dataforgoodfr/13_potentiel_solaire
Mar 2025 – Mar 2025
1 Month active
Languages Used
JSONJupyter NotebookPython
Technical Skills
API IntegrationBackend DevelopmentCode OrganizationData AnalysisData EngineeringData Pipeline Development
AmaurySalles
PROFILE
Amaurysalles
Amaury Salles developed new solar potential estimation workflows for the dataforgoodfr/13_potentiel_solaire repository, focusing on building-level and school-focused energy planning. He integrated the PVGIS API using Python and Pandas, implementing rate limiting and robust API URL construction to ensure reliable data retrieval. His work included refactoring legacy Jupyter Notebooks, decoupling the PVGIS integration from existing pipelines, and enforcing code quality through pre-commit checks. By aggregating geospatial data with GeoPandas and persisting results at multiple administrative levels, Amaury enabled reproducible, maintainable pipelines that support targeted solar energy planning for public facilities. The work demonstrated strong backend and data engineering skills.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
6Total
Bugs
0
Commits
6
Features
2
Lines of code
2,741
Activity Months1
Your Network
18 peopleWork History
March 2025
6 Commits • 2 Features
Mar 1, 2025March 2025 — Dataforgoodfr/13_potentiel_solaire: Delivered PVGIS-based solar potential workflows enabling building-level estimations and targeted energy planning, along with a school-focused pipeline to aggregate and persist results. Major bugs fixed included cleanup of legacy PVGIS notebooks, decoupling the integration from the MSN pipeline, and enforcing CI hygiene through pre-commit checks. Overall impact: new capabilities for energy planning across public facilities with improved maintainability and reproducibility. Technologies demonstrated: API integration, data preparation, rate limiting, multi-level data aggregation, persistent storage, refactoring, and CI practices.
6 Commits • 2 Features
Mar 1, 2025March 2025 — Dataforgoodfr/13_potentiel_solaire: Delivered PVGIS-based solar potential workflows enabling building-level estimations and targeted energy planning, along with a school-focused pipeline to aggregate and persist results. Major bugs fixed included cleanup of legacy PVGIS notebooks, decoupling the integration from the MSN pipeline, and enforcing CI hygiene through pre-commit checks. Overall impact: new capabilities for energy planning across public facilities with improved maintainability and reproducibility. Technologies demonstrated: API integration, data preparation, rate limiting, multi-level data aggregation, persistent storage, refactoring, and CI practices.
March 2025
Activity
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Quality Metrics
Correctness83.4%
Maintainability83.4%
Architecture80.0%
Performance73.4%
AI Usage20.0%
Skills & Technologies
Programming Languages
JSONJupyter NotebookPython
Technical Skills
API IntegrationBackend DevelopmentCode OrganizationData AnalysisData EngineeringData Pipeline DevelopmentData ProcessingGeoPandasGeospatial AnalysisJupyter NotebooksPandasPythonRefactoringSolar Energy Calculations
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