golang-samber-ro

Generate reactive pipelines in Go for asynchronous event streams.

Updated Mar 8, 2026
One-click install
npx skills add https://github.com/tamago0224/kuroshio-mta --skill golang-samber-ro-tamago0224
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: golang-samber-ro
Source: https://github.com/tamago0224/kuroshio-mta/tree/main/.agents/skills/golang-samber-ro
Command: npx skills add https://github.com/tamago0224/kuroshio-mta --skill golang-samber-ro-tamago0224

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

It simplifies building asynchronous, event‑driven pipelines in Go by offering a type‑safe, composable ReactiveX‑style library that handles backpressure, error propagation, and context integration.

Core Features & Use Cases

  • Typed operators (Pipe1Pipe25) ensure compile‑time safety.
  • Cold & hot observables with Share, ShareReplay, and subjects for multicasting.
  • Rich plugin ecosystem (HTTP, cron, fsnotify, observability, etc.) to extend pipelines.
  • Use cases include real‑time sensor processing, WebSocket event distribution, batch API calls with retry, and file‑system watchers.

Quick Start

Use the golang-samber-ro skill to generate a filtered string list from a range of numbers.

Frequently Asked Questions about golang-samber-ro

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I build reactive pipelines in Go for asynchronous event streams?

Reactive pipelines in Go handle asynchronous event streams by using a type-safe, composable library with operators like Pipe1 to Pipe25, ensuring compile-time safety while managing data flow, backpressure, and context integration for real-time processing.

What is the best way to handle backpressure in an event-driven Go service?

Handling backpressure in event-driven Go services is managed through ReactiveX-style typed operators and observables, which automatically propagate errors and respect context cancellation to safely control asynchronous data flow without overwhelming consumers.

Can I use Go observables for WebSocket event distribution and real-time processing?

Go observables support WebSocket event distribution and real-time processing through hot observables and multicasting features like Share and ShareReplay, allowing simultaneous event streaming to multiple subscribers in asynchronous pipelines.

Do I need a specific Go environment setup to use typed operators for event streams?

A Go environment setup is required to use typed operators for event streams, necessitating the samber/ro library for core reactive functionality and optional plugins for networking, scheduling, or observability extensions.

How does multicasting work with hot and cold observables in Go pipelines?

Multicasting with hot and cold observables in Go pipelines works by using Share and ShareReplay operators alongside subjects, transforming single-execution cold streams into shared hot streams that distribute events to multiple concurrent subscribers.

When should I not use reactive pipelines for event-driven Go applications?

Reactive pipelines for event-driven Go applications should be avoided when your use case involves simple synchronous request-response patterns without continuous data streams, as the overhead of observables and backpressure management adds unnecessary complexity.