samber/cc-skills-golangMIT6 files

Golang Samber Ro

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).

Specification
Skill ID
samber/cc-skills-golang/golang-samber-ro
Publisher
samber
Repository
cc-skills-golang
Installs
0
Files
6
License
MIT
Requires
Designed for Claude Code, Codex or similar harness, and for projects using Golang.
Synced
Sep 16, 2026
How to use it

Open any RiverX project, open the Skills panel in the chat, and search for this identifier. The files are fetched from the source repository at install time.

samber/cc-skills-golang/golang-samber-roInstalls these files
  • SKILL.md
  • evals/evals.json
  • references/operators-guide.md
  • references/patterns.md
  • references/plugin-ecosystem.md
  • references/subjects-guide.md

What this skill tells the agent

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, 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

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