#github

Build a daily GitHub trending-developers dataset with Python by extracting names, usernames, avatars, and popular repos from the live page.

Collect repository cards, stars, languages, repo URLs, and update timestamps from GitHub topic pages into a niche-watch dataset.

Build a daily GitHub Trending dataset with Python: collect repository names, languages, star counts, and URLs, then export clean CSV or JSON with an optional ProxiesAPI fetch layer.

Collect repo names, stars, forks, topics, and last-updated metadata from GitHub pages for market and competitor research.

Collect release tags, publish dates, changelog text, and asset links from GitHub Releases pages with Python so you can monitor repos automatically.

Collect GitHub repository metadata, stars, forks, topics, and README-linked context from the public HTML with Python. Includes defensive selectors, CSV export, and a screenshot.

Build a GitHub pull request queue from public HTML: collect PR titles, numbers, labels, comments, authors, timestamps, and draft status so you can triage reviews without the API.

Build a practical GitHub Issues scraper in Python: parse issue rows, collect labels + state + dates, follow pagination, and export a triage-ready CSV. Includes screenshot + working code.

Scrape GitHub repo metadata from HTML (not just the API): stars, forks, latest release, open issues, and pull requests. Includes a ProxiesAPI fetch layer, safe parsing, and CSV export + screenshot.

A practical GitHub Trending scraper: fetch the Trending page, extract repo names + language + stars, and export a clean dataset.

Scrape a GitHub Releases page, extract versions and release notes, and store structured data so you can alert on changes.