📅 2025-06-21 — Session: Debugged and Enhanced Article Processing Pipeline
🕒 23:05–23:25
🏷️ Labels: Python, Debugging, Data_Processing, Media_Monitoring, Automation
📂 Project: Media
⭐ Priority: MEDIUM
Session Goal
The primary aim of this session was to diagnose and resolve issues within the article processing pipeline, ensuring robust data handling and integration with existing media monitoring systems.
Key Activities
- Debugging Data Format Issues: Identified and proposed solutions for problems in data interpretation that were preventing the correct retrieval of new articles.
- Handling Format Coexistence: Developed code to manage both nested and flat formats in PromptFlow outputs, ensuring seamless integration of new articles without duplication.
- Enrichment Process Correction: Diagnosed and implemented solutions to maintain data consistency during article enrichment in the scraping process.
- Manual Pipeline Execution: Provided instructions for manually executing the updated explosion and enrichment pipeline, including necessary code adjustments for argument parsing.
- Error Resolution in DataFrames: Addressed common errors such as TypeError and KeyError in Pandas DataFrames, offering solutions to handle non-hashable types and missing columns.
- Media Monitoring Integration: Finalized the integration of a scraping script into the media monitoring pipeline, focusing on unique ID propagation and article filtering.
Achievements
- Successfully debugged and enhanced the article processing pipeline, ensuring robust data handling and integration.
- Improved error handling in data manipulation processes, reducing the likelihood of runtime errors.
Pending Tasks
- Further testing of the enhanced pipeline in a production environment to ensure stability and performance.
- Consider additional improvements for robustness in the media monitoring pipeline.