ways to use the generic accumulation algorithm.
abstract class Accumulator {
protected initial
abstract doAccumulate(total, v)
def accumulate(values) {
def total = initial
values.each { v -> total = doAccumulate(total, v) }
total
}
}
class Sum extends Accumulator {
def Sum() { initial = 0 }
def doAccumulate(total, v) { total + v }
}
class Product extends Accumulator {
def Product() { initial = 1 }
def doAccumulate(total, v) { total * v }
}
println new Sum().accumulate([1,2,3,4])
println new Product().accumulate([1,2,3,4])
The resulting output is:
10 24
In this particular case, you could use Groovy’s inject method to achieve a similar result using Closures:
Closure addAll = { total, item -> total += item }
def accumulated = [1, 2, 3, 4].inject(0, addAll)
println accumulated // => 10
Thanks to duck-typing, this would also work with other objects which support an add (plus() in Groovy) method, e.g.:
In this particular case, you could use Groovy’s inject method to achieve a similar result using Closures:
accumulated = [ "1", "2", "3", "4" ].inject("", addAll)
println accumulated // => "1234"
We could also do the multiplication case as follows:
Closure multAll = { total, item -> total *= item }
accumulated = [1, 2, 3, 4].inject(1, multAll)
println accumulated // => 24
Using closures this way looks more like the Strategy Pattern but if we realise that the built-in inject
method is the generic part of the algorithm for our template method, then the Closures become the customised parts of the template method pattern.
Visitor Pattern
The Visitor Pattern is one of those well-known but not often used patterns. I think this is strange, as it is really a nice thing.
The goal of the pattern is to separate an algorithm from an object structure. A practical result of this separation is the ability to add new operations to existing object structures without modifying those structures.
Simple Example
This example considers how to calculate the bounds of shapes (or collections of shapes). Our first attempt uses the traditional visitor pattern. We will see a more Groovy way to do this shortly.
abstract class Shape { }
class Rectangle extends Shape {
def x, y, width, height
Rectangle(x, y, width, height) {
this.x = x; this.y = y; this.width = width; this.height = height
}
def union(rect) {
if (!rect) return this
def minx = [rect.x, x].min()
def maxx = [rect.x + width, x + width].max()
def miny = [rect.y, y].min()
def maxy = [rect.y + height, y + height].max()
new Rectangle(minx, miny, maxx - minx, maxy - miny)
}
def accept(visitor) {
visitor.visit_rectangle(this)
}
}
class Line extends Shape {
def x1, y1, x2, y2
Line(x1, y1, x2, y2) {
this.x1 = x1; this.y1 = y1; this.x2 = x2; this.y2 = y2
}
def accept(visitor){
visitor.visit_line(this)
}
}
class Group extends Shape {
def shapes = []
def add(shape) { shapes += shape }
def remove(shape) { shapes -= shape }
def accept(visitor) {
visitor.visit_group(this)
}
}
class BoundingRectangleVisitor {
def bounds
def visit_rectangle(rectangle) {
if (bounds)
bounds = bounds.union(rectangle)
else
bounds = rectangle
}
def visit_line(line) {
def line_bounds = new Rectangle(line.x1, line.y1, line.x2-line.y1, line.x2-line.y2)
if (bounds)
bounds = bounds.union(line_bounds)
else
bounds = line_bounds
}
def visit_group(group) {
group.shapes.each { shape -> shape.accept(this) }
}
}
def group = new Group()
group.add(new Rectangle(100, 40, 10, 5))
group.add(new Rectangle(100, 70, 10, 5))
group.add(new Line(90, 30, 60, 5))
def visitor = new BoundingRectangleVisitor()
group.accept(visitor)
bounding_box = visitor.bounds
println bounding_box.dump()
That took quite a bit of code.
We can improve the clarity of our code (and make it about half the size) by making use of Groovy Closures as follows:
abstract class Shape {
def accept(Closure yield) { yield(this) }
}
class Rectangle extends Shape {
def x, y, w, h
def bounds() { this }
def union(rect) {
if (!rect) return this
def minx = [ rect.x, x ].min()
def maxx = [ rect.x + w, x + w ].max()
def miny = [ rect.y, y ].min()
def maxy = [ rect.y + h, y + h ].max()
new Rectangle(x:minx, y:miny, w:maxx - minx, h:maxy - miny)
}
}
class Line extends Shape {
def x1, y1, x2, y2
def bounds() {
new Rectangle(x:[x1, x2].min(), y:[y1, y2].min(), w:(x2 - x1).abs(), h:(y2 - y1).abs())
}
}
class Group {
def shapes = []
def leftShift(shape) { shapes += shape }
def accept(Closure yield) { shapes.each{it.accept(yield)} }
}
def group = new Group()
group << new Rectangle(x:100, y:40, w:10, h:5)
group << new Rectangle(x:100, y:70, w:10, h:5)
group << new Line(x1:90, y1:30, x2:60, y2:5)
def bounds
group.accept{ bounds = it.bounds().union(bounds) }
println bounds.dump()
Advanced Example
interface Visitor {
void visit(NodeType1 n1)
void visit(NodeType2 n2)
}
interface Visitable {
void accept(Visitor visitor)
}
class NodeType1 implements Visitable {
Visitable[] children = new Visitable[0]
void accept(Visitor visitor) {
visitor.visit(this)
for(int i = 0; i < children.length; ++i) {
children[i].accept(visitor)
}
}
}
class NodeType2 implements Visitable {
Visitable[] children = new Visitable[0]
void accept(Visitor visitor) {
visitor.visit(this)
for(int i = 0; i < children.length; ++i) {
children[i].accept(visitor)
}
}
}
class NodeType1Counter implements Visitor {
int count = 0
void visit(NodeType1 n1) {
count++
}
void visit(NodeType2 n2){}
}
If we now use NodeType1Counter
on a tree like this:
NodeType1 root = new NodeType1()
root.children = new Visitable[2]
root.children[0] = new NodeType1()
root.children[1] = new NodeType2()
Then we have one NodeType1
object as root and one of the children is also a NodeType1
instance. The other child is a NodeType2
instance. That means using NodeType1Counter
here should count 2 NodeType1
objects.
As you can see here very good we have a visitor that has a state while the tree of objects is not changed. That’s pretty useful in different areas, for example you could have a visitor counting all node types, or how many different types are used, or you could use methods special to the node to gather information about the tree and much more.
In this case we have to do much work.. we have to change Visitor to accept the new type, we have to write the new type itself of course and we have to change every Visitor we have already implemented. After very few changes you will modify all your Visitors to extend a default implementation of the visitor, so you don’t need to change every Visitor each time you add a new type.
Then you have a problem. since the node describes how to iterate, you have no influence and stop iteration at a point or change the order. So maybe we should change this a little to this:
interface Visitor {
void visit(NodeType1 n1)
void visit(NodeType2 n2)
}
class DefaultVisitor implements Visitor{
void visit(NodeType1 n1) {
for(int i = 0; i < n1.children.length; ++i) {
n1.children[i].accept(this)
}
}
void visit(NodeType2 n2) {
for(int i = 0; i < n2.children.length; ++i) {
n2.children[i].accept(this)
}
}
}
interface Visitable {
void accept(Visitor visitor)
}
class NodeType1 implements Visitable {
Visitable[] children = new Visitable[0]
void accept(Visitor visitor) {
visitor.visit(this)
}
}
class NodeType2 implements Visitable {
Visitable[] children = new Visitable[0];
void accept(Visitor visitor) {
visitor.visit(this)
}
}
class NodeType1Counter extends DefaultVisitor {
int count = 0
void visit(NodeType1 n1) {
count++
super.visit(n1)
}
}
Some small changes but with big effect… the visitor is now recursive and tells me how to iterate. The implementation in the Nodes is minimized to visitor.visit(this)
, DefaultVisitor
is now able to catch the new types, we can stop iteration by not delegating to super. Of course the big disadvantage now is that it is no longer iterative, but you can’t get all the benefits.
The question now is how to make that a bit more Groovy. Didn’t you find this visitor.visit(this)
strange? Why is it there? The answer is to simulate double dispatch. In Java the compile time type is used, so when I visitor.visit(children[i])
then the compiler won’t be able to find the correct method, because Visitor
does not contain a method visit(Visitable)
. And even if it would, we would like to visit the more special methods with NodeType1
or NodeType2
.
Now Groovy is not using the static type, Groovy uses the runtime type. This means I could do visitor.visit(children[i])
directly. Hmm.. since we minimized the accept method to just do the double dispatch part and since the runtime type system of Groovy will already cover that.. do we need the accept method? I think you can guess that I would answer no. But we can do more. We had the disadvantage of not knowing how to handle unknown tree elements. We had to extends the interface Visitor
for that, resulting in changes to DefaultVisitor
and then we have the task to provide a useful default like iterating the node or not doing anything at all. Now with Groovy we can catch that case by adding a visit(Visitable)
method that does nothing. That would be the same in Java btw.
But don’t let us stop here… do we need the Visitor interface? If we don’t have the accept method, then we don’t need the Visitor
interface at all. So the new code would be:
class DefaultVisitor {
void visit(NodeType1 n1) {
n1.children.each { visit(it) }
}
void visit(NodeType2 n2) {
n2.children.each { visit(it) }
}
void visit(Visitable v) { }
}
interface Visitable { }
class NodeType1 implements Visitable {
Visitable[] children = []
}
class NodeType2 implements Visitable {
Visitable[] children = []
}
class NodeType1Counter extends DefaultVisitor {
int count = 0
void visit(NodeType1 n1) {
count++
super.visit(n1)
}
}
Looks like we saved a few lines of code here. But we made more. The Visitable nodes now do not refer to any Visitor
class or interface. For me this is the best level of separation you could get here. But do we really need to stop here? No. Let us change the Visitable
interface a little and let it return the children we want to visit next. This allows us a general iteration method.
class DefaultVisitor {
void visit(Visitable v) {
doIteraton(v)
}
void doIteraton(Visitable v) {
v.children.each {
visit(it)
}
}
}
interface Visitable {
Visitable[] getChildren()
}
class NodeType1 implements Visitable {
Visitable[] children = []
}
class NodeType2 implements Visitable {
Visitable[] children = []
}
class NodeType1Counter extends DefaultVisitor {
int count = 0
void visit(NodeType1 n1) {
count++
super.visit(n1)
}
}
DefaultVisitor
now looks a bit different. I added a doIteration
method that will get the children it should iterate over and then call visit on each element. Per default this will call visit(Visitable)
which then iterates over the children of this child. I changed Visitable
to ensure that any node will be able to return children (even if empty). I didn’t have to change the NodeType1
and NodeType2
class, because the way the children filed was defined already made them a property, which means Groovy is so nice to generate a get method for us. No the really interesting part is NodeType1Counter
, it is interesting because we have not changed it. super.visit(n1)
will now call visit(Visitable)
which will call doIteration
which will start the next level of iteration. So no change. But visit(it)
will call visit(NodeType1)
if it is of type NodeType1
. In fact we don’t need the doIteration
method, we could do that in visit(Visitable)
too, but I thought this variant is better, because it allows us to write a new Visitor
that overwrites visit(Visitable
) for error cases which of course means we must not do super.visit(n1)
but doIteration(n1)
.
In the end we got ~40% less code, a robust and stable architecture and we completely removed the Visitor from the Visitable. I heard about visitor implementations based on Reflection to get a more generic version. Well, with this you see there is really no need to do such thing. If we add new types we don’t need to change anything. It is said that the visitor pattern doesn’t fit extreme programming techniques very well because you need to make changes to so many classes all the time. I think I proved that this is because of Java not because the pattern is bad or something.
There are variants of the Visitor pattern, like the acyclic visitor pattern, that tries to solve the problem of adding new node types with special visitors. I don’t like that very much, it works with casts, catches the ClassCastException
and other nasty things. In the end it tries to solve something we don’t even get with the Groovy version.
One more thing. NodeType1Counter
could be implemented in Java as well. Groovy will recognize the visit methods and call them as needed because DefaultVisitor
is still Groovy and does all the magic.
4.16.2. References
-
Erich Gamma, Richard Helm, Ralph Johnson, John Vlissides (1995). Design Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley. ISBN 0-201-63361-2.
-
The canonical reference of design patterns.
-
-
Martin Fowler (1999). Refactoring: Improving the Design of Existing Code. Addison-Wesley. ISBN 0-201-48567-2.
-
Joshua Kerievsky (2004). Refactoring To Patterns. Addison-Wesley. ISBN 0-321-21335-1.
-
Eric Freeman, Elisabeth Freeman, Kathy Sierra, Bert Bates (2004). Head First Design Patterns. O’Reilly. ISBN 0-596-00712-4. *A great book to read, informative as well as amusing.
-
Dierk Koenig with Andrew Glover, Paul King, Guillaume Laforge and Jon Skeet (2007). Groovy in Action. Manning. ISBN 1-932394-84-2.
-
Discusses Visitor, Builder and other Patterns.
-
-
Brad Appleton (1999). Pizza Inversion - a Pattern for Efficient Resource Consumption.
-
One of the most frequently used patterns by many software engineers!
-
-
Design Patterns in Dynamic Languages by Neil Ford. Houston Java User’s Group. Examples in Groovy and Ruby. http://www.hjug.org/present/Neal_Ford-Design_Patterns_in_Dynamic_Languages-slides.pdf
See also: Refactoring with Groovy.
5. Acknowledgements
5.1. Contributors
The Groovy team would like to thank the contributors of this documentation (by alphabetical order):
5.2. License
This work is licensed under a Creative Commons Attribution-ShareAlike 3.0 Unported License.