dataforgoodfr/13_pollution_eau
Mar 2025 – Apr 2025
2 Months active
Languages Used
CSSTypeScriptPython
Technical Skills
API DevelopmentBackend DevelopmentData ModelingMock Data ImplementationData EngineeringDatabase Management
Thibaut
PROFILE
Thibaut
Thibaut Duguet developed and enhanced core backend features for the dataforgoodfr/13_pollution_eau repository over a two-month period, focusing on robust API endpoints and data reliability. He implemented a UDI Mock Data API using Python and TypeScript, enabling consistent, testable responses for both present and missing UDI IDs, which improved local development and CI stability. Thibaut also standardized pollution category data, refined data pipelines, and introduced configuration management to streamline data handling. By extending the website’s data preparation and delivering mock data endpoints, he accelerated frontend development with React and ensured more reliable, consistent data models for integration and testing.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
4Total
Bugs
0
Commits
4
Features
3
Lines of code
1,170
Activity Months2
Your Network
12 peopleShared Repositories
12
Work History
April 2025
3 Commits • 2 Features
Apr 1, 2025April 2025: Implemented two core features for dataforgoodfr/13_pollution_eau that improve data reliability and frontend velocity. 1) Pollution Data Handling and Website Preparation: added a configuration file, standardized pollution category naming, refined data handling in components, and extended the website data pipeline to trim int__lien_commune_cdreseau for the UDI endpoint, increasing data availability. Commits cc27f0abe1f103ed782acdd51c6729ce7cf7c212 and 13b22685494094688cecd5ff891eee790210aefd. 2) Development API Endpoint for Mock Data: introduced a GET endpoint delivering mock data to accelerate frontend development. Commit 9c1f0a1f98bea4cb189768a187190b3296ca3006. Overall impact: more consistent data models, faster frontend iterations, and improved data availability on the website, reducing integration risk. Technologies/skills: backend configuration management, data pipeline enhancements, API design, mock data strategy, and Git-based traceability.
3 Commits • 2 Features
Apr 1, 2025April 2025: Implemented two core features for dataforgoodfr/13_pollution_eau that improve data reliability and frontend velocity. 1) Pollution Data Handling and Website Preparation: added a configuration file, standardized pollution category naming, refined data handling in components, and extended the website data pipeline to trim int__lien_commune_cdreseau for the UDI endpoint, increasing data availability. Commits cc27f0abe1f103ed782acdd51c6729ce7cf7c212 and 13b22685494094688cecd5ff891eee790210aefd. 2) Development API Endpoint for Mock Data: introduced a GET endpoint delivering mock data to accelerate frontend development. Commit 9c1f0a1f98bea4cb189768a187190b3296ca3006. Overall impact: more consistent data models, faster frontend iterations, and improved data availability on the website, reducing integration risk. Technologies/skills: backend configuration management, data pipeline enhancements, API design, mock data strategy, and Git-based traceability.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_pollution_eau: Implemented a UDI Mock Data API Endpoint to enable reliable, testable UDI data without external dependencies. The endpoint handles requests with and without a UDI ID, returning specific mock data or clear error messages for missing or not found IDs. Mock data includes detailed pollution analysis across categories and sub-categories. Commit reference: e3727fa15025e4b5d5ccfcd2aa70cb11b22ce454.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_pollution_eau: Implemented a UDI Mock Data API Endpoint to enable reliable, testable UDI data without external dependencies. The endpoint handles requests with and without a UDI ID, returning specific mock data or clear error messages for missing or not found IDs. Mock data includes detailed pollution analysis across categories and sub-categories. Commit reference: e3727fa15025e4b5d5ccfcd2aa70cb11b22ce454.
Activity
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Quality Metrics
Correctness90.0%
Maintainability90.0%
Architecture90.0%
Performance90.0%
AI Usage25.0%
Skills & Technologies
Programming Languages
CSSPythonTypeScript
Technical Skills
API DevelopmentBackend DevelopmentData EngineeringData ModelingDatabase ManagementMock Data ImplementationReactfront end development
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