Refactored and Improved Data Processing Pipeline

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📅 2025-06-11 — Session: Refactored and Improved Data Processing Pipeline

🕒 21:00–23:55
🏷️ Labels: Data Processing, Pipeline, Python, UID, Deduplication
📂 Project: Dev
⭐ Priority: MEDIUM

Session Goal

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

Key Activities

  • Developed a robust mapping strategy for article IDs to index IDs for LLM integration.
  • Addressed CSV concatenation errors and JSONL file validation issues.
  • Implemented error handling for missing JSONL files and resolved ValueErrors in JSON processing.
  • Automated the generation of Markdown and JSONL digests from CSVs, with scheduling capabilities.
  • Refactored the news fetching logic to include deduplication and additional columns for unique identification.
  • Conducted a design review of the update_master_index_from_directory function, suggesting enhancements for modularity and idempotence.
  • Proposed a multi-step pipeline analysis and refactor, focusing on modular design and improved orchestration.

Achievements

  • Successfully refactored the digest generation script to improve article ID handling and UID propagation.
  • Enhanced the UID-based scraping script for better stability and output integrity.
  • Conducted a critical analysis of the digest grouping and JSONL generator, proposing fixes for correctness and reproducibility.

Pending Tasks

  • Further audit and refine the pipeline orchestration layer to ensure seamless data management and execution flow.
  • Implement the proposed modular design for the data processing pipeline to enhance flexibility and scalability.

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