π 2025-06-11 β Session: Refactored and Enhanced Data Processing Pipeline
π 21:00β23:50
π·οΈ Labels: Data Processing, Pipeline, UID, Deduplication, Automation
π Project: Dev
β 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 pipelineβs 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 pipelineβs orchestration and structure.
Outcome
The session resulted in significant improvements to the data processing pipeline, with enhanced error handling, automation, and data integrity.