There are functions in the Kotlin stdlib for average, count, distinct,filtering, finding, grouping, joining, mapping, min, max, partitioning, slicing, sorting, summing, to/from arrays, to/from lists, to/from maps, union, co-iteration, all the functional paradigms, and more. So you can use those to create little 1-liners and there is no need to use the more complicated syntax of Java 8.
I think the only thing missing from the built-in Java 8 Collectors class is summarization (but in another answer to this question is a simple solution).
One thing missing from both is batching by count, which is seen in another Stack Overflow answer and has a simple answer as well. Another interesting case is this one also from Stack Overflow: Idiomatic way to spilt sequence into three lists using Kotlin. And if you want to create something like Stream.collect for another purpose, see Custom Stream.collect in Kotlin
EDIT 11.08.2017: Chunked/windowed collection operations were added in kotlin 1.2 M2, see https://blog.jetbrains.com/kotlin/2017/08/kotlin-1-2-m2-is-out/
It is always good to explore the API Reference for kotlin.collections as a whole before creating new functions that might already exist there.
Here are some conversions from Java 8 Stream.collect examples to the equivalent in Kotlin:
Accumulate names into a List
// Java:
List<String> list = people.stream().map(Person::getName).collect(Collectors.toList());
// Kotlin:
val list = people.map { it.name } // toList() not needed
Convert elements to strings and concatenate them, separated by commas
// Java:
String joined = things.stream()
.map(Object::toString)
.collect(Collectors.joining(", "));
// Kotlin:
val joined = things.joinToString(", ")
Compute sum of salaries of employee
// Java:
int total = employees.stream()
.collect(Collectors.summingInt(Employee::getSalary)));
// Kotlin:
val total = employees.sumBy { it.salary }
Group employees by department
// Java:
Map<Department, List<Employee>> byDept
= employees.stream()
.collect(Collectors.groupingBy(Employee::getDepartment));
// Kotlin:
val byDept = employees.groupBy { it.department }
Compute sum of salaries by department
// Java:
Map<Department, Integer> totalByDept
= employees.stream()
.collect(Collectors.groupingBy(Employee::getDepartment,
Collectors.summingInt(Employee::getSalary)));
// Kotlin:
val totalByDept = employees.groupBy { it.dept }.mapValues { it.value.sumBy { it.salary }}
Partition students into passing and failing
// Java:
Map<Boolean, List<Student>> passingFailing =
students.stream()
.collect(Collectors.partitioningBy(s -> s.getGrade() >= PASS_THRESHOLD));
// Kotlin:
val passingFailing = students.partition { it.grade >= PASS_THRESHOLD }
Names of male members
// Java:
List<String> namesOfMaleMembers = roster
.stream()
.filter(p -> p.getGender() == Person.Sex.MALE)
.map(p -> p.getName())
.collect(Collectors.toList());
// Kotlin:
val namesOfMaleMembers = roster.filter { it.gender == Person.Sex.MALE }.map { it.name }
Group names of members in roster by gender
// Java:
Map<Person.Sex, List<String>> namesByGender =
roster.stream().collect(
Collectors.groupingBy(
Person::getGender,
Collectors.mapping(
Person::getName,
Collectors.toList())));
// Kotlin:
val namesByGender = roster.groupBy { it.gender }.mapValues { it.value.map { it.name } }
Filter a list to another list
// Java:
List<String> filtered = items.stream()
.filter( item -> item.startsWith("o") )
.collect(Collectors.toList());
// Kotlin:
val filtered = items.filter { it.startsWith('o') }
Finding shortest string a list
// Java:
String shortest = items.stream()
.min(Comparator.comparing(item -> item.length()))
.get();
// Kotlin:
val shortest = items.minBy { it.length }
Counting items in a list after filter is applied
// Java:
long count = items.stream().filter( item -> item.startsWith("t")).count();
// Kotlin:
val count = items.filter { it.startsWith('t') }.size
// but better to not filter, but count with a predicate
val count = items.count { it.startsWith('t') }
and on it goes... In all cases, no special fold, reduce, or other functionality was required to mimic Stream.collect. If you have further use cases, add them in comments and we can see!
About laziness
If you want to lazy process a chain, you can convert to a Sequence using asSequence() before the chain. At the end of the chain of functions, you usually end up with a Sequence as well. Then you can use toList(), toSet(), toMap() or some other function to materialize the Sequence at the end.
// switch to and from lazy
val someList = items.asSequence().filter { ... }.take(10).map { ... }.toList()
// switch to lazy, but sorted() brings us out again at the end
val someList = items.asSequence().filter { ... }.take(10).map { ... }.sorted()
Why are there no Types?!?
You will notice the Kotlin examples do not specify the types. This is because Kotlin has full type inference and is completely type safe at compile time. More so than Java because it also has nullable types and can help prevent the dreaded NPE. So this in Kotlin:
val someList = people.filter { it.age <= 30 }.map { it.name }
is the same as:
val someList: List<String> = people.filter { it.age <= 30 }.map { it.name }
Because Kotlin knows what people is, and that people.age is Int therefore the filter expression only allows comparison to an Int, and that people.name is a String therefore the map step produces a List<String> (readonly List of String).
Now, if people were possibly null, as-in a List<People>? then:
val someList = people?.filter { it.age <= 30 }?.map { it.name }
Returns a List<String>? that would need to be null checked (or use one of the other Kotlin operators for nullable values, see this Kotlin idiomatic way to deal with nullable values and also Idiomatic way of handling nullable or empty list in Kotlin)
See also:
