EXCEEDS logo
Exceeds
David Riordan

PROFILE

David Riordan

Dave Riordan developed and delivered a suite of web scraping spiders for the alltheplaces/alltheplaces repository, focusing on extracting structured location data for grocery and restaurant brands. He implemented robust data extraction pipelines using Python, Scrapy, and regular expressions, normalizing addresses and hours to ensure consistency across datasets. In March, he built spiders for El Super US and Xi’an Famous Foods, handling end-to-end data parsing from sitemaps and individual pages. By May, he introduced a scalable, shared base class for Associated Supermarket Group brands, reducing code duplication and streamlining onboarding of new brands, which improved maintainability and expanded data coverage.

Overall Statistics

Feature vs Bugs

100%Features

Repository Contributions

3Total
Bugs
0
Commits
3
Features
3
Lines of code
662
Activity Months2

Work History

May 2025

1 Commits • 1 Features

May 1, 2025

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

2 Commits • 2 Features

Mar 1, 2025

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.

Activity

Loading activity data...

Quality Metrics

Correctness96.6%
Maintainability93.4%
Architecture93.4%
Performance86.6%
AI Usage20.0%

Skills & Technologies

Programming Languages

Python

Technical Skills

Data ExtractionPythonRegular ExpressionsScrapyWeb Scraping

Repositories Contributed To

1 repo

Overview of all repositories you've contributed to across your timeline

alltheplaces/alltheplaces

Mar 2025 May 2025
2 Months active

Languages Used

Python

Technical Skills

Data ExtractionPythonRegular ExpressionsScrapyWeb Scraping

Generated by Exceeds AIThis report is designed for sharing and indexing