Enhanced Google Maps Scraper and API Integration

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Enhanced Google Maps Scraper and API Integration

  • Day: 2025-10-05
  • Time: 21:15 to 22:45
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Google Maps, Api Integration, Python, Debugging, Data Normalization

Description

Session Goal

The session focused on advancing the Google Maps scraper project and integrating the Google Places API for robust data acquisition and processing.

Key Activities

  • Debugging and Engineering Practices: Transitioned from confusion to systematic engineering practices in the Google Maps scraper project, focusing on problem discovery and root-cause analysis.
  • API Pipeline Development: Made significant progress in developing a Places API pipeline, improving data normalization and addressing pagination and QA challenges.
  • Code Review and Improvements: Conducted a detailed review of text_runner.py, identifying high-impact issues and proposing fixes for better functionality and maintainability.
  • Function Enhancement: Enhanced the flatten_place function to normalize and expand Google Places API data.
  • Modular Package Design: Proposed a modular structure for the gmaps_scraper package, emphasizing separation of concerns.
  • Integration and Execution: Provided instructions for running the Gmaps Scraper with the Google Places API, including error handling and API field mask corrections.
  • Version Control and Documentation: Outlined git commit sequences, resolved git issues, ensured API key safety, and edited the README for clarity and modular design.

Achievements

  • Developed a robust pipeline for Google Places API data acquisition.
  • Improved the modular design and maintainability of the gmaps_scraper package.
  • Enhanced documentation and version control practices.

Pending Tasks

  • Further testing of the enhanced flatten_place function.
  • Additional QA and validation of the Places API pipeline.
  • Continued refinement of the modular package design for scalability.

Evidence

  • source_file=2025-10-05.sessions.jsonl, line_number=1, event_count=0, session_id=d94f4885de46363d89800664b46dbb6183e7f679af8b765fd9067b6ba6b40718
  • event_ids: []

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