# Yixiaohan/codeparkshare

Python初学者（零基础学习Python、Python入门）书籍、视频、资料、社区推荐

Repository: https://github.com/Yixiaohan/codeparkshare
Canonical: https://ross.abutalabs.com/products/codeparkshare
License Family: other
Topics: tutorial, python, newbie, beginner
Last push: 2019-01-14T07:50:30+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 4917, "days_push": 2788, "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 6315, forks 1386 (observed 2026-08-28T04:09:41.701979+00:00)

## What it is
A curated Chinese-language resource list for absolute beginners learning Python, collecting recommended books, videos, tutorials, communities, and learning methods. It is a documentation-style guide rather than software.

## Use cases
- learn python from scratch
- find beginner python books
- python learning resources for non-programmers
- python video courses for beginners
- how to start learning python with no background
- python tutorials in chinese

## When to choose
- you are a complete beginner wanting curated Python learning materials
- you prefer Chinese-language books, videos, and tutorials
- you want community advice on how to study Python effectively

## When to avoid
- you need runnable code or a software tool
- you are an experienced Python developer seeking advanced references
- you need up-to-date resources - the list was last updated around 2019

## Facets
- artifact type: learning-resource
- maturity: maintenance
- function: documentation
- domain: tutorials, programming-languages, education
- platform: cross-platform
- tags: python, beginner, curated-list, awesome-list, chinese

## Member repositories
- Yixiaohan/codeparkshare (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:09:41.701979+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 2026-08-29T17:46:12.226401+00:00, confidence not recorded.
  - readme: https://github.com/Yixiaohan/codeparkshare (fetched 2026-08-28T04:09:41.701979+00:00, sha 146fe2051c0b)
- Data as of 2026-08-30T08:39:29.467469+00:00.