How to Scrape YouTube in 2026: Videos, Channels, Comments, and Metadata

YouTube hosts over 800 million videos. Whether you're building a competitor analysis tool, tracking trends, or collecting training data — extracting YouTube data programmatically is a common need. In this guide, I'll walk you through the practical ways to scrape YouTube in 2026: what data you can get, Python code examples, and when to use the official API vs web scraping. What YouTube Data Can You Extract? You can collect: Video metadata : title, description, view count, likes, upload date, duration, tags Channel info : subscriber count, total videos, channel description, creation date Comments : text, author, likes, reply count, timestamps Search results : videos matching keywords, filters by date/relevance/views Playlists : video lists, playlist metadata Method 1: YouTube Data API v3 The official API is the cleanest option for structured data. Setup import requests API_KEY = ' YOUR_YOUTUBE_API_KEY ' BASE_URL = ' https://www.googleapis.com/youtube/v3 ' def get_video_details ( video_id