Scraping Wikipedia: Bulk Data Extraction and API Usage

Wikipedia is one of the largest knowledge bases on the internet, making it a goldmine for data extraction projects. In this guide, we'll explore how to scrape Wikipedia efficiently using Python — both through its official API and direct HTML parsing. Why Scrape Wikipedia? Whether you're building a knowledge graph, training an NLP model, or collecting structured data for research, Wikipedia offers: Millions of articles across every topic imaginable Structured data through infoboxes, tables, and categories A free API with generous rate limits Regular updates with community-maintained accuracy Method 1: Using the Wikipedia API The MediaWiki API is the cleanest way to extract data. No HTML parsing needed. import requests def get_wikipedia_article ( title ): url = " https://en.wikipedia.org/w/api.php " params = { " action " : " query " , " titles " : title , " prop " : " extracts|pageimages|categories " , " exintro " : True , " explaintext " : True , " format " : " json " } response = reque