Index
Lambda Expression
(int a) -> a * 2; // Calculate the double of a
a -> a * 2; // or simply without type
(a, b) -> a + b; // Sum of 2 parameters
If the lambda is more than one expression we can use { } and return
(x, y) -> {
int sum = x + y;
int avg = sum / 2;
return avg;
}
A lambda expression cannot stand alone in Java, it needs to be associated with a functional interface.
interface MyMath {
int getDoubleOf(int a);
}
MyMath d = a -> a * 2; // associated to the interface
d.getDoubleOf(4); // is 8
Note on interface limitations
interface Pair<A, B> {
A first();
B second();
}
A steam of type Stream<Pair<String, Long>> :
stream.sorted(Comparator.comparing(Pair::first)) // okstream.sorted(Comparator.comparing(Pair::first).thenComparing(Pair::second)) // dont work
Java cannot infer type for the .comparing(Pair::first) part and fallback to Object, on which Pair::first cannot be applied.
The required type for the whole expression cannot be propagated through the method call (.thenComparing) and used to infer the type of the first part.
Type must be given explicitly.
stream.sorted(
Comparator.<Pair<String, Long>, String>comparing(Pair::first)
.thenComparing(Pair::second)
) // ok
All examples with "list" use :
List<String> list = [Bohr, Darwin, Galilei, Tesla, Einstein, Newton]
Collections
sort sort(list, comparator)
list.sort((a, b) -> a.length() - b.length())
list.sort(Comparator.comparing(n -> n.length())); // same
list.sort(Comparator.comparing(String::length)); // same
//> [Bohr, Tesla, Darwin, Newton, Galilei, Einstein]
removeIf
list.removeIf(w -> w.length() < 6);
//> [Darwin, Galilei, Einstein, Newton]
merge
merge(key, value, remappingFunction)
Map<String, String> names = new HashMap<>();
names.put("Albert", "Ein?");
names.put("Marie", "Curie");
names.put("Max", "Plank");
// Value "Albert" exists
// {Marie=Curie, Max=Plank, Albert=Einstein}
names.merge("Albert", "stein", (old, val) -> old.substring(0, 3) + val);
// Value "Newname" don't exists
// {Marie=Curie, Newname=stein, Max=Plank, Albert=Einstein}
names.merge("Newname", "stein", (old, val) -> old.substring(0, 3) + val);
Method Expressions
Allows to reference methods (and constructors) without executing them
// Lambda Form:
getPrimes(numbers, a -> StaticMethod.isPrime(a));
// Method Reference:
getPrimes(numbers, StaticMethod::isPrime);
| Method Reference | Lambda Form |
|---|---|
StaticMethod::isPrime |
n -> StaticMethod.isPrime(n) |
String::toUpperCase |
(String w) -> w.toUpperCase() |
String::compareTo |
(String s, String t) -> s.compareTo(t) |
System.out::println |
x -> System.out.println(x) |
Double::new |
n -> new Double(n) |
String[]::new |
(int n) -> new String[n] |
Streams
Similar to collections, but
- They don't store their own data
- The data comes from elsewhere (collection, file, db, web, ...)
- immutable (produce new streams)
- lazy (only computes what is necessary !)
// Will compute just 3 "filter"
Stream<String> longNames = list
.filter(n -> n.length() > 8)
.limit(3);
Create a new stream
Stream<Integer> stream = Stream.of(1, 2, 3, 5, 7, 11);
Stream<String> stream = Stream.of("Jazz", "Blues", "Rock");
Stream<String> stream = Stream.of(myArray); // or from an array
list.stream(); // or from a list
// Infinit stream [0; inf[
Stream<Integer> integers = Stream.iterate(0, n -> n + 1);
Collecting results
// Collect into an array (::new is the constructor reference)
String[] myArray = stream.toArray(String[]::new);
// Collect into a List or Set
List<String> myList = stream.collect(Collectors.toList());
Set<String> mySet = stream.collect(Collectors.toSet());
// Collect into a String
String str = list.collect(Collectors.joining(", "));
map map(mapper)
Applying a function to each element
// Apply "toLowerCase" for each element
res = stream.map(w -> w.toLowerCase());
res = stream.map(String::toLowerCase);
//> bohr darwin galilei tesla einstein newton
res = Stream.of(1,2,3,4,5).map(x -> x + 1);
//> 2 3 4 5 6
filter filter(predicate)
Retains elements that match the predicate
// Filter elements that begin with "E"
res = stream.filter(n -> n.substring(0, 1).equals("E"));
//> Einstein
res = Stream.of(1,2,3,4,5).filter(x -> x < 3);
//> 1 2
reduce
Reduce the elements to a single value
String reduced = stream
.reduce("", (acc, el) -> acc + "|" + el);
//> |Bohr|Darwin|Galilei|Tesla|Einstein|Newton
limit limit(maxSize)
The n first elements
res = stream.limit(3);
//> Bohr Darwin Galilei
skip
Discarding the first n elements
res = strem.skip(2); // skip Bohr and Darwin
//> Galilei Tesla Einstein Newton
distinct
Remove duplicated elements
res = Stream.of(1,0,0,1,0,1).distinct();
//> 1 0
sorted
Sort elements (must be Comparable)
res = stream.sorted();
//> Bohr Darwin Einstein Galilei Newton Tesla
allMatch
// Check if there is a "e" in each elements
boolean res = words.allMatch(n -> n.contains("e"));
anyMatch: Check if there is a "e" in an element
noneMatch: Check if there is no "e" in elements
parallel
Returns an equivalent stream that is parallel
findAny
faster than findFirst on parallel streams
Primitive-Type Streams
Wrappers (like Stream) are inefficient. It requires a lot of unboxing and boxing for each element. Better to use IntStream, DoubleStream, etc.
Creation
IntStream stream = IntStream.of(1, 2, 3, 5, 7);
stream = IntStream.of(myArray); // from an array
stream = IntStream.range(5, 80); // range from 5 to 80
Random gen = new Random();
IntStream rand = gen(1, 9); // stream of randoms
Use mapToX (mapToObj, mapToDouble, etc.) if the function yields Object, double, etc. values.
Grouping Results
Collectors.groupingBy
// Groupe by length
Map<Integer, List<String>> groups = stream
.collect(Collectors.groupingBy(w -> w.length()));
//> 4=[Bohr], 5=[Tesla], 6=[Darwin, Newton], ...
Collectors.toSet
// Same as before but with Set
... Collectors.groupingBy(
w -> w.substring(0, 1), Collectors.toSet()) ...
Collectors.counting
Count the number of values in a group
Collectors.summing__
summingInt, summingLong, summingDouble to sum group values
Collectors.averaging__
averagingInt, averagingLong, ...
// Average length of each element of a group
Collectors.averagingInt(String::length)
PS: Don't forget Optional (like Map<T, Optional<T>>) with some Collection methods (like Collectors.maxBy).
Parallel Streams
Creation
Stream<String> parStream = list.parallelStream();
Stream<String> parStream = Stream.of(myArray).parallel();
unordered
Can speed up the limit or distinct
stream.parallelStream().unordered().distinct();
PS: Work with the streams library. Eg. use filter(x -> x.length() < 9) instead of a forEach with an if.
Optional
In Java, it is common to use null to denote the absence of a result.
Problems when no checks: NullPointerException.
// Optional<String> contains a string or nothing
Optional<String> res = stream
.filter(w -> w.length() > 10)
.findFirst();
// length of the value or "" if nothing
int length = res.orElse("").length();
// run the lambda if there is a value
res.ifPresent(v -> results.add(v));
Return an Optional
Optional<Double> squareRoot(double x) {
if (x >= 0) { return Optional.of(Math.sqrt(x)); }
else { return Optional.empty(); }
}
Top comments (0)