📅 2025-07-14 — Session: Developed and Optimized Headless Scraping Solutions
🕒 01:15–02:25
🏷️ Labels: Web Scraping, Headless Browser, Automation, Fastapi, Playwright
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The session aimed to enhance and optimize web scraping techniques using headless browsers, focusing on automation and efficiency.
Key Activities
- Fixed Clipboard Issues: Addressed
pyperclip.paste()
failures in headless Chrome by using Selenium for HTML extraction. - Job Data Extraction: Developed strategies for extracting job information using JSON-LD and HTML snippets.
- Streamlit App Alternatives: Explored alternatives for text extraction beyond Streamlit limitations.
- Automation Strategies: Planned various approaches for automating web content extraction using browser extensions and desktop apps.
- Cloud-Based Scraping: Outlined the setup for cloud services using headless browsers.
- Resource Usage Reflection: Analyzed the resource demands of headless browsers for scaling.
- Scaling Strategies: Planned scaling for real browsing simulation using headless browsers.
- API Development: Set up a headless browser scraper API with FastAPI and Playwright.
- Testing and Debugging: Tested scrapers on JavaScript-heavy pages and resolved DNS errors.
- Microservice Development: Built and Dockerized a headless scraping microservice.
- Cookie Consent Handling: Implemented multilingual consent handling and refactored code for better management.
- Spider API Investigation: Explored Spider API capabilities for handling dynamic content and anti-bot systems.
Achievements
- Successfully set up and tested a headless browser scraper API.
- Developed a scalable solution for web scraping using cloud services.
- Implemented effective cookie consent handling across languages.
Pending Tasks
- Further investigation into Spider API’s full capabilities and integration.
- Continuous optimization of resource usage in headless browsers.