Functional patterns for Java 8
Lambda was born out of a desire to use some of the same canonical functions (e.g. unfoldr, takeWhile, zipWith) and functional patterns (e.g. Functor and friends) that are idiomatic in other languages and make them available for Java.
Some things a user of lambda most likely values:
- Lazy evaluation
- Immutability by design
- Composition
- Higher-level abstractions
- Parametric polymorphism
Generally, everything that lambda produces is lazily-evaluated (except for terminal operations like reduce), immutable (except for Iterators, since it's effectively impossible), composable (even between different arities, where possible), foundational (maximally contravariant), and parametrically type-checked (even where this adds unnecessary constraints due to a lack of higher-kinded types).
Although the library is currently (very) small, these values should always be the driving forces behind future growth.
Add the following dependency to your:
pom.xml (Maven):
<dependency>
<groupId>com.jnape.palatable</groupId>
<artifactId>lambda</artifactId>
<version>1.5.4</version>
</dependency>build.gradle (Gradle):
compile group: 'com.jnape.palatable', name: 'lambda', version: '1.5.4'First, the obligatory map/filter/reduce example:
Integer sumOfEvenIncrements =
reduceLeft((x, y) -> x + y,
filter(x -> x % 2 == 0,
map(x -> x + 1, asList(1, 2, 3, 4, 5))));
//-> 12Every function in lambda is curried, so we could have also done this:
Fn1<Iterable<Integer>, Integer> sumOfEvenIncrementsFn =
map((Integer x) -> x + 1)
.then(filter(x -> x % 2 == 0))
.then(reduceLeft((x, y) -> x + y));
Integer sumOfEvenIncrements = sumOfEvenIncrementsFn.apply(asList(1, 2, 3, 4, 5));
//-> 12How about the positive squares below 100:
Iterable<Integer> positiveSquaresBelow100 =
takeWhile(x -> x < 100, map(x -> x * x, iterate(x -> x + 1, 1)));
//-> [1, 4, 9, 16, 25, 36, 49, 64, 81]We could have also used unfoldr:
Iterable<Integer> positiveSquaresBelow100 = unfoldr(x -> {
int square = x * x;
return square < 100 ? Optional.of(tuple(square, x + 1)) : Optional.empty();
}, 1);
//-> [1, 4, 9, 16, 25, 36, 49, 64, 81]What if we want the cross product of a domain and codomain:
Iterable<Tuple2<Integer, String>> crossProduct =
take(10, cartesianProduct(asList(1, 2, 3), asList("a", "b", "c")));
//-> (1,"a"), (1,"b"), (1,"c"), (2,"a"), (2,"b"), (2,"c"), (3,"a"), (3,"b"), (3,"c")Let's compose two functions:
Fn1<Integer, Integer> add = x -> x + 1;
Fn1<Integer, Integer> subtract = x -> x -1;
Fn1<Integer, Integer> noOp = add.then(subtract);
// same as
Fn1<Integer, Integer> alsoNoOp = subtract.compose(add);And partially apply some:
Fn2<Integer, Integer, Integer> add = (x, y) -> x + y;
Fn1<Integer, Integer> add1 = add.apply(1);
add1.apply(2);
//-> 3And have fun with 3s:
Iterable<Iterable<Integer>> multiplesOf3InGroupsOf3 =
take(10, inGroupsOf(3, unfoldr(x -> Optional.of(tuple(x * 3, x + 1)), 1)));
//-> [[3, 6, 9], [12, 15, 18], [21, 24, 27]]Check out the tests or javadoc for more examples.
In addition to the functions above, lambda also supports a few first-class algebraic data types.
HLists are type-safe heterogeneous lists, meaning they can store elements of different types in the same list while facilitating certain type-safe interactions.
The following illustrates how the linear expansion of the recursive type signature for HList prevents ill-typed expressions:
HCons<Integer, HCons<String, HNil>> hList = HList.cons(1, HList.cons("foo", HList.nil()));
System.out.println(hList.head()); // prints 1
System.out.println(hList.tail().head()); // prints "foo"
HNil nil = hList.tail().tail();
//nil.head() won't type-checkOne of the primary downsides to using HLists in Java is how quickly the type signature grows.
To address this, tuples in lambda are specializations of HLists up to 5 elements deep, with added support for index-based accessor methods.
HNil nil = HList.nil();
SingletonHList<Integer> singleton = nil.cons(5);
Tuple2<Integer, Integer> tuple2 = singleton.cons(4);
Tuple3<Integer, Integer, Integer> tuple3 = tuple2.cons(3);
Tuple4<Integer, Integer, Integer, Integer> tuple4 = tuple3.cons(2);
Tuple5<Integer, Integer, Integer, Integer, Integer> tuple5 = tuple4.cons(1);
System.out.println(tuple2._1()); // prints 4
System.out.println(tuple5._5()); // prints 5Additionally, HList provides convenience static factory methods for directly constructing lists of up to 5 elements:
SingletonHList<Integer> singleton = HList.singletonHList(1);
Tuple2<Integer, Integer> tuple2 = HList.tuple(1, 2);
Tuple3<Integer, Integer, Integer> tuple3 = HList.tuple(1, 2, 3);
Tuple4<Integer, Integer, Integer, Integer> tuple4 = HList.tuple(1, 2, 3, 4);
Tuple5<Integer, Integer, Integer, Integer, Integer> tuple5 = HList.tuple(1, 2, 3, 4, 5);Index can be used for type-safe retrieval and updating of elements at specific indexes:
HCons<Integer, HCons<String, HCons<Character, HNil>>> hList = cons(1, cons("2", cons('3', nil())));
HCons<Integer, Tuple2<String, Character>> tuple = tuple(1, "2", '3');
Tuple5<Integer, String, Character, Double, Boolean> longerHList = tuple(1, "2", '3', 4.0d, false);
Index<Character, HCons<Integer, ? extends HCons<String, ? extends HCons<Character, ?>>>> characterIndex =
Index.<Character>index().<String>after().after();
characterIndex.get(hList); // '3'
characterIndex.get(tuple); // '3'
characterIndex.get(longerHList); // '3'
characterIndex.set('4', hList); // HList{ 1 :: "2" :: '4' }Finally, all Tuple* classes are instances of both Functor and Bifunctor:
Tuple2<Integer, String> mappedTuple2 = tuple(1, 2).biMap(x -> x + 1, Object::toString);
System.out.println(mappedTuple2._1()); // prints 2
System.out.println(mappedTuple2._2()); // prints "2"
Tuple3<String, Boolean, Integer> mappedTuple3 = tuple("foo", true, 1).biMap(x -> !x, x -> x + 1);
System.out.println(mappedTuple3._1()); // prints "foo"
System.out.println(mappedTuple3._2()); // prints false
System.out.println(mappedTuple3._3()); // prints 2HMaps are type-safe heterogeneous maps, meaning they can store mappings to different value types in the same map; however, whereas HLists encode value types in their type signatures, HMaps rely on the keys to encode the value type that they point to.
TypeSafeKey<String> stringKey = TypeSafeKey.typeSafeKey();
TypeSafeKey<Integer> intKey = TypeSafeKey.typeSafeKey();
HMap hmap = HMap.hMap(stringKey, "string value",
intKey, 1);
Optional<String> stringValue = hmap.get(stringKey); // Optional["string value"]
Optional<Integer> intValue = hmap.get(intKey); // Optional[1]
Optional<Integer> anotherIntValue = hmap.get(anotherIntKey); // Optional.emptyCoProducts generalize unions of disparate types in a single consolidated type.
CoProduct3<String, Integer, Character> string = CoProduct3.a("string");
CoProduct3<String, Integer, Character> integer = CoProduct3.b(1);
CoProduct3<String, Integer, Character> character = CoProduct3.c('a');Rather than supporting explicit value unwrapping, which would necessarily jeopardize type safety, CoProducts support a match method that takes one function per possible value type and maps it to a final common result type:
CoProduct3<String, Integer, Character> string = CoProduct3.a("string");
CoProduct3<String, Integer, Character> integer = CoProduct3.b(1);
CoProduct3<String, Integer, Character> character = CoProduct3.c('a');
Integer result = string.<Integer>match(String::length, identity(), Character::charCount); // 6Additionally, because a CoProduct2<A, B> guarantees a subset of a CoProduct3<A, B, C>, the diverge method exists between CoProduct types of single magnitude differences to make it easy to use a more convergent CoProduct where a more divergent CoProduct is expected:
CoProduct2<String, Integer> coProduct2 = CoProduct2.a("string");
CoProduct3<String, Integer, Character> coProduct3 = coProduct2.diverge(); // still just the coProduct2 value, adapted to the coProduct3 shapeThere are CoProduct specializations for type unions of up to 5 different types: CoProduct2 through CoProduct5, respectively.
Either<L, R> represents a specialized CoProduct2<L, R>, which resolve to one of two possible values: a left value wrapping an L, or a right value wrapping an R (typically an exceptional value or a successful value, respectively).
As with CoProduct2, rather than supporting explicit value unwrapping, Either supports many useful comprehensions to help facilitate type-safe interactions:
Either<String, Integer> right = Either.right(1);
Either<String, Integer> left = Either.left("Head fell off");
Integer result = right.orElse(-1);
//-> 1
List<Integer> values = left.match(l -> Collections.emptyList(), Collections::singletonList);
//-> [] Check out the tests for more examples of ways to interact with Either.
Lambda also ships with a first-class lens type, as well as a small library of useful general lenses:
Lens<List<String>, List<String>, Optional<String>, String> stringAt0 = ListLens.at(0);
List<String> strings = asList("foo", "bar", "baz");
view(stringAt0, strings); // Optional[foo]
set(stringAt0, "quux", strings); // [quux, bar, baz]
over(stringAt0, s -> s.map(String::toUpperCase).orElse(""), strings); // [FOO, bar, baz]There are three functions that lambda provides that interface directly with lenses: view, over, and set. As the name implies, view and set are used to retrieve values and store values, respectively, whereas over is used to apply a function to the value a lens is focused on, alter it, and store it (you can think of set as a specialization of over using constantly).
Lenses can be easily created. Consider the following Person class:
public final class Person {
private final int age;
public Person(int age) {
this.age = age;
}
public int getAge() {
return age;
}
public Person setAge(int age) {
return new Person(age);
}
public Person setAge(LocalDate dob) {
return setAge((int) YEARS.between(dob, LocalDate.now()));
}
}...and a lens for getting and setting age as an int:
Lens<Person, Person, Integer, Integer> ageLensWithInt = Lens.lens(Person::getAge, Person::setAge);
//or, when each pair of type arguments match...
Lens.Simple<Person, Integer> alsoAgeLensWithInt = Lens.simpleLens(Person::getAge, Person::setAge);If we wanted a lens for the LocalDate version of setAge, we could use the same method references and only alter the type signature:
Lens<Person, Person, Integer, LocalDate> ageLensWithLocalDate = Lens.lens(Person::getAge, Person::setAge);Compatible lenses can be trivially composed:
Lens<List<Integer>, List<Integer>, Optional<Integer>, Integer> at0 = ListLens.at(0);
Lens<Map<String, List<Integer>>, Map<String, List<Integer>>, List<Integer>, List<Integer>> atFoo = MapLens.atKey("foo", emptyList());
view(atFoo.andThen(at0), singletonMap("foo", asList(1, 2, 3))); // Optional[1]Lens provides independent map operations for each parameter, so incompatible lenses can also be composed:
Lens<List<Integer>, List<Integer>, Optional<Integer>, Integer> at0 = ListLens.at(0);
Lens<Map<String, List<Integer>>, Map<String, List<Integer>>, Optional<List<Integer>>, List<Integer>> atFoo = MapLens.atKey("foo");
Lens<Map<String, List<Integer>>, Map<String, List<Integer>>, Optional<Integer>, Integer> composed =
atFoo.mapA(optL -> optL.orElse(singletonList(-1)))
.andThen(at0);
view(composed, singletonMap("foo", emptyList())); // Optional.emptyCheck out the tests or the javadoc for more info.
Wherever possible, lambda maintains interface compatibility with similar, familiar core Java types. Some examples of where this works well is with both Fn1 and Predicate, which extend j.u.f.Function and j.u.f.Predicate, respectively. In these examples, they also override any implemented methods to return their lambda-specific counterparts (Fn1.compose returning Fn1 instead of j.u.f.Function as an example).
Unfortunately, due to Java's type hierarchy and inheritance inconsistencies, this is not always possible. One surprising example of this is how Fn1 extends j.u.f.Function, but Fn2 does not extend j.u.f.BiFunction. This is because j.u.f.BiFunction itself does not extend j.u.f.Function, but it does define methods that collide with j.u.f.Function. For this reason, both Fn1 and Fn2 cannot extend their Java counterparts without sacrificing their own inheritance hierarchy. These types of asymmetries are, unfortunately, not uncommon; however, wherever these situations arise, measures are taken to attempt to ease the transition in and out of core Java types (in the case of Fn2, a supplemental #toBiFunction method is added). I do not take these inconveniences for granted, and I'm regularly looking for ways to minimize the negative impact of this as much as possible. Suggestions and use cases that highlight particular pain points here are particularly appreciated.
lambda is part of palatable, which is distributed under The MIT License.