📅 2025-07-14 — Session: Enhanced Web Scraping Pipeline Using Spider API
🕒 03:00–03:20
🏷️ Labels: Spider Api, Web Scraping, Automation, Python, Data Extraction
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal:
The session aimed to enhance the web scraping pipeline by integrating the Spider API, replacing legacy systems, and improving data extraction processes for job listings.
Key Activities:
- Provided a step-by-step guide for creating a minimal JSONL input file to execute the Spider API for web scraping.
- Scraped job listings from BaxEnergy’s careers page using a Python script, including command-line execution and content verification.
- Successfully invoked a web scraping spider and verified meaningful content extraction from a specified URL.
- Compared Spider API’s advantages over Playwright for web scraping, suggesting enhancements for the scraping pipeline.
- Outlined a structured upgrade path for the web scraper, focusing on modularity, logging, and optional cost tracking.
- Conducted a quality analysis of scraped job entries, providing specific suggestions for improvement.
- Analyzed and recommended strategies for improving job scraping processes and categorizing job sources.
- Proposed enhancements and best practices for a Python script utilizing the Spider API, focusing on configurability and robustness.
- Suggested improvements to the web scraping pipeline, including following inner links and detecting low-content pages.
- Refactored a Python script to replace a Selenium call with a Spider-based call, detailing necessary adjustments.
Achievements:
- Successfully integrated the Spider API into the web scraping pipeline, replacing legacy Selenium calls.
- Improved the robustness and modularity of the web scraping scripts.
- Developed strategies for enhancing data extraction processes and pipeline efficiency.
Pending Tasks:
- Further refine the scraping process to handle more complex job listing structures.
- Implement additional logging and cost tracking features as outlined in the upgrade path.