lo
โจ 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.
๐ Install
go get github.com/samber/lo
๐ก 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"}
๐ค 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.
๐ฉ 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) thango-funk
, a relection-based Map implementation.lo.Map
have the same allocation profile thanfor
.lo.Map
is 4% slower thanfor
.lop.Map
is slower thanlo.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.
๐ค Contributing
- Ping me on twitter @samuelberthe (DMs, mentions, whatever :))
- Fork the project
- Fix open issues or request new features
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
๐ค Authors
- Samuel Berthe
๐ซ Show your support
Give a โญ๏ธ if this project helped you!
๐ License
Copyright ยฉ 2022 Samuel Berthe.
This project is MIT licensed.