# code4craft/netty-learning

Netty learning.

Repository: https://github.com/code4craft/netty-learning
Canonical: https://ross.abutalabs.com/products/netty-learning
Language: Java
License Family: other
Last push: 2017-02-07T08:39:36+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4732, "days_push": 3494, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases, no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3544, forks 1178 (observed 2026-08-28T04:08:09.357978+00:00)

## What it is
A series of Chinese-language articles guiding readers through the Netty source code, covering its architecture, buffers, pipelines, and the Reactor pattern. It also includes practical examples like building a SOCKS proxy with Netty and links to other learning materials.

## Use cases
- understand how Netty works internally
- learn high-performance network programming in Java
- study the Reactor pattern through real code
- prepare for deep-diving into Netty source code
- learn how to build a SOCKS proxy with Netty

## When to choose
- you use Netty at work and want deeper understanding
- you are interested in Java NIO and network framework internals
- you want to learn good code organization from a mature framework

## When to avoid
- you need up-to-date coverage of recent Netty versions
- you want a hands-on tutorial rather than source-code reading
- you need English-language documentation

## Facets
- artifact type: learning-resource
- maturity: abandoned
- function: documentation, developer-tools
- domain: networking, developer-tools, tutorials
- platform: jvm
- tags: netty, source-code-analysis, java-nio, reactor-pattern, tutorial-series

## Member repositories
- code4craft/netty-learning (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:09.357978+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:34:25.808890+00:00, confidence not recorded.
  - readme: https://github.com/code4craft/netty-learning (fetched 2026-08-28T04:08:09.357978+00:00, sha 5b23e16258af)
- Data as of 2026-08-30T08:39:29.467469+00:00.