YouTube Scraper Live
Completed November 2023
PythonWeb ScrapingDataAutomation
Overview
YouTube Scraper is a high-performance data extraction tool designed for researchers and analysts. It automates the process of gathering comprehensive data from YouTube channels and individual videos, providing structured outputs suitable for sentiment analysis, trend tracking, and competitive research.
Features
- Channel Metadata Extraction — Capture subscriber counts, total views, and video counts
- Video Engagement Stats — Extract likes, comments, and view duration trends
- Transcript Automation — Automatically download and clean video transcripts for NLP tasks
- Comment Analysis — Scrape thousands of comments for sentiment and keyword analysis
- Proxy Support — Built-in rotation to handle large-scale extraction without throttling
Technologies Used
- Python — Core logic and async execution
- Playwright / Selenium — For dynamic content rendering
- BeautifulSoup4 — Static HTML parsing
- Pandas — Data structuring and cleaning
- SQLite — Local caching of results
How It Works
- Input Configuration — Define target channels or video lists
- Dynamic Crawling — Playwright navigates the UI to trigger infinite scroll/dynamic loads
- Parsing Engine — Extracts specific entities (Title, View count, Upload date)
- Transcription Fetch — Uses internal APIs to retrieve available CC/Transcripts
- Output Generation — Exports results to CSV, JSON, or direct database insert
Built with ❤️ by Hassan Ali