caojiaolong

caojiaolong / spaces-index

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本项目自动抓取并索引科学空间的文章元数据，按研究主题进行规则分类，方便在 GitHub 上快速浏览并跳转到原文。

45
0
100% credibility
Found May 04, 2026 at 45 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

An open-source indexer that fetches metadata from science blog articles, classifies them by topics like deep learning and mathematics, and generates browsable Markdown pages with links to originals.

How It Works

1
🔍 Discover the Science Index

You find this GitHub collection that neatly organizes hundreds of insightful articles on AI, math, physics, and more from a popular science blog.

2
📋 Browse the Welcome Page

The main page greets you with a clear directory of topics, recent articles, and quick links to jump right in.

3
🌟 Pick Your Interest

You choose a topic like 'Big Models' or 'Math Tools' and see articles beautifully grouped into series or standalone reads.

4
📖 Dive into Details

Each section shows article dates, tags, short previews, and series info, making it feel like a personalized library.

5
🔗 Read the Full Story

With one click, you head to the original blog to enjoy the complete article in its natural home.

✅ Master New Ideas Easily

You effortlessly stay updated on cutting-edge science topics without endless searching, feeling smarter every visit.

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Star Growth

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AI-Generated Review

What is spaces-index?

spaces-index is a Python scraper that pulls article metadata from spaces.ac.cn, a Chinese science blog on ML and math, then classifies posts into topics like transformers, optimization, and embeddings. It detects series, extracts tags and summaries, and renders searchable Markdown pages for GitHub Pages or local viewing. Developers get a clean index to browse hundreds of posts with direct links to originals, solving stale manual GitHub repos of curated content.

Why is it gaining traction?

It auto-updates via GitHub Actions, keeping topic indexes fresh without user effort – unlike static GitHub Pages lists or Zhihu compilations that lag. Rule-based classification and series grouping make discovery fast in a GitHub repo format, with CLI scripts like update_all.py for custom runs using github_token if needed. Python simplicity hooks devs building personal index spaces over clunky alternatives.

Who should use this?

ML researchers following Su Jianlin's posts on big models or math tools, Chinese AI students needing topic-sorted archives, or GitHub Pages users indexing niche blogs. Ideal for devs in github_workspace scripting quick scrapers, not full search setups.

Verdict

Grab it for a ready index spaces melbourne-style niche if you're in AI/math – 45 stars and 1.0% credibility score show it's early but functional with solid Python deps and docs. Run locally via uv sync and CLI; skip for production-scale indexing.

(187 words)

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