πŸ“… 2025-06-11 β€” Session: Refactored and Enhanced Data Processing Pipeline

πŸ•’ 21:00–23:50
🏷️ Labels: Data Processing, Pipeline, UID, Deduplication, Automation
πŸ“‚ Project: Dev
⭐ Priority: MEDIUM

Session Goal

The primary objective of this session was to improve and refactor the data processing pipeline, focusing on UID integrity, deduplication logic, and file tracking durability.

Key Activities

  • Mapping Article IDs to Index IDs: Implemented a strategy to reconcile natural article IDs with index IDs for LLM integration.
  • Error Handling: Addressed issues with CSV concatenation and JSONL file management, including troubleshooting steps for missing files and syntax errors in Python.
  • Digest Generation: Automated the generation of digests in Markdown and JSONL formats, ensuring robust error handling and UID propagation.
  • Pipeline Analysis: Conducted a critical analysis of the digest grouping and JSONL generator, proposing fixes for correctness and reliability.
  • Design Review: Reviewed the update_master_index_from_directory function to enhance modularity and idempotence.
  • Script Enhancements: Improved the UID-based scraping script and refactored the news fetching logic to include deduplication.

Achievements

  • Successfully mapped and reconciled article IDs, enhancing the pipeline’s data integrity.
  • Implemented robust error handling mechanisms for CSV and JSONL file operations.
  • Automated digest generation, improving efficiency and accuracy.
  • Conducted a thorough pipeline analysis, identifying critical issues and proposing actionable solutions.

Pending Tasks

  • Further refactor the pipeline for modularity and better orchestration.
  • Implement the proposed design criteria for article_id in CSV files.
  • Continue auditing the pipeline’s orchestration and structure.

Outcome

The session resulted in significant improvements to the data processing pipeline, with enhanced error handling, automation, and data integrity.