Enhanced Article Scraping Process

📅 2025-06-12 — Session: Enhanced Article Scraping Process

🕒 05:10–05:40
🏷️ Labels: Scraping, Automation, Python, Data Processing, Content Strategy
📂 Project: Media
⭐ Priority: MEDIUM

The session aimed to refine and enhance the article scraping logic and process to improve efficiency and accuracy.

Refinement Proposal for Article Scraping Logic: Reviewed and proposed enhancements for the article scraping process using a post-PromptFlow dataset, including changes in logic and an updated scraper script.
Script Extension for Data Enrichment: Proposed an extension for the explode_pf_outputs.py script to merge data from master_ref.csv and scraped_links.jsonl, creating an enriched CSV file articles_to_scrape.csv.
Adaptation of Article Scraper: Adapted a script for scraping articles from a JSONL file, using ‘index_id’ as the primary key and avoiding recalculation of ‘uid’.
Modification for Complete Processing: Modified the main() method and CLI to process the entire file without date or time filters, using index_id to prevent duplicates.
Reinforcement of index_id Use: Finalized the script to use index_id as the sole identifier, ensuring idempotency and consistency.
Review of Scraping Pipeline: Conducted a review of the scraping pipeline, highlighting its current state and suggesting improvements for robustness and modularity.
News Intelligence System Status: Detailed the progress and components for developing a semi-autonomous content generation and curation system.
Content Generation Strategy: Described a workflow for transforming seed ideas into strategic content and drafts using an automated system.

Enhanced the article scraping process with improved logic and enriched data handling.
Established a robust system using index_id for consistent and idempotent scraping.
Reviewed and suggested improvements for the scraping pipeline.