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lo

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โœจ lo is a Lodash-style Go library based on Go 1.18+ Generics.

This project have started as an experiment to discover generics implementation. It may look like Lodash in some aspects. I used to code with the awesome go-funk package, but it uses reflection and therefore is not typesafe.

As expected, benchmarks demonstrate that generics will be much faster than implementations based on reflect stdlib package. Benchmarks also shows similar performances to pure for loops. See below.

In the future, 5 to 10 helpers will overlap with those coming into the Go standard library (under package names slices and maps). Anyway I feel this library legitimate to offer many more such useful abstractions.

Why this name?

I wanted a short name, similar to "Lodash", and no Go package currently use this name.

๐Ÿš€ Install

go get github.com/samber/lo

๐Ÿ’ก Usage

You can import lo using a basic statement:

import (
    "github.com/samber/lo"
    lop "github.com/samber/lo/parallel"
)

Then use one of the helpers below:

names := lo.Uniq[string]([]string{"Samuel", "Marc", "Samuel"})
// []string{"Samuel", "Marc"}

๐Ÿค  Spec

GoDoc: https://godoc.org/github.com/samber/lo

Supported helpers for slices:

  • Filter
  • Map
  • Reduce
  • ForEach
  • Times
  • Uniq
  • UniqBy
  • GroupBy
  • Chunk
  • PartitionBy
  • Flatten
  • Shuffle
  • Reverse
  • Fill
  • Repeat
  • ToMap

Supported helpers for maps:

  • Keys
  • Values
  • Entries
  • FromEntries
  • Assign (merge of maps)

Supported helpers for tuples:

  • Zip2 -> Zip9
  • Unzip2 -> Unzip9

Supported intersection helpers:

  • Contains
  • Every
  • Some
  • Intersect
  • Difference

Supported search helpers:

  • IndexOf
  • LastIndexOf
  • Find
  • Min
  • Max
  • Last
  • Nth
  • Sample
  • Samples

Other functional programming helpers:

  • Ternary (1 line if/else statement)
  • If / ElseIf / Else
  • Switch / Case / Default
  • ToPtr
  • ToSlicePtr
  • Attempt

Constraints:

  • Clonable

Map

Manipulates a slice and transforms it to a slice of another type:

import "github.com/samber/lo"

lo.Map[int64, string]([]int64{1, 2, 3, 4}, func(x int64, _ int) string {
    return strconv.FormatInt(x, 10)
})
// []string{"1", "2", "3", "4"}

Parallel processing: like lo.Map(), but mapper is called in goroutine. Results are returned in the same order.

import lop "github.com/samber/lo/parallel"

lop.Map[int64, string]([]int64{1, 2, 3, 4}, func(x int64, _ int) string {
    return strconv.FormatInt(x, 10)
}, 2)
// []string{"1", "2", "3", "4"}

Filter

Iterates over elements of collection, returning an array of all elements predicate returns truthy for.

even := lo.Filter[int]([]int{1, 2, 3, 4}, func(x int, _ int) bool {
    return x%2 == 0
})
// []int{2, 4}

Contains

Returns true if an element is present in a collection.

present := lo.Contains[int]([]int{0, 1, 2, 3, 4, 5}, 5)
// true

Reduce

Reduces collection to a value which is the accumulated result of running each element in collection through accumulator, where each successive invocation is supplied the return value of the previous.

sum := lo.Reduce[int, int]([]int{1, 2, 3, 4}, func(agg int, item int, _ int) int {
    return agg + item
}, 0)
// 10

ForEach

Iterates over elements of collection and invokes iteratee for each element.

import "github.com/samber/lo"

lo.ForEach[string]([]string{"hello", "world"}, func(x string, _ int) {
    println(x)
})
// prints "hello\nworld\n"

Parallel processing: like lo.ForEach(), but callback is called in goroutine.

import lop "github.com/samber/lo/parallel"

lop.ForEach[string]([]string{"hello", "world"}, func(x string, _ int) {
    println(x)
})
// prints "hello\nworld\n" or "world\nhello\n"

Times

Times invokes the iteratee n times, returning an array of the results of each invocation. The iteratee is invoked with index as argument.

import "github.com/samber/lo"

lo.Times[string](3, func(i int) string {
    return strconv.FormatInt(int64(i), 10)
})
// []string{"0", "1", "2"}

Parallel processing: like lo.Times(), but callback is called in goroutine.

import lop "github.com/samber/lo/parallel"

lop.Times[string](3, func(i int) string {
    return strconv.FormatInt(int64(i), 10)
})
// []string{"0", "1", "2"}

Uniq

Returns a duplicate-free version of an array, in which only the first occurrence of each element is kept. The order of result values is determined by the order they occur in the array.

uniqValues := lo.Uniq[int]([]int{1, 2, 2, 1})
// []int{1, 2}

UniqBy

Returns a duplicate-free version of an array, in which only the first occurrence of each element is kept. The order of result values is determined by the order they occur in the array. It accepts iteratee which is invoked for each element in array to generate the criterion by which uniqueness is computed.

uniqValues := lo.UniqBy[int, int]([]int{0, 1, 2, 3, 4, 5}, func(i int) int {
    return i%3
})
// []int{0, 1, 2}

GroupBy

Returns an object composed of keys generated from the results of running each element of collection through iteratee.

import lo "github.com/samber/lo"

groups := lo.GroupBy[int, int]([]int{0, 1, 2, 3, 4, 5}, func(i int) int {
    return i%3
})
// map[int][]int{0: []int{0, 3}, 1: []int{1, 4}, 2: []int{2, 5}}

Parallel processing: like lo.GroupBy(), but callback is called in goroutine.

import lop "github.com/samber/lo/parallel"

lop.GroupBy[int, int]([]int{0, 1, 2, 3, 4, 5}, func(i int) int {
    return i%3
})
// map[int][]int{0: []int{0, 3}, 1: []int{1, 4}, 2: []int{2, 5}}

Chunk

Returns an array of elements split into groups the length of size. If array can't be split evenly, the final chunk will be the remaining elements.

lo.Chunk[int]([]int{0, 1, 2, 3, 4, 5}, 2)
// [][]int{{0, 1}, {2, 3}, {4, 5}}

lo.Chunk[int]([]int{0, 1, 2, 3, 4, 5, 6}, 2)
// [][]int{{0, 1}, {2, 3}, {4, 5}, {6}}

lo.Chunk[int]([]int{}, 2)
// [][]int{}

lo.Chunk[int]([]int{0}, 2)
// [][]int{{0}}

PartitionBy

Returns an array of elements split into groups. The order of grouped values is determined by the order they occur in collection. The grouping is generated from the results of running each element of collection through iteratee.

import lo "github.com/samber/lo"

partitions := lo.PartitionBy[int, string]([]int{-2, -1, 0, 1, 2, 3, 4, 5}, func(x int) string {
    if x < 0 {
        return "negative"
    } else if x%2 == 0 {
        return "even"
    }
    return "odd"
})
// [][]int{{-2, -1}, {0, 2, 4}, {1, 3, 5}}

Parallel processing: like lo.PartitionBy(), but callback is called in goroutine. Results are returned in the same order.

import lop "github.com/samber/lo/parallel"

partitions := lo.PartitionBy[int, string]([]int{-2, -1, 0, 1, 2, 3, 4, 5}, func(x int) string {
    if x < 0 {
        return "negative"
    } else if x%2 == 0 {
        return "even"
    }
    return "odd"
})
// [][]int{{-2, -1}, {0, 2, 4}, {1, 3, 5}}

Flatten

Returns an array a single level deep.

flat := lo.Flatten[int]([][]int{{0, 1}, {2, 3, 4, 5}})
// []int{0, 1, 2, 3, 4, 5}

Shuffle

Returns an array of shuffled values. Uses the Fisher-Yates shuffle algorithm.

randomOrder := lo.Shuffle[int]([]int{0, 1, 2, 3, 4, 5})
// []int{0, 1, 2, 3, 4, 5}

Reverse

Reverses array so that the first element becomes the last, the second element becomes the second to last, and so on.

reverseOder := lo.Reverse[int]([]int{0, 1, 2, 3, 4, 5})
// []int{5, 4, 3, 2, 1, 0}

Fill

Fills elements of array with initial value.

type foo struct {
	bar string
}

func (f foo) Clone() foo {
	return foo{f.bar}
}

initializedSlice := lo.Fill[foo]([]foo{foo{"a"}, foo{"a"}}, foo{"b"})
// []foo{foo{"b"}, foo{"b"}}

Repeat

Builds a slice with N copies of initial value.

type foo struct {
	bar string
}

func (f foo) Clone() foo {
	return foo{f.bar}
}

initializedSlice := lo.Repeat[foo](2, foo{"a"})
// []foo{foo{"a"}, foo{"a"}}

ToMap

Transforms a slice or an array of structs to a map based on a pivot callback.

m := lo.ToMap[int, string]([]string{"a", "aa", "aaa"}, func(str string) int {
    return len(str)
})
// map[int]string{1: "a", 2: "aa", 3: "aaa"}

Keys

Creates an array of the map keys.

keys := lo.Keys[string, int](map[string]int{"foo": 1, "bar": 2})
// []string{"bar", "foo"}

Values

Creates an array of the map values.

values := lo.Values[string, int](map[string]int{"foo": 1, "bar": 2})
// []int{1, 2}

Entries

Transforms a map into array of key/value pairs.

entries := lo.Entries[string, int](map[string]int{"foo": 1, "bar": 2})
// []lo.Entry[string, int]{
//     {
//         Key: "foo",
//         Value: 1,
//     },
//     {
//         Key: "bar",
//         Value: 2,
//     },
// }

FromEntries

Transforms an array of key/value pairs into a map.

m := lo.FromEntries[string, int]([]lo.Entry[string, int]{
    {
        Key: "foo",
        Value: 1,
    },
    {
        Key: "bar",
        Value: 2,
    },
})
// map[string]int{"foo": 1, "bar": 2}

Assign

Merges multiple maps from left to right.

mergedMaps := lo.Assign[string, int](
    map[string]int{"a": 1, "b": 2},
    map[string]int{"b": 3, "c": 4},
)
// map[string]int{"a": 1, "b": 3, "c": 4}

Zip2 -> Zip9

Zip creates a slice of grouped elements, the first of which contains the first elements of the given arrays, the second of which contains the second elements of the given arrays, and so on.

When collections have different size, the Tuple attributes are filled with zero value.

tuples := lo.Zip2[string, int]([]string{"a", "b"}, []int{1, 2})
// []Tuple2[string, int]{{A: "a", B: 1}, {A: "b", B: 2}}

Unzip2 -> Unzip9

Unzip accepts an array of grouped elements and creates an array regrouping the elements to their pre-zip configuration.

a, b := lo.Unzip2[string, int]([]Tuple2[string, int]{{A: "a", B: 1}, {A: "b", B: 2}})
// []string{"a", "b"}
// []int{1, 2}

Every

Returns true if all elements of a subset are contained into a collection.

ok := lo.Every[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 2})
// true

ok := lo.Every[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 6})
// false

Some

Returns true if at least 1 element of a subset is contained into a collection.

ok := lo.Some[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 2})
// true

ok := lo.Some[int]([]int{0, 1, 2, 3, 4, 5}, []int{-1, 6})
// false

Intersect

Returns the intersection between two collections.

result1 := lo.Intersect[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 2})
// []int{0, 2}

result2 := lo.Intersect[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 6}
// []int{0}

result3 := lo.Intersect[int]([]int{0, 1, 2, 3, 4, 5}, []int{-1, 6})
// []int{}

Difference

Returns the difference between two collections.

  • The first value is the collection of element absent of list2.
  • The second value is the collection of element absent of list1.
left, right := lo.Difference[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 2, 6})
// []int{1, 3, 4, 5}, []int{6}

left, right := Difference[int]([]int{0, 1, 2, 3, 4, 5}, []int{0, 1, 2, 3, 4, 5})
// []int{}, []int{}

IndexOf

Returns the index at which the first occurrence of a value is found in an array or return -1 if the value cannot be found.

found := lo.IndexOf[int]([]int{0, 1, 2, 1, 2, 3}, 2)
// 2

notFound := lo.IndexOf[int]([]int{0, 1, 2, 1, 2, 3}, 6)
// -1

LastIndex

Returns the index at which the last occurrence of a value is found in an array or return -1 if the value cannot be found.

found := lo.LastIndexOf[int]([]int{0, 1, 2, 1, 2, 3}, 2)
// 4

notFound := lo.LastIndexOf[int]([]int{0, 1, 2, 1, 2, 3}, 6)
// -1

Find

Search an element in a slice based on a predicate. It returns element and true if element was found.

str, ok := lo.Find[string]([]string{"a", "b", "c", "d"}, func(i string) bool {
    return i == "b"
})
// "b", true

str, ok := lo.Find[string]([]string{"foobar"}, func(i string) bool {
    return i == "b"
})
// "", false

Min

Search the minimum value of a collection.

min := lo.Min[int]([]int{1, 2, 3})
// 1

min := lo.Min[int]([]int{})
// 0

Max

Search the maximum value of a collection.

max := lo.Max[int]([]int{1, 2, 3})
// 3

max := lo.Max[int]([]int{})
// 0

Last

Returns the last element of a collection or error if empty.

last, err := lo.Last[int]([]int{1, 2, 3})
// 3

Nth

Returns the element at index nth of collection. If nth is negative, the nth element from the end is returned. An error is returned when nth is out of slice bounds.

nth, err := lo.Nth[int]([]int{0, 1, 2, 3}, 2)
// 2

nth, err := lo.Nth[int]([]int{0, 1, 2, 3}, -2)
// 2

Sample

Returns a random item from collection.

lo.Sample[string]([]string{"a", "b", "c"})
// a random string from []string{"a", "b", "c"}

lo.Sample[string]([]string{})
// ""

Samples

Returns N random unique items from collection.

lo.Samples[string]([]string{"a", "b", "c"}, 3)
// []string{"a", "b", "c"} in random order

Ternary

A 1 line if/else statement.

result := lo.Ternary[string](true, "a", "b")
// "a"

result := lo.Ternary[string](false, "a", "b")
// "b"

If / ElseIf / Else

result := lo.If[int](true, 1).
    ElseIf(false, 2).
    Else(3)
// 1

result := lo.If[int](false, 1).
    ElseIf(true, 2).
    Else(3)
// 2

result := lo.If[int](false, 1).
    ElseIf(false, 2).
    Else(3)
// 3

Switch / Case / Default

result := lo.Switch[int, string](1).
    Case(1, "1").
    Case(2, "2").
    Default("3")
// "1"

result := lo.Switch[int, string](2).
    Case(1, "1").
    Case(2, "2").
    Default("3")
// "2"

result := lo.Switch[int, string](42).
    Case(1, "1").
    Case(2, "2").
    Default("3")
// "3"

Using callbacks:

result := lo.Switch[int, string](1).
    CaseF(1, func() string {
        return "1"
    }).
    CaseF(2, func() string {
        return "2"
    }).
    DefaultF(func() string {
        return "3"
    })
// "1"

ToPtr

Returns a pointer copy of value.

ptr := lo.ToPtr[string]("hello world")
// *string{"hello world"}

ToSlicePtr

Returns a slice of pointer copy of value.

ptr := lo.ToSlicePtr[string]([]string{"hello", "world"})
// []*string{"hello", "world"}

Attempt

Invokes a function N times until it returns valid output. Returning either the caught error or nil. When first argument is less than 1, the function runs until a sucessfull response is returned.

iter, err := lo.Attempt(42, func(i int) error {
    if i == 5 {
        return nil
    }

    return fmt.Errorf("failed")
})
// 6
// nil

iter, err := lo.Attempt(2, func(i int) error {
    if i == 5 {
        return nil
    }

    return fmt.Errorf("failed")
})
// 2
// error "failed"

iter, err := lo.Attempt(0, func(i int) error {
    if i < 42 {
        return fmt.Errorf("failed")
    }

    return nil
})
// 43
// nil

For more advanced retry strategies (delay, exponential backoff...), please take a look on cenkalti/backoff.

๐Ÿ›ฉ Benchmark

We executed a simple benchmark with the a dead-simple lo.Map loop:

See the full implementation here.

_ = lo.Map[int64](arr, func(x int64, i int) string {
    return strconv.FormatInt(x, 10)
})

Result:

Here is a comparison between lo.Map, lop.Map, go-funk library and a simple Go for loop.

$ go test -benchmem -bench ./...
goos: linux
goarch: amd64
pkg: github.com/samber/lo
cpu: Intel(R) Core(TM) i5-7267U CPU @ 3.10GHz
cpu: Intel(R) Core(TM) i7 CPU         920  @ 2.67GHz
BenchmarkMap/lo.Map-8         	       8	 132728237 ns/op	39998945 B/op	 1000002 allocs/op
BenchmarkMap/lop.Map-8        	       2	 503947830 ns/op	119999956 B/op	 3000007 allocs/op
BenchmarkMap/reflect-8        	       2	 826400560 ns/op	170326512 B/op	 4000042 allocs/op
BenchmarkMap/for-8            	       9	 126252954 ns/op	39998674 B/op	 1000001 allocs/op
PASS
ok  	github.com/samber/lo	6.657s
  • lo.Map is way faster (x7) than go-funk, a relection-based Map implementation.
  • lo.Map have the same allocation profile than for.
  • lo.Map is 4% slower than for.
  • lop.Map is slower than lo.Map because it implies more memory allocation and locks. lop.Map will be usefull for long-running callbacks, such as i/o bound processing.
  • for beats other implementations for memory and CPU.

๐Ÿค Contributing

Don't hesitate ;)

Install go 1.18

make go1.18beta1

If your OS currently not default to Go 1.18, replace BIN=go by BIN=go1.18beta1 in the Makefile.

With Docker

docker-compose run --rm dev

Without Docker

# Install some dev dependencies
make tools

# Run tests
make test
# or
make watch-test

๐Ÿ‘ค Authors

  • Samuel Berthe

๐Ÿ’ซ Show your support

Give a โญ๏ธ if this project helped you!

support us

๐Ÿ“ License

Copyright ยฉ 2022 Samuel Berthe.

This project is MIT licensed.

lo's People

Contributors

bluskript avatar fsouza avatar hirbodbehnam avatar lepijohnny avatar lsmoura avatar morgangeek avatar retornam avatar samber avatar

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