Enhanced Data Processing and Digest Generation

📅 2025-06-11 — Session: Enhanced Data Processing and Digest Generation

🕒 03:30–04:50
🏷️ Labels: Python, Data Processing, Markdown, File Management
📂 Project: Dev
⭐ Priority: MEDIUM

The session aimed to enhance data processing capabilities and improve the generation of markdown digest files from DataFrames.

Enhanced a Python function for topic-based grouping in DataFrames, ensuring data integrity and consistent subgroup identification.
Revised strategy for DataFrame storage and markdown digest generation with improved file naming conventions.
Updated fetch_and_save_news() function to assign unique IDs to articles, improving downstream processing.
Proposed a new naming convention for CSV files generated during slicing, enhancing organization and traceability.
Refined functions for saving digest files, incorporating improved naming conventions and metadata collection.
Utilized glob to process CSV files and generate markdown digests with sanitized topics and structured output.
Enhanced markdown digest composition by including metadata such as links, publication dates, and sources.
Refined group splitting logic to ensure even distribution and consistent labeling of groups.
Fixed grouping logic in digest files to prevent mixing articles from different topics.
Updated date formatting in markdown files to include hours in 24-hour format.

Successfully implemented enhancements in data processing and digest generation, improving the overall workflow and output quality.

Further testing of the new file naming conventions and digest generation process to ensure robustness and accuracy.