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golang-samber-lo

samber/cc-skills-golang

500+ type-safe functional helpers for Go slices, maps, and channels—Map, Filter, Reduce, GroupBy without boilerplate.

What is golang-samber-lo?

samber/lo is a Lodash-inspired utility library providing 500+ generic functions for functional-style data transformations in Go. Use it when working with slices, maps, channels, or strings to replace manual loops with declarative, composable operations—or upgrade to parallel (lop), mutable (lom), or lazy iterator (loi) variants when profiling demands it.

  • Transform slices with Map, Filter, Reduce, and error-aware variants (MapErr, FilterErr)
  • Group, chunk, flatten, and deduplicate collections with GroupBy, Chunk, Flatten, Uniq
  • Perform membership tests and searches with Contains, Find, Every, Some
  • Operate on maps and channels with type-safe generics and zero external dependencies
  • Access concurrent variants (lo/parallel), in-place mutations (lo/mutable), and lazy iterators (lo/it for Go 1.23+)

How to install golang-samber-lo

npx skills add https://github.com/samber/cc-skills-golang --skill golang-samber-lo
Prerequisites
  • Go 1.18+ (core lo package); Go 1.23+ for lazy iterators (lo/it); Go 1.25+ for SIMD variants
  • Run `go get github.com/samber/lo` to install
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How to use golang-samber-lo

  1. 1.Import the appropriate package: `import "github.com/samber/lo"` (or `lo/parallel`, `lo/mutable`, `lo/it`)
  2. 2.Use lo.Map, lo.Filter, lo.Reduce to transform collections declaratively instead of writing for-loops
  3. 3.Chain functions together: `lo.Filter(data, predicate)` → `lo.Map(result, transform)`
  4. 4.For error handling, use error variants like `lo.MapErr` to stop on first error and propagate cleanly
  5. 5.Profile with `go tool pprof` before switching to lop (parallel), lom (mutable), or loi (lazy) for optimization

Use cases

Good for
  • Transform user objects to a list of names or emails without manual loops
  • Filter paid orders and sum their amounts in a single composed chain
  • Group tasks by status to build a dashboard view
  • Deduplicate a large dataset after a merge operation
  • Parallelize CPU-bound transforms on 1000+ item slices using lo/parallel
Who it's for
  • Go engineers building data pipelines and collection transforms
  • Teams adopting functional programming patterns in Go
  • Developers working with large datasets who want to avoid allocation overhead
  • Projects already importing github.com/samber/lo seeking best practices

golang-samber-lo FAQ

When should I use lo instead of Go's stdlib slices and maps packages?

Use stdlib (slices.Contains, slices.Sort, maps.Keys) when available since Go 1.21+. Use lo for transforms the stdlib doesn't offer: Map, Filter, Reduce, GroupBy, Chunk, Flatten, Uniq, Find. Prefer lo.MapErr over manual error collection.

Should I use lo/parallel (lop) for all large datasets?

No. lop is for CPU-bound work on 1000+ items; goroutine overhead makes it slower on small slices. For I/O concurrency, use errgroup instead. Always profile with pprof before switching from lo to lop.

Does lo mutate the input slice?

No, lo is immutable by default—it returns new collections. Use lo/mutable (lom) only if profiling confirms allocation is a bottleneck and you understand the side effects of in-place mutation.

What is lo/it (loi) and when should I use it?

lo/it provides lazy iterators (Go 1.23+) that avoid intermediate allocations in chains like Map → Filter → Take. Use it for large datasets with multiple chained transforms where memory is measured as a bottleneck.

Can I use lo.Must in production code?

No, lo.Must panics on error. Use it only in tests and init blocks. In production request handlers, use the non-Must variant and handle errors explicitly.

Full instructions (SKILL.md)

Source of truth, from samber/cc-skills-golang.


name: golang-samber-lo description: "Functional programming helpers for Golang using samber/lo — 500+ type-safe generic functions for slices, maps, channels, strings, math, tuples, and concurrency (Map, Filter, Reduce, GroupBy, Chunk, Flatten, Find, Uniq, etc.). Core immutable package (lo), concurrent variants (lo/parallel aka lop), in-place mutations (lo/mutable aka lom), lazy iterators (lo/it aka loi for Go 1.23+), and experimental SIMD (lo/exp/simd). Apply when using or adopting samber/lo, when the codebase imports github.com/samber/lo, or when implementing functional-style data transformations in Go. Not for streaming pipelines (→ See samber/cc-skills-golang@golang-samber-ro skill)." user-invocable: true license: MIT compatibility: Designed for Claude Code or similar AI coding agents, and for projects using Golang. metadata: author: samber version: "1.1.1" openclaw: emoji: "🧰" homepage: https://github.com/samber/cc-skills-golang requires: bins: - go install: [] skill-library-version: "1.53.0" allowed-tools: Read Edit Write Glob Grep Bash(go:) Bash(golangci-lint:) Bash(git:*) mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion

Persona: You are a Go engineer who prefers declarative collection transforms over manual loops. You reach for lo to eliminate boilerplate, but you know when the stdlib is enough and when to upgrade to lop, lom, or loi.

samber/lo — Functional Utilities for Go

Lodash-inspired, generics-first utility library with 500+ type-safe helpers for slices, maps, strings, math, channels, tuples, and concurrency. Zero external dependencies. Immutable by default.

Official Resources:

This skill is not exhaustive. Please refer to library documentation and code examples for more information. Context7 can help as a discoverability platform. For Go package docs, versions, symbols, and known vulnerabilities, → See samber/cc-skills-golang@golang-pkg-go-dev skill.

Why samber/lo

Go's stdlib slices and maps packages cover ~10 basic helpers (sort, contains, keys). Everything else — Map, Filter, Reduce, GroupBy, Chunk, Flatten, Zip — requires manual for-loops. lo fills this gap:

  • Type-safe generics — no interface{} casts, no reflection, compile-time checking, no interface boxing overhead
  • Immutable by default — returns new collections, safe for concurrent reads, easier to reason about
  • Composable — functions take and return slices/maps, so they chain without wrapper types
  • Zero dependencies — only Go stdlib, no transitive dependency risk
  • Progressive complexity — start with lo, upgrade to lop/lom/loi only when profiling demands it
  • Error variants — most functions have Err suffixes (MapErr, FilterErr, ReduceErr) that stop on first error

Installation

go get github.com/samber/lo
PackageImportAliasGo version
Core (immutable)github.com/samber/lolo1.18+
Parallelgithub.com/samber/lo/parallellop1.18+
Mutablegithub.com/samber/lo/mutablelom1.18+
Iteratorgithub.com/samber/lo/itloi1.23+
SIMD (experimental)github.com/samber/lo/exp/simd1.25+ (amd64 only)

Choose the Right Package

Start with lo. Move to other packages only when profiling shows a bottleneck or when lazy evaluation is explicitly needed.

PackageUse whenTrade-off
loDefault for all transformsAllocates new collections (safe, predictable)
lopCPU-bound work on large datasets (1000+ items)Goroutine overhead; not for I/O or small slices
lomHot path confirmed by pprof -alloc_objectsMutates input — caller must understand side effects
loiLarge datasets with chained transforms (Go 1.23+)Lazy evaluation saves memory but adds iterator complexity
simdNumeric bulk ops after benchmarking (experimental)Unstable API, may break between versions

Key rules:

  • lop is for CPU parallelism, not I/O concurrency — for I/O fan-out, use errgroup instead
  • lom breaks immutability — only use when allocation pressure is measured, never assumed
  • loi eliminates intermediate allocations in chains like Map → Filter → Take by evaluating lazily
  • For reactive/streaming pipelines over infinite event streams, → see samber/cc-skills-golang@golang-samber-ro skill + samber/ro package

For detailed package comparison and decision flowchart, see Package Guide.

Core Patterns

Transform a slice

// ✓ lo — declarative, type-safe
names := lo.Map(users, func(u User, _ int) string {
    return u.Name
})

// ✗ Manual — boilerplate, error-prone
names := make([]string, 0, len(users))
for _, u := range users {
    names = append(names, u.Name)
}

Filter + Reduce

total := lo.Reduce(
    lo.Filter(orders, func(o Order, _ int) bool {
        return o.Status == "paid"
    }),
    func(sum float64, o Order, _ int) float64 {
        return sum + o.Amount
    },
    0,
)

GroupBy

byStatus := lo.GroupBy(tasks, func(t Task, _ int) string {
    return t.Status
})
// map[string][]Task{"open": [...], "closed": [...]}

Error variant — stop on first error

results, err := lo.MapErr(urls, func(url string, _ int) (Response, error) {
    return http.Get(url)
})

Common Mistakes

MistakeWhy it failsFix
Using lo.Contains when slices.Contains existsUnnecessary dependency for a stdlib-covered opPrefer slices.Contains/slices.Sort since Go 1.21+ and slices.Collect(maps.Keys(m)) since Go 1.23+ when a key slice is needed
Using lop.Map on 10 itemsGoroutine creation overhead exceeds transform costUse lo.Maplop benefits start at ~1000+ items for CPU-bound work
Assuming lo.Filter modifies the inputlo is immutable by default — it returns a new sliceUse lom.Filter if you explicitly need in-place mutation
Using lo.Must in production code pathsMust panics on error — fine in tests and init, dangerous in request handlersUse the non-Must variant and handle the error
Chaining many eager transforms on large dataEach step allocates an intermediate sliceUse loi (lazy iterators) to avoid intermediate allocations

Best Practices

  1. Prefer stdlib when availableslices.Contains and slices.Sort (Go 1.21+) carry no dependency; maps.Keys is Go 1.23+ and returns an iterator, so use slices.Collect(maps.Keys(m)) when you need a slice. Use lo for transforms the stdlib doesn't offer (Map, Filter, Reduce, GroupBy, Chunk, Flatten)
  2. Compose lo functions — chain lo.Filterlo.Maplo.GroupBy instead of writing nested loops. Each function is a building block
  3. Profile before optimizing — switch from lo to lom/lop only after go tool pprof confirms allocation or CPU as the bottleneck
  4. Use error variants — prefer lo.MapErr over lo.Map + manual error collection. Error variants stop early and propagate cleanly
  5. Use lo.Must only in tests and init — in production, handle errors explicitly

Quick Reference

FunctionWhat it does
lo.MapTransform each element
lo.Filter / lo.RejectKeep / remove elements matching predicate
lo.ReduceFold elements into a single value
lo.ForEachSide-effect iteration
lo.GroupByGroup elements by key
lo.ChunkSplit into fixed-size batches
lo.FlattenFlatten nested slices one level
lo.Uniq / lo.UniqByRemove duplicates
lo.Find / lo.FindOrElseFirst match or default
lo.Contains / lo.Every / lo.SomeMembership tests
lo.Keys / lo.ValuesExtract map keys or values
lo.PickBy / lo.OmitByFilter map entries
lo.Zip2 / lo.Unzip2Pair/unpair two slices
lo.Range / lo.RangeFromGenerate number sequences
lo.Ternary / lo.IfInline conditionals
lo.ToPtr / lo.FromPtrPointer helpers
lo.Must / lo.TryPanic-on-error / recover-as-bool
lo.Async / lo.AttemptAsync execution / retry with backoff
lo.Debounce / lo.ThrottleRate limiting
lo.ChannelDispatcherFan-out to multiple channels

For the complete function catalog (300+ functions), see API Reference.

For composition patterns, stdlib interop, and iterator pipelines, see Advanced Patterns.

If you encounter a bug or unexpected behavior in samber/lo, open an issue at github.com/samber/lo/issues.

Cross-References

  • → See samber/cc-skills-golang@golang-samber-ro skill for reactive/streaming pipelines over infinite event streams (samber/ro package)
  • → See samber/cc-skills-golang@golang-samber-mo skill for monadic types (Option, Result, Either) that compose with lo transforms
  • → See samber/cc-skills-golang@golang-data-structures skill for choosing the right underlying data structure
  • → See samber/cc-skills-golang@golang-performance skill for profiling methodology before switching to lom/lop