Swift’s randomness API is powerful and simple to use. It allows us to create random values from many basic types, such as booleans and numeric types, and it allows us to randomly shuffle arrays and pluck random elements from collections.
However, it does not make it easy for us to extend the randomness API, nor does it provide an API that is composable, which would allow us to create complex types of randomness from simpler pieces.
Gen is a lightweight wrapper over Swift’s randomness APIs that makes it easy to build custom generators of any kind of value.
Examples
Gen’s namesake type, Gen, is responsible for producing random values. Most often you will reach for one of the static variables inside Gen to get access to a Gen value:
Gen.bool
// Gen<Bool>
Rather than immediately producing a random value, Gen describes a random value that can be produced by calling its run method:
Every random function that comes with Swift is also available as a static function on Gen:
Swift’s API
Gen’s API
Int.random(in: 0...9)
Gen.int(in: 0...9)
Double.random(in: 0...9)
Gen.double(in: 0...9)
Bool.random()
Gen.bool
[1, 2, 3].randomElement()
Gen.element(of: [1, 2, 3])
[1, 2, 3].shuffled()
Gen.shuffle([1, 2, 3])
The reason it is powerful to wrap randomness in the Gen type is that we can make the Gen type composable. For example, a generator of integers can be turned into a generator of numeric strings with a simple application of the map function:
Already this is a form of randomness that Swift’s API’s do not provide out of the box.
Gen provides many operators for generating new types of randomness, such as map, flatMap and zip, as well as helper functions for generating random arrays, sets, dictionaries, strings, distributions and more! A random password generator, for example, is just a few operators away.
// Take a generator of random letters and numbers.
let password = Gen.letterOrNumber
// Generate 6-character strings of them.
.string(of: .always(6))
// Generate 3 segments of these strings.
.array(of: .always(3))
// And join them.
.map { $0.joined(separator: "-") }
password.run() // "9BiGYA-fmvsOf-VYDtDv"
password.run() // "dS2MGr-FQSuC4-ZLEicl"
password.run() // "YusZGF-HILrCo-rNGfCA"
This kind of composition makes it simple to generate random values of anything.
// Use `zip` to combine generators together and build structures.
let randomPoint = zip(.int(in: -10...10), .int(in: -10...10))
.map(CGPoint.init(x:y:))
// Gen<CGPoint>
But composability isn’t the only reason the Gen type shines. By delaying the creation of random values until the run method is invoked, we allow ourselves to control randomness in circumstances where we need determinism, such as tests. The run method has an overload that takes a RandomNumberGenerator value, which is Swift’s protocol that powers their randomness API. By default it uses the SystemRandomNumberGenerator, which is a good source of randomness, but we can also provide a seedable “pseudo” random number generator, so that we can get predictable results in tests:
This means you don’t have to sacrifice testability when leveraging randomness in your application.
For more examples of using Gen to build complex randomness, see our blog post on creating a Zalgo generator and our two-part video series (part 1 and part 2) on creating generative art.
Installation
If you want to use Gen in a project that uses SwiftPM, it’s as simple as adding a dependencies clause to your Package.swift:
These concepts (and more) are explored thoroughly in Point-Free, a video series exploring functional programming and Swift hosted by Brandon Williams and Stephen Celis.
The design of this library was explored in the following Point-Free episodes:
🎱 Gen
Composable, transformable, controllable randomness.
Table of Contents
Motivation
Swift’s randomness API is powerful and simple to use. It allows us to create random values from many basic types, such as booleans and numeric types, and it allows us to randomly shuffle arrays and pluck random elements from collections.
However, it does not make it easy for us to extend the randomness API, nor does it provide an API that is composable, which would allow us to create complex types of randomness from simpler pieces.
Gen is a lightweight wrapper over Swift’s randomness APIs that makes it easy to build custom generators of any kind of value.
Examples
Gen’s namesake type,
Gen
, is responsible for producing random values. Most often you will reach for one of the static variables insideGen
to get access to aGen
value:Rather than immediately producing a random value,
Gen
describes a random value that can be produced by calling itsrun
method:Every random function that comes with Swift is also available as a static function on
Gen
:Int.random(in: 0...9)
Gen.int(in: 0...9)
Double.random(in: 0...9)
Gen.double(in: 0...9)
Bool.random()
Gen.bool
[1, 2, 3].randomElement()
Gen.element(of: [1, 2, 3])
[1, 2, 3].shuffled()
Gen.shuffle([1, 2, 3])
The reason it is powerful to wrap randomness in the
Gen
type is that we can make theGen
type composable. For example, a generator of integers can be turned into a generator of numeric strings with a simple application of themap
function:Already this is a form of randomness that Swift’s API’s do not provide out of the box.
Gen provides many operators for generating new types of randomness, such as
map
,flatMap
andzip
, as well as helper functions for generating random arrays, sets, dictionaries, strings, distributions and more! A random password generator, for example, is just a few operators away.This kind of composition makes it simple to generate random values of anything.
But composability isn’t the only reason the
Gen
type shines. By delaying the creation of random values until therun
method is invoked, we allow ourselves to control randomness in circumstances where we need determinism, such as tests. Therun
method has an overload that takes aRandomNumberGenerator
value, which is Swift’s protocol that powers their randomness API. By default it uses theSystemRandomNumberGenerator
, which is a good source of randomness, but we can also provide a seedable “pseudo” random number generator, so that we can get predictable results in tests:This means you don’t have to sacrifice testability when leveraging randomness in your application.
For more examples of using Gen to build complex randomness, see our blog post on creating a Zalgo generator and our two-part video series (part 1 and part 2) on creating generative art.
Installation
If you want to use Gen in a project that uses SwiftPM, it’s as simple as adding a
dependencies
clause to yourPackage.swift
:Interested in learning more?
These concepts (and more) are explored thoroughly in Point-Free, a video series exploring functional programming and Swift hosted by Brandon Williams and Stephen Celis.
The design of this library was explored in the following Point-Free episodes:
License
All modules are released under the MIT license. See LICENSE for details.