Enhanced News Scraping and Storage Pipeline

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📅 2024-10-01 — Session: Enhanced News Scraping and Storage Pipeline

🕒 03:10–03:55
🏷️ Labels: News Scraping, Automation, NLP, Debugging, Database
📂 Project: Media
⭐ Priority: MEDIUM

Session Goal

The objective of this session was to enhance a news scraping setup by expanding content extraction capabilities, implementing unstructured data storage with MongoDB, integrating NLP for keyword extraction and classification, and automating the triage of news articles.

Key Activities

  • Developed a comprehensive plan for a news processing pipeline, focusing on automation and NLP integration.
  • Outlined the implementation plan for a NewsDataCollector bot to scrape news from RSS feeds and store them in a SQLite database.
  • Implemented verbose testing for the NewsDataCollector to ensure data integrity and trace execution flow.
  • Enhanced a Python function for news collection with verbose print statements for debugging.
  • Debugged issues related to database storage, specifically addressing errors in the save_to_db function.
  • Revised the save_to_db method to ensure the news table exists before data insertion, preventing operational errors.

Achievements

  • Successfully outlined and partially implemented a robust framework for automated news scraping and storage.
  • Improved error handling and debugging capabilities in the news data collection process.

Pending Tasks

  • Complete the integration of NLP for keyword extraction and classification.
  • Finalize the automation of news article triage.
  • Conduct further testing to ensure the robustness of the entire pipeline.

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