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Golang Samber Ro

Samuel BertheCommunityCreated by samberDistributed by Samuel Berthe

  • Skill
  • Tool integration
  • Software development
  • MIT
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From the author

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).
— the description by samber

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

samber/ro is a Go implementation of ReactiveX that provides a type-safe, declarative approach to managing asynchronous data streams. It replaces complex, manual goroutine and channel wiring with a composable pipeline architecture. The library features over 150 operators, support for both cold and hot observables, automatic backpressure, and built-in error propagation. It is designed for scenarios involving infinite event streams, real-time data processing, and complex async coordination, offering a robust alternative to standard library concurrency primitives when declarative stream management is required.

What it does

  • Provides 150+ type-safe operators for transforming, filtering, and combining data streams.
  • Supports cold and hot observables for flexible event distribution and resource management.
  • Includes 40+ plugins for common tasks like HTTP, cron, logging, and file system monitoring.
  • Implements automatic backpressure and error propagation across pipeline stages.
  • Integrates natively with Go context for cancellation and timeout management.
  • Offers five subject types for advanced multicast and state-sharing patterns.

When to use it

  • When building infinite event-driven pipelines (e.g., WebSockets, tickers, file watchers).
  • When real-time data enrichment requires combining multiple asynchronous sources.
  • When you need declarative retry, timeout, or fallback logic for remote service calls.
  • When managing pub/sub patterns where multiple consumers share a single data source.
  • When standard goroutine/channel patterns become too verbose or difficult to maintain.

Advantages

  • Reduces boilerplate code compared to manual channel and goroutine management.
  • Enhances code readability through declarative, chainable pipeline operators.
  • Improves reliability with built-in error handling and context-aware cancellation.
  • Provides compile-time type safety via typed Pipe functions.
  • Simplifies complex async coordination like stream merging, zipping, and throttling.

Usage examples

“Create a reactive pipeline that filters even numbers from an interval stream and maps them to strings.”
The agent generates a Pipe2 chain using ro.RangeWithInterval, ro.Filter, and ro.Map, followed by a Subscribe call to handle the output.
“How do I implement a remote API call with retries and a timeout using samber/ro?”
The agent provides a pipeline using ro.Timeout and ro.RetryWithConfig to wrap the API call, ensuring robust execution.
“Show me how to share a single WebSocket stream between two different consumers.”
The agent demonstrates using ro.Share to convert a cold observable into a hot one, allowing multiple subscribers to receive the same events.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/samber/golang-samber-ro/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip golang-samber-ro.zip -d .agents/skills

Documentation by samber

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

Files

references/subjects-guide.md

Subjects Guide

Subjects are both Observable and Observer — they can receive values (via Send, Error, Complete) and be subscribed to. Subjects are natively hot: subscribers share a single execution, and late subscribers only see future emissions (unless replay is configured).

Table of Contents

  • When to Use Subjects vs Cold Observables

  • Subject Types

    • PublishSubject

    • BehaviorSubject

    • ReplaySubject

    • AsyncSubject

    • UnicastSubject

  • Cold to Hot Conversion

    • Share

    • ShareReplay

    • Connectable Observable

  • Subject Decision Table

  • Common Subject Mistakes

When to Use Subjects vs Cold Observables

Use caseApproach
Data pipeline from a known source (slice, channel, HTTP)Cold observable (default)
Event bus where producers and consumers are decoupledSubject
Multiple consumers need the same WebSocket/ticker streamCold observable + Share() or ShareReplay()
Imperatively push values from non-reactive codeSubject
Bridge between callback API and reactive pipelineSubject (receive callbacks, emit to pipeline)

Subject Types

PublishSubject

Standard multicast. Subscribers only see values emitted after they subscribe.

subject := ro.NewPublishSubject[string]()

// Subscriber 1
subject.Subscribe(ro.OnNext(func(s string) {
    fmt.Println("sub1:", s)
}))

subject.Send("hello")  // sub1 sees this

// Subscriber 2 (late)
subject.Subscribe(ro.OnNext(func(s string) {
    fmt.Println("sub2:", s)
}))

subject.Send("world")  // both see this
subject.Complete()

Use when: broadcasting events where late subscribers don't need history — UI events, log streams, notifications.

BehaviorSubject

Replays the last emitted value (or the initial value) to every new subscriber immediately on subscription.

subject := ro.NewBehaviorSubject[int](0) // initial value = 0

// Subscriber 1 immediately receives 0
subject.Subscribe(ro.OnNext(func(v int) {
    fmt.Println("sub1:", v) // 0, then 42
}))

subject.Send(42)

// Subscriber 2 immediately receives 42 (latest value)
subject.Subscribe(ro.OnNext(func(v int) {
    fmt.Println("sub2:", v) // 42
}))

Use when: subscribers need the current state — config values, connection status, latest price.

ReplaySubject

Buffers the last N values and replays them to every new subscriber.

subject := ro.NewReplaySubject[string](3) // buffer size = 3

subject.Send("a")
subject.Send("b")
subject.Send("c")
subject.Send("d") // "a" evicted from buffer

// Late subscriber receives "b", "c", "d" (last 3)
subject.Subscribe(ro.OnNext(func(s string) {
    fmt.Println(s)
}))

Use when: late subscribers need recent history — chat messages, recent logs, last N stock ticks.

AsyncSubject

Emits only the last value and only when the subject completes. If the subject errors, no value is emitted.

subject := ro.NewAsyncSubject[int]()

subject.Subscribe(ro.NewObserver(
    func(v int) { fmt.Println(v) },    // receives 3 only
    func(err error) { },
    func() { fmt.Println("done") },
))

subject.Send(1)
subject.Send(2)
subject.Send(3)
subject.Complete() // triggers emission of 3, then "done"

Use when: only the final result matters — computation result, last response in a batch.

UnicastSubject

Allows exactly one subscriber. Buffers values internally until that subscriber connects.

subject := ro.NewUnicastSubject[int](100) // buffer size

subject.Send(1) // buffered
subject.Send(2) // buffered

// Single subscriber receives buffered + future values
subject.Subscribe(ro.OnNext(func(v int) {
    fmt.Println(v) // 1, 2, then future values
}))
// Second subscribe would panic or error

Use when: single consumer with buffering — job queues, request pipelines where exactly one handler processes events.

Cold to Hot Conversion

When you have a cold observable (e.g. an HTTP request) but need multiple subscribers to share it:

Share
// Each subscriber to `cold` would trigger a separate HTTP request
cold := httpPlugin.Get[Data](url)

// Share: single execution, multiple subscribers
hot := ro.Pipe1(cold, ro.Share[Data]())

hot.Subscribe(uiObserver)       // shares one HTTP call
hot.Subscribe(metricsObserver)  // same data, no extra request

Share uses reference counting: the source subscribes when the first subscriber arrives and unsubscribes when the last one leaves.

ShareReplay
// Late subscribers get the last N values + future values
hot := ro.Pipe1(cold, ro.ShareReplay[Data](1))
Connectable Observable

For precise control over when the shared subscription starts:

connectable := ro.Connectable[Data](cold)

// Set up subscribers first
connectable.Subscribe(observer1)
connectable.Subscribe(observer2)

// Start the shared execution explicitly
sub, err := connectable.Connect(ctx)

Subject Decision Table

SubjectReplaySubscribersUse case
PublishSubjectNoneManyEvent bus, notifications
BehaviorSubjectLast 1 (+ initial)ManyCurrent state, config
ReplaySubjectLast NManyRecent history, chat
AsyncSubjectLast 1 (on complete)ManyFinal computation result
UnicastSubjectBuffered (pre-subscribe)Exactly 1Single-consumer queue

Common Subject Mistakes

MistakeWhyFix
Calling Send() after Complete()Values are silently dropped — the subject is terminalTrack lifecycle, don't reuse completed subjects
Using PublishSubject when late subscribers need historyLate subscribers miss all prior eventsUse BehaviorSubject (last 1) or ReplaySubject (last N)
Using ReplaySubject with unbounded bufferMemory grows without limitSet an explicit bufferSize
Multiple subscribers on UnicastSubjectPanics or undefined behaviorUse PublishSubject for multicast, UnicastSubject for single consumer
Not calling Complete() on subjectsSubscribers wait forever, goroutine leakAlways Complete() or Error() when the source is done

Requirements and compatibility

Written for: Claude Code, OpenAI Codex

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Declares allowed tools, Claude Code frontmatter

The author says: Designed for Claude Code, Codex or similar harness, and for projects using Golang.

Security

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Attribution and licence

Created by
samber
Publisher
Samuel Berthe (Community)
Distributed by
Samuel Berthe
Source
samber/cc-skills-golang · skills/golang-samber-ro · commit bb1d43d
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
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