The collections framework is the heart of the Scala 2.13 standard library, also used in Scala 3.x. It provides a common, uniform, and all-encompassing framework for collection types. This framework enables you to work with data in memory at a high level, with the basic building blocks of a program being whole collections, instead of individual elements.

This style of programming requires some learning. Fortunately, the adaptation is helped by several nice properties of the Scala collections. They are easy to use, concise, safe, fast, universal.

Easy to use: A small vocabulary of 20-50 methods is enough to solve most collection problems in a couple of operations. No need to wrap your head around complicated looping structures or recursions. Persistent collections and side-effect-free operations mean that you need not worry about accidentally corrupting existing collections with new data. Interference between iterators and collection updates is eliminated.

Concise: You can achieve with a single word what used to take one or several loops. You can express functional operations with lightweight syntax and combine operations effortlessly, so that the result feels like a custom algebra.

Safe: This one has to be experienced to sink in. The statically typed and functional nature of Scala’s collections means that the overwhelming majority of errors you might make are caught at compile-time. The reason is that (1) the collection operations themselves are heavily used and therefore well tested. (2) the usages of the collection operation make inputs and output explicit as function parameters and results. (3) These explicit inputs and outputs are subject to static type checking. The bottom line is that the large majority of misuses will manifest themselves as type errors. It’s not at all uncommon to have programs of several hundred lines run at first try.

Fast: Collection operations are tuned and optimized in the libraries. As a result, using collections is typically quite efficient. You might be able to do a little better with carefully hand-tuned data structures and operations, but you might also do a lot worse by making some suboptimal implementation decisions along the way.

Parallel: The scala-parallel-collections module provides parallel execution of collections operations across multiple cores. Parallel collections generally support the same operations as sequential ones. You can turn a sequential collection into a parallel one simply by invoking the par method.

Universal: Collections provide the same operations on any type where it makes sense to do so. So you can achieve a lot with a fairly small vocabulary of operations. For instance, a string is conceptually a sequence of characters. Consequently, in Scala collections, strings support all sequence operations. The same holds for arrays.

Example: Here’s one line of code that demonstrates many of the advantages of Scala’s collections.

val (minors, adults) = people partition (_.age < 18)

It’s immediately clear what this operation does: It partitions a collection of people into minors and adults depending on their age. Because the partition method is defined in the root collection type IterableOps, this code works for any kind of collection, including arrays. The resulting minors and adults collections will be of the same type as the people collection.

This code is much more concise than the one to three loops required for traditional collection processing (three loops for an array, because the intermediate results need to be buffered somewhere else). Once you have learned the basic collection vocabulary you will also find writing this code is much easier and safer than writing explicit loops.

Furthermore, the partition operation is quite fast, and can be even faster on parallel collections on multiple cores.

This document provides an in depth discussion of the APIs of the Scala collections classes from a user’s perspective. It takes you on a tour of all the fundamental classes and the methods they define.

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