📅 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.