Developed and Optimized Web Scraping Pipelines

Day: 2025-06-11
Time: 15:40 to 18:50
Project: Dev
Workspace: WP 2: Operational
Status: Completed
Priority: MEDIUM
Assignee: Matías Nehuen Iglesias
Tags: Web Scraping, Python, Data Pipeline, Error Handling, Soap Notes

Description

The session aimed to develop and optimize web scraping pipelines using Python and Selenium, while also addressing data management and error handling challenges.

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.

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.

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.

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