
Over a two-month period, contributed to the alltheplaces/alltheplaces repository by developing and enhancing web scraping spiders for grocery and restaurant location data. Built robust Scrapy spiders in Python, leveraging regular expressions for address and hours normalization, and ensured consistent extraction of store details such as names, coordinates, and operating hours. Introduced a shared base class to consolidate scraping logic, reducing code duplication and streamlining onboarding for new brands. The modular, config-driven approach enabled scalable data extraction across multiple supermarket chains, improving maintainability and supporting downstream analytics. No major bugs were reported, and existing pipelines remained stable throughout the work.
Month: May 2025 | Repository: alltheplaces/alltheplaces. Key deliverable: a scalable set of grocery store brand web scraping spiders built on a shared base class, consolidating common scraping logic and improving maintainability. Implemented brand-specific spiders for Associated Supermarket Group brands (Associated Supermarket, Compare Foods, Met Foodmarket, Pioneer Supermarket) configured with brand names and URLs to extract store location data, enabling broader data collection and actionable business insights. Impact: expanded data coverage across multiple brands, faster onboarding of new brands, reduced code duplication, and easier ongoing maintenance. Demonstrated Python OOP, modular scraper design, and config-driven architecture. Related commit: 44f36723589c9145f2df08885fc81165314a1b5c (Add spiders for Associated Supermarket Group brands) as part of (#13075).
Month: May 2025 | Repository: alltheplaces/alltheplaces. Key deliverable: a scalable set of grocery store brand web scraping spiders built on a shared base class, consolidating common scraping logic and improving maintainability. Implemented brand-specific spiders for Associated Supermarket Group brands (Associated Supermarket, Compare Foods, Met Foodmarket, Pioneer Supermarket) configured with brand names and URLs to extract store location data, enabling broader data collection and actionable business insights. Impact: expanded data coverage across multiple brands, faster onboarding of new brands, reduced code duplication, and easier ongoing maintenance. Demonstrated Python OOP, modular scraper design, and config-driven architecture. Related commit: 44f36723589c9145f2df08885fc81165314a1b5c (Add spiders for Associated Supermarket Group brands) as part of (#13075).
March 2025 monthly summary: Delivered two new location data spiders for alltheplaces/alltheplaces, expanding coverage to El Super US (68 locations) and Xi'an Famous Foods (16 locations). Implemented robust address, hours, and coordinate parsing with normalization to ensure consistent data across sites. Achieved end-to-end data extraction from sitemaps and individual pages with traceable commits for governance. No major bugs reported; existing pipelines remained stable, improving data completeness and enabling faster downstream usage for search, analytics, and partner integrations.
March 2025 monthly summary: Delivered two new location data spiders for alltheplaces/alltheplaces, expanding coverage to El Super US (68 locations) and Xi'an Famous Foods (16 locations). Implemented robust address, hours, and coordinate parsing with normalization to ensure consistent data across sites. Achieved end-to-end data extraction from sitemaps and individual pages with traceable commits for governance. No major bugs reported; existing pipelines remained stable, improving data completeness and enabling faster downstream usage for search, analytics, and partner integrations.

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