This chapter covers the semantics of the Groovy programming language.
1. Statements
1.1. 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.
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1.2. 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
1.2.1. Multiple assignment
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'
1.2.2. Overflow and Underflow
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
1.2.3. Object destructuring with multiple assignment
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. |
1.3. Control structures (WIP)
1.3.1. Conditional structures
if / else
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 {
...
}
switch / case
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.
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when using a closure case value, the default it parameter is actually the switch value (in our example, variable x )
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1.3.2. Looping structures
Classic for loop
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 '
for in loop
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.
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while loop
Groovy supports the usual while {…} loops like Java:
def x = 0
def y = 5
while ( y-- > 0 ) {
x++
}
assert x == 5
1.3.3. Exception handling
Exception handling is the same as Java.
1.3.4. try / catch / finally
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'
}
1.3.5. Multi-catch
With the multi catch block (since Groovy 2.0), we’re able to define several exceptions to be catch and treated by the same catch block:
try {
/* ... */
} catch ( IOException | NullPointerException e ) {
/* one block to handle 2 exceptions */
}
1.4. Power assertion (TBD)
1.5. Labeled statements (TBD)
2. Expressions (TBD)
2.1. GPath expressions (TBD)
3. Promotion and coercion (TBD)
3.1. Number promotion (TBD)
3.2. Closure to type coercion
3.2.1. Assigning a closure to a SAM type
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()
3.2.2. Calling a method accepting a SAM type with a closure
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.
3.2.3. Closure to arbitrary type coercion
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()
3.3. 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
3.4. 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
3.5. 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))
}
}
3.6. 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()
4. Optionality (TBD)
4.1. Optional parentheses (TBD)
4.2. Optional semicolons (TBD)
4.3. Optional return keyword (TBD)
4.4. Optional public keyword (TBD)
5. The Groovy Truth (TBD)
5.1. Customizing the truth with asBoolean() methods (TBD)
6. Typing (WIP)
6.1. 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 .
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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.
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6.2. 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.
6.2.1. The @TypeChecked
annotation
Activating type checking at compile time
The 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.
Skipping sections
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.
6.2.2. Type checking assignments
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 ofB
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 ofB
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 |
|
6.2.3. List and map constructors
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 |
6.2.4. Method resolution
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 ofB
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.
6.2.5. Type inference
Principles
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
.
Variables vs fields in type inference
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.
|
Collection literal type inference
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.
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
.
instanceof inference
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
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.
Advanced type inference
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
.
6.2.6. Closures and type inference
The type checker performs special inference on closures, resulting on additional checks on one side and improved fluency on the other side.
Return type inference
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.
Parameter type inference
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
.
Explicit closure parameters
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.
Parameters inferred from single-abstract method types
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.
The @ClosureParams
annotation
Groovy 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.
6.3. Static compilation (WIP)
6.3.1. Dynamic vs static
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
.
6.3.2. The @CompileStatic
annotation
The @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.
6.3.3. Key benefits
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. |