📅 2025-06-11 — Session: Developed and Optimized Web Scraping Pipelines
🕒 15:40–18:50
🏷️ Labels: Web Scraping, Python, Data Pipeline, Error Handling, Soap Notes
📂 Project: Dev
Session Goal
The session aimed to develop and optimize web scraping pipelines using Python and Selenium, while also addressing data management and error handling challenges.
Key Activities
- Created a structured SOAP note template for various medical procedures, including hernioplasty, tubal ligation, and perineoplasty, to ensure comprehensive patient care documentation.
- Conducted a detailed analysis of existing data processing pipelines, identifying strengths and weaknesses, and provided recommendations for improvements in error handling and scalability.
- Designed a new RSS article fetching pipeline, focusing on separating article indexing from scraping.
- Developed a Python script for managing a master article index, including deduplication and incremental updates.
- Implemented error handling strategies for common issues like KeyError in DataFrame processing and JSON serialization of Pandas timestamps.
- Proposed enhancements to scraping scripts, including temporal filtering and backlog management, to improve efficiency and reliability.
Achievements
- Successfully created and optimized multiple components of the web scraping pipeline, enhancing data processing and error handling capabilities.
- Developed comprehensive SOAP note templates for medical documentation, improving patient care records.
Pending Tasks
- Further refine the scraping scripts to handle additional edge cases and improve processing speed.
- Continue to monitor and adjust the pipeline for scalability and robustness as more data is processed.