# 521xueweihan/python

《笨方法学 Python》（Learn Python the Hard Way）学习笔记

Repository: https://github.com/521xueweihan/python
Canonical: https://ross.abutalabs.com/products/521xueweihan-python
Language: Python
License Family: other
Topics: python
Last push: 2023-12-16T17:56:58+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4135, "days_push": 991, "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 1426, forks 424 (observed 2026-08-28T04:04:41.683003+00:00)

## What it is
A collection of study notes and completed exercise code from working through Zed Shaw's 'Learn Python the Hard Way' book. Each exercise file contains the typed-out code plus the author's insights and summaries as comments.

## Use cases
- learn python from scratch with exercises
- find solutions to learn python the hard way exercises
- study python basics with worked examples
- beginner python practice code
- python learning notes in chinese

## When to choose
- you are a beginner following Learn Python the Hard Way and want reference solutions
- you prefer learning by typing out and running every exercise yourself
- you want Chinese-language notes alongside the book

## When to avoid
- you need a maintained library or tool for production use
- you want a structured course rather than personal notes
- you need up-to-date Python 3 idioms, as the book targets older Python

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: developer-tools
- domain: education, programming-languages, tutorials
- platform: python, cross-platform
- tags: study-notes, learn-python-the-hard-way, beginner, exercises, chinese

## Member repositories
- 521xueweihan/python (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:04:41.683003+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 2026-08-30T04:37:24.736369+00:00, confidence not recorded.
  - readme: https://github.com/521xueweihan/python (fetched 2026-08-28T04:04:41.683003+00:00, sha 03fecb7f5481)
- Data as of 2026-08-30T08:39:29.467469+00:00.