sliceutil

sliceutil filters, maps, and reduces slices with generic functions, and summarizes numeric slices with descriptive statistics.

Table of contents

Part of nurago, a collection of independent Go packages for backend services.

import "github.com/tecnickcom/nurago/pkg/sliceutil"

Package sliceutil filters, maps, and reduces slices with generic functions, and summarizes numeric slices with descriptive statistics.

What It Provides

Functional slice primitives, generic over S ~[]E, whose callbacks receive the element index:

  • [Filter]: returns a new slice containing elements that satisfy a predicate.
  • [Map]: returns a new slice with each element transformed to a new type.
  • [Reduce]: folds a slice into a single value using an accumulator.

Descriptive statistics for numeric slices:

  • [Stats]: computes a DescStats summary for any numeric slice type, and returns ErrEmptySlice for an empty slice.
  • DescStats includes count, sum, min/max (+ indexes), range, mode, mean/median, entropy, variance, standard deviation, skewness, and excess kurtosis.

Usage

adults := sliceutil.Filter(users, func(_ int, u User) bool { return u.Age >= 18 })
names := sliceutil.Map(adults, func(_ int, u User) string { return u.Name })
total := sliceutil.Reduce([]int{1, 2, 3, 4}, 0, func(_ int, v int, acc int) int {
    return acc + v
})
_ = names
_ = total

ds, err := sliceutil.Stats([]int{53, 83, 13, 79})
if err != nil {
    return err
}
_ = ds.Mean

When To Use

  • You want map, filter, and reduce over slices without writing loops each time.
  • A numeric slice needs mean, median, or percentile values.

Example

s := []string{"Hello", "World", "Extra"}

filterFn := func(_ int, v string) bool { return v == "World" }

s2 := sliceutil.Filter(s, filterFn)

fmt.Println(s2)

// Output:
// [World]

Full source is in example_sliceutil_test.go. More runnable examples are on pkg.go.dev.

Dependencies

This package reaches no external module: it uses only the Go standard library.