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golang-samber-ro

samber/cc-skills-golang

Reactive streams and event-driven programming in Go with 150+ type-safe operators, subjects, and plugins.

What is golang-samber-ro?

samber/ro is a ReactiveX implementation for Go that enables declarative, composable pipelines for asynchronous and infinite data streams. Use it when building event-driven architectures, real-time data processing, or complex async workflows where manual goroutine/channel wiring becomes unwieldy.

  • 150+ type-safe operators (Map, Filter, FlatMap, Merge, Zip, CombineLatest, Retry, Timeout, etc.) chainable via Pipe
  • 5 subject types (Publish, Behavior, Replay, Async, Unicast) for hot observables and pub/sub patterns
  • Cold and hot observables with Share, ShareReplay, and Connectable for controlling subscription behavior
  • Automatic backpressure, error propagation, and Go context integration throughout pipelines
  • 40+ plugins (HTTP, cron, fsnotify, JSON, logging) for common async sources and sinks
  • Lazy evaluation and time-aware operators (Delay, Throttle, Interval, Timeout, Buffer)

How to install golang-samber-ro

npx skills add https://github.com/samber/cc-skills-golang --skill golang-samber-ro
Prerequisites
  • Go installed (go command available)
  • github.com/samber/ro imported in your project (go get github.com/samber/ro)
Claude Code
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How to use golang-samber-ro

  1. 1.Identify your data source (channel, ticker, API, file watcher) and wrap it in an observable using From*, Range, Interval, or a Subject
  2. 2.Chain operators via Pipe2–Pipe25 (typed) or Pipe (untyped) to transform, filter, combine, or handle errors
  3. 3.Decide if you need a cold observable (default, safe) or hot observable (Share, ShareReplay, Subject) based on subscriber count and source cost
  4. 4.Subscribe with an Observer (onNext, onError, onComplete callbacks) or use terminal operators like Collect, ToSlice, or ToChannel
  5. 5.Call .Wait() to block until completion or .Unsubscribe() to cancel early; use context integration for graceful shutdown

Use cases

Good for
  • Build WebSocket or file-watcher pipelines with declarative operators instead of manual select loops
  • Combine multiple async data sources (APIs, database polls, event streams) with CombineLatest or Zip
  • Implement retry logic, timeouts, and error recovery across complex async workflows
  • Create pub/sub systems where multiple subscribers share a single expensive source via hot observables
  • Transform infinite event streams in real-time with backpressure-aware operators
Who it's for
  • Go engineers building asynchronous or event-driven systems
  • Teams adopting reactive programming patterns to replace manual goroutine/channel wiring
  • Developers working with infinite or long-lived data streams (WebSockets, sensors, event buses)
  • Projects requiring composable, declarative async pipelines with built-in error handling

golang-samber-ro FAQ

When should I use samber/ro instead of samber/lo or plain goroutines?

Use samber/ro for infinite or long-lived async streams (WebSockets, tickers, event buses). Use samber/lo for finite slice transforms. Use plain goroutines or errgroup only for simple, bounded concurrency without complex operator composition.

What is the difference between cold and hot observables?

Cold observables (default) execute independently for each subscriber — safe and predictable. Hot observables (Share, Subjects) share a single execution across subscribers — use when the source is expensive or subscribers must see the same events.

How do I combine multiple async sources?

Use Merge (all values from all sources), Zip (tuples when all emit), CombineLatest (latest from each), or Race (first to emit). Choose based on whether you want all events, synchronized tuples, or latest values.

How does error handling work in samber/ro?

Errors propagate through the pipeline and trigger the onError callback. Use Catch, OnErrorReturn, OnErrorResumeNextWith, or Retry operators to recover and continue the stream.

What are subjects and when do I use them?

Subjects are hot observables you control directly: call .Send() to emit, .Error() to propagate errors, .Complete() to finish. Use PublishSubject for simple pub/sub, BehaviorSubject to replay the last value, or ReplaySubject to buffer N past values.

Full instructions (SKILL.md)

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


name: golang-samber-ro description: "Reactive streams and event-driven programming in Golang using samber/ro — ReactiveX implementation with 150+ type-safe operators, cold/hot observables, 5 subject types (Publish, Behavior, Replay, Async, Unicast), declarative pipelines via Pipe, 40+ plugins (HTTP, cron, fsnotify, JSON, logging), automatic backpressure, error propagation, and Go context integration. Apply when using or adopting samber/ro, when the codebase imports github.com/samber/ro, or when building asynchronous event-driven pipelines, real-time data processing, streams, or reactive architectures in Go. Not for finite slice transforms (→ See samber/cc-skills-golang@golang-samber-lo skill)." user-invocable: true license: MIT compatibility: Designed for Claude Code, Codex or similar harness, and for projects using Golang. metadata: author: samber version: "1.2.2" openclaw: emoji: "👁" homepage: https://github.com/samber/cc-skills-golang requires: bins: - go install: [] skill-library-version: "0.3.0" allowed-tools: Read Edit Write Glob Grep Bash(go:) Bash(golangci-lint:) Bash(git:) Agent mcp__context7__resolve-library-id mcp__context7__query-docs AskUserQuestion Bash(godig:) Bash(gopls:) LSP mcp__gopls__ paths:

  • "**/*.go"

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: Reason as thoroughly as possible when designing advanced reactive pipelines or choosing between cold/hot observables, subjects, and combining operators — wrong architecture leads to resource leaks or missed events. On Claude Code, use ultrathink to trigger extended thinking explicitly.

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 — refer to library documentation and code examples for more information:

  • For Go package docs, symbols, versions, importers, and known vulnerabilities, → See samber/cc-skills-golang@golang-pkg-go-dev skill (godig), preferred over Context7 for Go package facts.
  • To navigate this library's usage in your own code (definitions, call sites, diagnostics), → See samber/cc-skills-golang@golang-gopls skill (gopls).
  • Context7 remains a fallback for docs not indexed on pkg.go.dev.

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, Zip2–Zip6, CombineLatest2–CombineLatest5, 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 functions — Pipe2, 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