golang-samber-ro

作成者: samber

Golangにおけるsamber/roを使用したリアクティブストリームとイベント駆動プログラミング — 150以上の型安全なオペレーター、コールド/ホットオブザーバブル、5つのサブジェクトタイプ(Publish、Behavior、Replay、Async、Unicast)、Pipeによる宣言的パイプライン、40以上のプラグイン(HTTP、cron、fsnotify、JSON、ロギング)、自動バックプレッシャー、エラー伝搬、Goコンテキスト統合を備えたReactiveX実装。samber/roを使用または採用する場合、コードベースがgithub.com/samber/roをインポートする場合、または非同期処理を構築する場合に適用。

npx skills add https://github.com/samber/cc-skills-golang --skill golang-samber-ro

Persona: You are a Go engineer who reaches for reactive streams when data flows asynchronously or infinitely. You use samber/ro to build declarative pipelines instead of manual goroutine/channel wiring, but you know when a simple slice + samber/lo is enough.

Thinking mode: Use ultrathink when designing advanced reactive pipelines or choosing between cold/hot observables, subjects, and combining operators. Wrong architecture leads to resource leaks or missed events.

samber/ro — Reactive Streams for Go

Go implementation of ReactiveX. Generics-first, type-safe, composable pipelines for asynchronous data streams with automatic backpressure, error propagation, context integration, and resource cleanup. 150+ operators, 5 subject types, 40+ plugins.

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/ro (Streams vs Slices)

Go channels + goroutines become unwieldy for complex async pipelines: manual channel closures, verbose goroutine lifecycle, error propagation across nested selects, and no composable operators. samber/ro solves this with declarative, chainable stream operators.

When to use which tool:

ScenarioToolWhy
Transform a slice (map, filter, reduce)samber/loFinite, synchronous, eager — no stream overhead needed
Simple goroutine fan-out with error handlingerrgroupStandard lib, lightweight, sufficient for bounded concurrency
Infinite event stream (WebSocket, tickers, file watcher)samber/roDeclarative pipeline with backpressure, retry, timeout, combine
Real-time data enrichment from multiple async sourcessamber/roCombineLatest/Zip compose dependent streams without manual select
Pub/sub with multiple consumers sharing one sourcesamber/roHot observables (Share/Subjects) handle multicast natively

Key differences: lo vs ro

Aspectsamber/losamber/ro
DataFinite slicesInfinite streams
ExecutionSynchronous, blockingAsynchronous, non-blocking
EvaluationEager (allocates intermediate slices)Lazy (processes items as they arrive)
TimingImmediateTime-aware (delay, throttle, interval, timeout)
Error modelReturn (T, error) per callError channel propagates through pipeline
Use caseCollection transformsEvent-driven, real-time, async pipelines

Installation

go get github.com/samber/ro

Core Concepts

Four building blocks:

  1. Observable — a data source that emits values over time. Cold by default: each subscriber triggers independent execution from scratch
  2. Observer — a consumer with three callbacks: onNext(T), onError(error), onComplete()
  3. Operator — a function that transforms an observable into another observable, chained via Pipe
  4. Subscription — the connection between observable and observer. Call .Wait() to block or .Unsubscribe() to cancel
observable := ro.Pipe2(
    ro.RangeWithInterval(0, 5, 1*time.Second),
    ro.Filter(func(x int) bool { return x%2 == 0 }),
    ro.Map(func(x int) string { return fmt.Sprintf("even-%d", x) }),
)

observable.Subscribe(ro.NewObserver(
    func(s string) { fmt.Println(s) },      // onNext
    func(err error) { log.Println(err) },    // onError
    func() { fmt.Println("Done!") },         // onComplete
))
// Output: "even-0", "even-2", "even-4", "Done!"

// Or collect synchronously:
values, err := ro.Collect(observable)

Cold vs Hot Observables

Cold (default): each .Subscribe() starts a new independent execution. Safe and predictable — use by default.

Hot: multiple subscribers share a single execution. Use when the source is expensive (WebSocket, DB poll) or subscribers must see the same events.

Convert withBehavior
Share()Cold → hot with reference counting. Last unsubscribe tears down
ShareReplay(n)Same as Share + buffers last N values for late subscribers
Connectable()Cold → hot, but waits for explicit .Connect() call
SubjectsNatively hot — call .Send(), .Error(), .Complete() directly
SubjectConstructorReplay behavior
PublishSubjectNewPublishSubject[T]()None — late subscribers miss past events
BehaviorSubjectNewBehaviorSubject[T](initial)Replays last value to new subscribers
ReplaySubjectNewReplaySubject[T](bufferSize)Replays last N values
AsyncSubjectNewAsyncSubject[T]()Emits only last value, only on complete
UnicastSubjectNewUnicastSubject[T](bufferSize)Single subscriber only

For subject details and hot observable patterns, see Subjects Guide.

Operator Quick Reference

CategoryKey operatorsPurpose
CreationJust, FromSlice, FromChannel, Range, Interval, Defer, FutureCreate observables from various sources
TransformMap, MapErr, FlatMap, Scan, Reduce, GroupByTransform or accumulate stream values
FilterFilter, Take, TakeLast, Skip, Distinct, Find, First, LastSelectively emit values
CombineMerge, Concat, Zip2Zip6, CombineLatest2CombineLatest5, RaceMerge multiple observables
ErrorCatch, OnErrorReturn, OnErrorResumeNextWith, Retry, RetryWithConfigRecover from errors
TimingDelay, DelayEach, Timeout, ThrottleTime, SampleTime, BufferWithTimeControl emission timing
Side effectTap/Do, TapOnNext, TapOnError, TapOnCompleteObserve without altering stream
TerminalCollect, ToSlice, ToChannel, ToMapConsume stream into Go types

Use typed Pipe2, Pipe3 ... Pipe25 for compile-time type safety across operator chains. The untyped Pipe uses any and loses type checking.

For the complete operator catalog (150+ operators with signatures), see Operators Guide.

Common Mistakes

MistakeWhy it failsFix
Using ro.OnNext() without error handlerErrors are silently dropped — bugs hide in productionUse ro.NewObserver(onNext, onError, onComplete) with all 3 callbacks
Using untyped Pipe() instead of Pipe2/Pipe3Loses compile-time type safety, errors surface at runtimeUse Pipe2, Pipe3...Pipe25 for typed operator chains
Forgetting .Unsubscribe() on infinite streamsGoroutine leak — the observable runs foreverUse TakeUntil(signal), context cancellation, or explicit Unsubscribe()
Using Share() when cold is sufficientUnnecessary complexity, harder to reason about lifecycleUse hot observables only when multiple consumers need the same stream
Using samber/ro for finite slice transformsStream overhead (goroutines, subscriptions) for a synchronous operationUse samber/lo — it's simpler, faster, and purpose-built for slices
Not propagating context for cancellationStreams ignore shutdown signals, causing resource leaks on terminationChain ContextWithTimeout or ThrowOnContextCancel in the pipeline

Best Practices

  1. Always handle all three events — use NewObserver(onNext, onError, onComplete), not just OnNext. Unhandled errors cause silent data loss
  2. Use Collect() for synchronous consumption — when the stream is finite and you need []T, Collect blocks until complete and returns the slice + error
  3. Prefer typed Pipe functionsPipe2, Pipe3...Pipe25 catch type mismatches at compile time. Reserve untyped Pipe for dynamic operator chains
  4. Bound infinite streams — use Take(n), TakeUntil(signal), Timeout(d), or context cancellation. Unbounded streams leak goroutines
  5. Use Tap/Do for observability — log, trace, or meter emissions without altering the stream. Chain TapOnError for error monitoring
  6. Prefer samber/lo for simple transforms — if the data is a finite slice and you need Map/Filter/Reduce, use lo. Reach for ro when data arrives over time, from multiple sources, or needs retry/timeout/backpressure

Plugin Ecosystem

40+ plugins extend ro with domain-specific operators:

CategoryPluginsImport path prefix
EncodingJSON, CSV, Base64, Gobplugins/encoding/...
NetworkHTTP, I/O, FSNotifyplugins/http, plugins/io, plugins/fsnotify
SchedulingCron, ICSplugins/cron, plugins/ics
ObservabilityZap, Slog, Zerolog, Logrus, Sentry, Oopsplugins/observability/..., plugins/samber/oops
Rate limitingNative, Ululeplugins/ratelimit/...
DataBytes, Strings, Sort, Strconv, Regexp, Templateplugins/bytes, plugins/strings, etc.
SystemProcess, Signalplugins/proc, plugins/signal

For the full plugin catalog with import paths and usage examples, see Plugin Ecosystem.

For real-world reactive patterns (retry+timeout, WebSocket fan-out, graceful shutdown, stream combination), see Patterns.

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

Cross-References

  • → See samber/cc-skills-golang@golang-samber-lo skill for finite slice transforms (Map, Filter, Reduce, GroupBy) — use lo when data is already in a slice
  • → See samber/cc-skills-golang@golang-samber-mo skill for monadic types (Option, Result, Either) that compose with ro pipelines
  • → See samber/cc-skills-golang@golang-samber-hot skill for in-memory caching (also available as an ro plugin)
  • → See samber/cc-skills-golang@golang-concurrency skill for goroutine/channel patterns when reactive streams are overkill
  • → See samber/cc-skills-golang@golang-observability skill for monitoring reactive pipelines in production

samberのその他のスキル

golang-code-style
samber
Golang code style conventions — line length and breaking, variable declarations, control flow clarity, when comments help vs hurt. Use when writing or reviewing Go code, asking about style or clarity, or establishing project coding standards. Not for naming conventions (→ See `samber/cc-skills-golang@golang-naming` skill), linter configuration (→ See `samber/cc-skills-golang@golang-lint` skill), or doc comments (→ See `samber/cc-skills-golang@golang-documentation` skill).
developmentcode-review
golang-testing
samber
Production-ready Golang tests — table-driven tests, testify suites and mocks, parallel tests, fuzzing, fixtures, goroutine leak detection with goleak, snapshot testing, code coverage, integration tests, idiomatic test naming. Use when writing or reviewing Go tests, choosing a testing approach, setting up Go test CI, or debugging flaky/slow tests. For testify-specific APIs see `samber/cc-skills-golang@golang-stretchr-testify`; for measurement methodology see...
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慣用的なGo言語のデザインパターン — 関数型オプション、コンストラクタ、エラーフローとカスケード、リソース管理とライフサイクル、グレースフルシャットダウン、耐障害性、アーキテクチャ、依存性注入、データ処理、ストリーミングなど。アーキテクチャパターンを明示的に選択する際、関数型オプションを実装する際、コンストラクタAPIを設計する際、グレースフルシャットダウンを設定する際、耐障害性パターンを適用する際、または特定の問題に適合する慣用的なGoパターンを尋ねる際に適用します。
developmentdesigncode-review
golang-error-handling
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Idiomatic Golang error handling — creation, wrapping with %w, errors.Is/As, errors.Join, custom error types, sentinel errors, panic/recover, the single handling rule, structured logging with slog, HTTP request logging middleware, and samber/oops for production errors. Built to make logs usable at scale with log aggregation 3rd-party tools. Apply when creating, wrapping, inspecting, or logging errors in Go code. For samber/oops specifics → See `samber/cc-skills-golang@golang-samber-oops`...
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golang-performance
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Golangのパフォーマンス最適化パターンと方法論 - XのボトルネックがあればYを適用。アロケーション削減、CPU効率、メモリレイアウト、GCチューニング、プーリング、キャッシング、ホットパス最適化をカバー。プロファイリングやベンチマークでボトルネックが特定され、それを修正するための適切な最適化パターンが必要な場合に使用。また、パフォーマンスコードレビューを行い、改善点や迅速なパフォーマンス向上を特定するのに役立つベンチマークを提案する場合にも使用。測定方法論には使用しない(→...)
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golang-security
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Golangのセキュリティベストプラクティスと脆弱性防止。インジェクション(SQL、コマンド、XSS)、暗号化、ファイルシステムの安全性、ネットワークセキュリティ、クッキー、シークレット管理、メモリ安全性、ログ記録をカバー。Goコードのセキュリティに関する作成、レビュー、監査時、または暗号、I/O、シークレット管理、ユーザー入力処理、認証を含むリスクのあるコードに取り組む際に適用。セキュリティツールの設定を含む。
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golang-database
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Goデータベースアクセスの包括的ガイド — パラメータ化クエリ、構造体スキャン、NULL許容カラム、トランザクション、分離レベル、SELECT FOR UPDATE、コネクションプール、バッチ処理、コンテキスト伝搬、マイグレーションツール。PostgreSQL、MariaDB、MySQL、SQLiteと連携するGolangコードの作成、レビュー、デバッグ時、データベーステスト時、またはdatabase/sql、sqlx、pgxに関する質問時に使用します。データベーススキーマやマイグレーションSQLは生成しません。
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GolangプロジェクトにおけるLintのベストプラクティスとgolangci-lintの設定 — リンターの実行、.golangci.ymlの設定、nolintディレクティブによる警告の抑制、Lint出力の解釈、リンターの選択。golangci-lintの設定時、Lint警告やnolint抑制について質問がある時、コード品質ツールのセットアップ時、またはリンターを選択する時に使用します。また、ユーザーがgolangci-lint、go vet、staticcheck、reviveに言及した場合にも使用します。
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