Data & analysis

golang-samber-lo

Try it

Replace manual Go for-loops with type-safe Map, Filter, Reduce, GroupBy, and 500+ generic helpers from samber/lo.

What it does

Guides Go engineers on using samber/lo for declarative collection transforms over slices, maps, channels, strings, math, tuples, and concurrency. Covers choosing between the immutable core (`lo`), parallel (`lop`), mutable (`lom`), lazy iterator (`loi`), and experimental SIMD packages, plus stdlib interop and error variants. Helps decide when the stdlib's `slices`/`maps` packages are enough and when profiling justifies an upgrade.

When to use it

  • Rewriting slice handling with lo.Map, lo.Filter, lo.Reduce, and friends
  • Choosing between lo, lop, lom, and loi based on pprof data
  • Handling errors in collection transforms via MapErr, FilterErr, ReduceErr
  • Deciding when stdlib slices/maps is enough vs. importing samber/lo

The skill document

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.

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/simd—1.25+ (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.Map — lop 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 available — slices.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.Filter → lo.Map → lo.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

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