GitHub Data Mining: Extract Repos, Stars, and Contributors with Python

Why Mine GitHub Data? GitHub hosts over 200 million repositories and 100 million developers. Mining this data enables powerful use cases: Developer analytics — Track trending technologies and skill demand Competitive intelligence — Monitor competitor open-source activity Talent sourcing — Find developers by contribution patterns Technology trends — Identify rising frameworks and tools Open source health — Evaluate project sustainability This guide covers both GitHub's API and web scraping techniques for large-scale data extraction. GitHub REST API: The Foundation GitHub's API is well-documented and generous — 5,000 requests/hour with authentication. Setup import requests import time from datetime import datetime , timedelta class GitHubClient : BASE_URL = ' https://api.github.com ' def __init__ ( self , token = None ): self . session = requests . Session () self . session . headers . update ({ ' Accept ' : ' application/vnd.github.v3+json ' , ' User-Agent ' : ' DataMiner/1.0 ' }) if to