Make Go functional with dogs

Overview

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Make Go functional with dogs

Caution

This is a highly-experimental package. Any changes will be made in a backward-incompatible manner.

This package will not compile without gotip since type parameters are not supported currently in any of Go releases.

Probably you don't need this even after type parameters becomes GA. Even if you feel you do, maybe you shouldn't use this. It's against Go's philosophy.

Features

We will continue to implement more utility types and functions.

Type classes

  • Eq
  • Ord
  • Semigroup
  • Monoid

Data types

  • Pair
  • List
  • Slice
  • Map
  • Set
  • Iterator

Examples

More examples here.

FizzBuzz

func main() {
	monoid := option.DeriveMonoid[string](algebra.DeriveAdditiveSemigroup[string]())
	fizzBuzz := func(i int) string {
		fizz := option.Filter(option.Some[string]("Fizz"), func(_ string) bool { return i%3 == 0 })
		buzz := option.Filter(option.Some[string]("Buzz"), func(_ string) bool { return i%5 == 0 })
		return option.UnwrapOr(monoid.Combine(fizz, buzz), fmt.Sprint(i))
	}
	it := iterator.Map(iterator.Range[int](1, 15), fizzBuzz)
	iterator.ForEach(it, func(s string) { fmt.Println(s) })
}

Fibonacci

func main() {
	type Pair = pair.Pair[int, int]
	it := iterator.Unfold(
		Pair{1, 1},
		func(p Pair) (Pair, int, bool) {
			a, b := p.Values()
			return Pair{b, a + b}, a, true
		},
	)
	iterator.ForEach(
		iterator.Take(it, 5),
		func(i int) { fmt.Println(i) },
	)
}

Acknowledgements

This library is inspired mainly by:

and many other functional languages.

License

Distributed under the Apache License, Version 2.0. See LICENSE for more information.

Comments
  • Examples needed.

    Examples needed.

    Hello @genkami!

    First of all thank you for this nice project. I've recently discovered it and find it interesting.

    I wanted to send you a letter, but then thought, that this issue maybe useful to some other enthusiasts, and also I can use the markdown formatting. Apologies for a long read and for the fact that I haven't had the chance to push the project to GitHub yet.

    Before the generics were available I was playing around Monoids in Golang. My favourite example is FizzBuzz!

    So I implemented the solution which was highly inspired by a couple of articles mentioned bellow. The first approach looked something like this:

    // FizzBuzzFunctional
    //
    // https://web.archive.org/web/20130511210903/http://dave.fayr.am/posts/2012-10-4-finding-fizzbuzz.html
    // https://medium.com/@iopguy/fizzbuzz-can-finally-be-implemented-in-stable-rust-87649a882f2d
    // https://www.parsonsmatt.org/2016/02/27/an_elegant_fizzbuzz.html
    func FizzBuzzFunctional(n int) string {
    	m := monoid.ForString("").
    		Append(monoid.ForString("Fizz").Filtered(func() bool {
    			return n%3 == 0
    		})).
    		Append(monoid.ForString("Buzz").Filtered(func() bool {
    			return n%5 == 0
    		}))
    
    	return m.UnwrapOr(strconv.Itoa(n))
    }
    

    I had to implement an Optional type (an equivalent of Maybe, the name seemed more conventional for Golang). UnwrapOr is basically FromMaybe in Haskell. After that I turned that Optional into a monoid. The API is not ideal, but the solution looks pretty simple. Given that we don't have the monadic list comprehensions I used Filtered function to add the predicated. So basically the structure that implemented the monoid, also had a Filtered method. Not very elegant, but better than nothing.

    The beauty of this solution is that we can easily add more predicates: Fizz, Buzz, Bizz, etc... However in order for it to work we need to be able to create a Monoid which is basically a function, and not a concrete a simple type.

    My Optional Monoidlooked like this:

    package monoid
    
    type OptionString struct {
    	op option.String
    }
    
    // SomeString wraps the s into an optional string.
    func SomeString(s string) OptionString {
    	return OptionString{
    		op: option.SomeString(s),
    	}
    }
    
    // NoneString returns an empty optional string.
    func NoneString() OptionString {
    	return OptionString{
    		op: option.NoneString(),
    	}
    }
    
    func (m OptionString) Empty() OptionString {
    	return NoneString()
    }
    
    func (m OptionString) Append(other OptionString) OptionString {
    	switch {
    	case m == NoneString():
    		return other
    	case other == NoneString():
    		return m
    	default:
    		return SomeString(m.op.Append(other.op).UnwrapOrDefault())
    	}
    }
    
    func (m OptionString) Filtered(fn func() bool) OptionString {
    	if fn() {
    		return m
    	}
    
    	return NoneString()
    }
    
    func (m OptionString) UnwrapOr(s string) string {
    	return m.op.UnwrapOr(s)
    }
    

    It was using a String Option which supported the Append for convenience, however it was not a Monoid, it didn't respect the Monodic laws, however the monoid.OptionsSting did:

    func TestOptionString(t *testing.T) {
    	t.Parallel()
    
    	// A set S equipped with a binary operation S × S → S,
    	// which we will denote •, is a monoid if it satisfies the following two axioms:
    
    	t.Run("it has valid identity", func(t *testing.T) {
    		t.Parallel()
    
    		m := monoid.SomeString("test")
    
    		// There exists an element e in S such that for every element a in S,
    		// the equations e • a = a and a • e = a hold.
    		AssertEqual(t, m, m.Append(m.Empty()))
    		AssertEqual(t, m.Empty().Append(m), m.Append(m.Empty()))
    	})
    
    	t.Run("it has valid associativity", func(t *testing.T) {
    		t.Parallel()
    
    		a := monoid.SomeString("foo")
    		b := monoid.SomeString("bar")
    		c := monoid.NoneString()
    
    		// For all a, b and c in S, the equation (a • b) • c = a • (b • c) holds.
    		AssertEqual(t, a.Append(b).Append(c), a.Append(b.Append(c)))
    	})
    }
    

    The new iteration was changed a little to use foldable:

    func FizzBuzzFunctional(n int) string {
    	fizz := func(n int) bool {
    		return n%3 == 0
    	}
    
    	buzz := func(n int) bool {
    		return n%5 == 0
    	}
    
    	filters := foldable.RuleFoldable{
    		monoid.ForFizzBuzzPredicate(fizz, "Fizz"),
    		monoid.ForFizzBuzzPredicate(buzz, "Buzz"),
    	}
    
    	rules := fold(filters, monoid.NewEmptyFizzBuzzRuleset()) // a monoid which combines all the filters together
    
    	return monoid.FromStringOption(strconv.Itoa(n), rules(n))
    }
    
    // fold :: (Foldable t, Monoid m) => t m -> m
    func fold(filters foldable.RuleFoldable, m monoid.FizzBuzzRuleset) monoid.FizzBuzzRuleset {
    	rules := filters.Foldl(filters.Init(), func(result foldable.T, next foldable.T) foldable.T {
    		rule, ok := next.(func(int) monoid.OptionString)
    		mustOk(ok, "cannot cast result foldable.T to func(int) monoid.OptionString")
    
    		m = m.Append(rule)
    
    		return m
    	})
    
    	ruleSet, ok := rules.(monoid.FizzBuzzRuleset)
    	mustOk(ok, "cannot cast result foldable.T to monoid.FizzBuzzRuleset")
    
    	return ruleSet
    }
    
    func mustOk(ok bool, msg string) {
    	if !ok {
    		panic(msg)
    	}
    }
    

    Now that we have the generics, and your library we probably can come up with a better solution. I tried to use some of your ideas but at the moment you're changing the API faster than I have the time to follow :-D Nonetheless, I was almost able to implement the monoids I need from your wonderful library, however I stuck at the moment with a monoid to combine two functions. It got pretty ugly on my side.

    Could you please add an ExampleTest for this FizzBuzz case to demonstrate the usage of your library the way you were intended? What I really would like to achieve is the following translated into Go without being too ugly :)

    {-# LANGUAGE MonadComprehensions #-}
    
    module Main where
    import Data.Monoid (mappend)
    import Data.Maybe (fromMaybe, listToMaybe, maybe)
    import System.Environment (getArgs)
    
    
    fizzbuzz i = fromMaybe (show i) $ mappend ["fizz" | i `rem` 3 == 0]
                                              ["buzz" | i `rem` 5 == 0]
    
    main = mapM_ putStrLn [ fizzbuzz i | i <- [1..100] ]
    

    Thank you very much.

    opened by screwyprof 2
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  • Examples with functional monoids.

    Examples with functional monoids.

    Hello @genkami,

    Thank you for you detailed response and a great example. I also noticed you've updated the repo and added the FizzBuzz example:

    func main() {
    	monoid := option.DeriveMonoid[string](algebra.DeriveAdditiveSemigroup[string]())
    	fizzBuzz := func(i int) string {
    		fizz := option.Filter(option.Some[string]("Fizz"), func(_ string) bool { return i%3 == 0 })
    		buzz := option.Filter(option.Some[string]("Buzz"), func(_ string) bool { return i%5 == 0 })
    		return option.UnwrapOr(monoid.Combine(fizz, buzz), fmt.Sprint(i))
    	}
    	it := iterator.Map(iterator.Range[int](1, 15), fizzBuzz)
    	iterator.ForEach(it, func(s string) { fmt.Println(s) })
    }
    

    It looks nice, concise and pretty aligned with idiomatic Golang. What I'm not sure about is whether combining not monoids is ok, because they don't follow the monodic laws. Is it the expected behavior? In the example above you use a monoid to combine options which don't implement the Monoid interface.

    Allow me to drive it a little bit further: At the moment we have this Filter function on the option type. But what if (following the ideas from the aforementioned articles) we try to fold over a set of fizz-buzz Rules, where a Rule is function which takes a predicate and the word:

    type FizzBuzzPredicate func(num int) bool
    type FizzBuzzRule func(n int) option.String
    
    func Rule(p FizzBuzzPredicate, s string) FizzBuzzRule {
    	return func(n int) option.String {
    		if p(n) {
    			return option.Some(s)
    		}
    
    		return option.NoneString()
    	}
    }
    
    func FizzBuz(n int) string {
    	fizz := func(n int) bool {
    		return n%3 == 0
    	}
    
    	buzz := func(n int) bool {
    		return n%5 == 0
    	}
    
    	// rules should be a foldable of monoids
    	rules := []FizzBuzzRule{
    		Rule(fizz, "Fizz"),
    		Rule(buzz, "Buzz"),
    	}
    
    	// ruleSet is a monoid, which is a function by its nature: monoid[FizzBuzzRule]
    	// Written in a move verbose way it is the same as: monoid[ func(n int) option.String].
            // see https://blog.ploeh.dk/2017/11/06/function-monoids/
    	ruleSet := fold(rules)
    
    	return ruleSet(n).UnwrapOr(strconv.ItoA(i))
    }
    
    // fold :: (Foldable t, Monoid m) => t m -> m
    func Fold(filters Foldable) monoid[FizzBuzzFilter] {
      // fold over filters and turn them into a monoid
    }
    

    An excerpt in Haskell:

    fizzbuzz i = fromMaybe (show i) (ruleSet i)
    ruleSet = fold rules
    

    The reasoning behind this is is as such:

    • Option should probably not have the Filter method, or should it? I've added it for convenience :)
    • Monoids could be the functions per sei, so the combine method should be able to join the function together into a single monoid.

    Tell me what do you think?

    Thank you for your wonderful job and for patience!

    PS: I'm writing without an IDE at hand, so forgive me for some inconsistencies.

    opened by screwyprof 10
Owner
Genta Kamitani
Kyoto -> Tokyo
Genta Kamitani
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Viant, Inc 220 Sep 13, 2022
Functional programming library for Go including a lazy list implementation and some of the most usual functions.

functional A functional programming library including a lazy list implementation and some of the most usual functions. import FP "github.com/tcard/fun

Toni Cárdenas 31 May 21, 2022
An always-on framework that performs end-to-end functional network testing for reachability, latency, and packet loss

Arachne Arachne is a packet loss detection system and an underperforming path detection system. It provides fast and easy active end-to-end functional

Uber Open Source 368 Sep 11, 2022
Helpfully Functional Go like underscore.js

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null 382 Sep 19, 2022
vcluster - Create fully functional virtual Kubernetes clusters - Each cluster runs inside a Kubernetes namespace and can be started within seconds

Website • Quickstart • Documentation • Blog • Twitter • Slack vcluster - Virtual Clusters For Kubernetes Lightweight & Low-Overhead - Based on k3s, bu

Loft Labs 2k Oct 2, 2022
The package manager for macOS you didn’t know you missed. Simple, functional, and fast.

Stew The package manager for macOS you didn’t know you missed. Built with simplicity, functionality, and most importantly, speed in mind. Installation

Stew 20 Mar 30, 2022
functional programming in go

function programming experimental lib why another fp lib I like fp style and I haven’t found a lib with these features: streamingly, I can handle infi

Jason 9 Sep 1, 2022