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 (Pipe1‑Pipe25) 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.