dataforgoodfr/13_potentiel_solaire
Jan 2025 – Oct 2025
10 Months active
Languages Used
MarkdownPythonYAMLBashJSONJupyter NotebookShellGit
Technical Skills
CI/CDCI/CD ConfigurationCollaborationDependency ManagementDevOpsDocumentation
machbry
PROFILE
Machbry
Matthieu Chambery led the engineering of dataforgoodfr/13_potentiel_solaire, building a modular, scalable backend for solar potential analysis across French educational buildings. He architected robust data pipelines and geospatial workflows using Python, SQL, and Docker, integrating sources like PVGIS and GeoJSON to deliver reproducible analytics and interactive visualizations. Matthieu implemented database migrations, asynchronous API calls, and CLI tooling to streamline deployment and data processing, while enhancing data quality through validation, deduplication, and schema evolution. His work improved onboarding, reliability, and cross-platform portability, enabling accurate, stakeholder-facing solar assessments and supporting maintainable, production-ready analytics infrastructure for ongoing collaborative development.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
208Total
Bugs
34
Commits
208
Features
79
Lines of code
121,911
Activity Months10
Your Network
18 peopleWork History
October 2025
4 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for dataforgoodfr/13_potentiel_solaire. Delivered a robust Admin Directory Data Source and improved data accessibility, while fixing critical data quality issues in the admin directory. The work enhances governance contact data reliability, reduces manual remediation, and improves downstream processes that depend on admin contact information. Key infrastructure and deployment improvements were completed to ensure data integrity across environments.
4 Commits • 1 Features
Oct 1, 2025October 2025 monthly summary for dataforgoodfr/13_potentiel_solaire. Delivered a robust Admin Directory Data Source and improved data accessibility, while fixing critical data quality issues in the admin directory. The work enhances governance contact data reliability, reduces manual remediation, and improves downstream processes that depend on admin contact information. Key infrastructure and deployment improvements were completed to ensure data integrity across environments.
October 2025
September 2025
14 Commits • 4 Features
Sep 1, 2025September 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered robust data initialization, interactive visualization, accuracy improvements for solar potential calculations, data quality updates for educational addresses, and release/readiness maintenance. These efforts enhanced reliability, data quality, and stakeholder-facing analytics while strengthening production readiness.
September 2025
14 Commits • 4 Features
Sep 1, 2025September 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered robust data initialization, interactive visualization, accuracy improvements for solar potential calculations, data quality updates for educational addresses, and release/readiness maintenance. These efforts enhanced reliability, data quality, and stakeholder-facing analytics while strengthening production readiness.
August 2025
11 Commits • 2 Features
Aug 1, 2025August 2025 for dataforgoodfr/13_potentiel_solaire: Delivered configurable PVGIS-based solar potential analysis, enhanced roof segmentation visuals, and strengthened data flow reliability. Implemented orientation/slope configurability, asynchronous PVGIS calls, standardized parameter naming, and enriched notebooks for cross-algorithm comparisons and exportable results. A reliability fix was implemented for the ADMINEXPRESS-COG data flow, and zone-level indicators were corrected for accurate reporting. These changes enable faster, more accurate solar potential assessments for prioritized rooftops and more stakeholder-facing outputs.
11 Commits • 2 Features
Aug 1, 2025August 2025 for dataforgoodfr/13_potentiel_solaire: Delivered configurable PVGIS-based solar potential analysis, enhanced roof segmentation visuals, and strengthened data flow reliability. Implemented orientation/slope configurability, asynchronous PVGIS calls, standardized parameter naming, and enriched notebooks for cross-algorithm comparisons and exportable results. A reliability fix was implemented for the ADMINEXPRESS-COG data flow, and zone-level indicators were corrected for accurate reporting. These changes enable faster, more accurate solar potential assessments for prioritized rooftops and more stakeholder-facing outputs.
August 2025
July 2025
36 Commits • 21 Features
Jul 1, 2025July 2025: Delivered modular, scalable data processing workflows for solar potential assessments with city-wide scope, improved data integrity and observability, and enabling department-level analysis. The work strengthened code modularity, pipeline reliability, and performance, delivering clear business value for multi-city evaluation and reporting.
July 2025
36 Commits • 21 Features
Jul 1, 2025July 2025: Delivered modular, scalable data processing workflows for solar potential assessments with city-wide scope, improved data integrity and observability, and enabling department-level analysis. The work strengthened code modularity, pipeline reliability, and performance, delivering clear business value for multi-city evaluation and reporting.
June 2025
10 Commits • 5 Features
Jun 1, 2025June 2025 monthly summary for dataforgoodfr/13_potentiel_solaire highlighting key features delivered, major fixes, and impact on business value through improved data quality, targeting, and analytics capabilities.
10 Commits • 5 Features
Jun 1, 2025June 2025 monthly summary for dataforgoodfr/13_potentiel_solaire highlighting key features delivered, major fixes, and impact on business value through improved data quality, targeting, and analytics capabilities.
June 2025
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered Dockerized Database Initialization improvements and associated documentation to boost deployment portability and reliability. Consolidated Docker-related setup, ensured sources.yaml is included in the Docker image and moved out of the data folder; prevented automatic creation of the results directory during Dockerized DB initialization; added process documentation and updated README to reflect portable, relative Docker volume mount paths for cross-environment usage. These changes reduce setup errors, improve developer onboarding, and enhance consistency across local, CI, and cloud environments.
May 2025
2 Commits • 1 Features
May 1, 2025May 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered Dockerized Database Initialization improvements and associated documentation to boost deployment portability and reliability. Consolidated Docker-related setup, ensured sources.yaml is included in the Docker image and moved out of the data folder; prevented automatic creation of the results directory during Dockerized DB initialization; added process documentation and updated README to reflect portable, relative Docker volume mount paths for cross-environment usage. These changes reduce setup errors, improve developer onboarding, and enhance consistency across local, CI, and cloud environments.
April 2025
35 Commits • 14 Features
Apr 1, 2025April 2025 monthly highlights for dataforgoodfr/13_potentiel_solaire: delivered key data-model and analytics improvements, strengthened CI/CD practices, and enhanced infrastructure to increase data accuracy, deployment reliability, and operational velocity. Key outcomes include database schema cleanup for etablissements, a new search view and join tables to optimize geographic lookups, analytics enhancements with per-area indicator totals, and a more robust deployment stack featuring a DuckDB-based Docker image, cleaner notebooks, improved logging, and a refactored PVGIS retry workflow. These changes drive higher-quality solar potential assessments, faster data access for stakeholders, and smoother deployments across environments.
35 Commits • 14 Features
Apr 1, 2025April 2025 monthly highlights for dataforgoodfr/13_potentiel_solaire: delivered key data-model and analytics improvements, strengthened CI/CD practices, and enhanced infrastructure to increase data accuracy, deployment reliability, and operational velocity. Key outcomes include database schema cleanup for etablissements, a new search view and join tables to optimize geographic lookups, analytics enhancements with per-area indicator totals, and a more robust deployment stack featuring a DuckDB-based Docker image, cleaner notebooks, improved logging, and a refactored PVGIS retry workflow. These changes drive higher-quality solar potential assessments, faster data access for stakeholders, and smoother deployments across environments.
April 2025
March 2025
49 Commits • 19 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered core data ingestion and geospatial improvements enabling reliable, scalable solar potential analyses at department and national levels. Key features include data loading and CRS harmonization for protected buildings (separate download/read steps; standardized CRS usage for buffers), PVGIS integration enhancements (units conversion to kWh/year; robust parameter handling; reduced API calls by centering on department), DuckDB core data integration with Alembic migrations and export to GPKG, regional/national calculation capability, and WFS-based arrondissement retrieval. Major bugs fixed include an alert for non EPSG:2154 CRS during WMS flux retrieval, PVGIS API cleanup, and data integrity improvements (deduplication of school directory; geometry corrections; Alembic-related fixes). The work delivers tangible business value through more reliable, scalable, and faster solar potential analyses, reduced latency and API overhead, and stronger data governance. Technologies/skills demonstrated include Python data processing (Pandas/GeoPandas), DuckDB with Alembic migrations, GIS CRS management (EPSG:2154), PVGIS/WFS/WMS integration, GPKG export, notebook-driven data exploration, and CI/CD hygiene.
March 2025
49 Commits • 19 Features
Mar 1, 2025March 2025 monthly summary for dataforgoodfr/13_potentiel_solaire: Delivered core data ingestion and geospatial improvements enabling reliable, scalable solar potential analyses at department and national levels. Key features include data loading and CRS harmonization for protected buildings (separate download/read steps; standardized CRS usage for buffers), PVGIS integration enhancements (units conversion to kWh/year; robust parameter handling; reduced API calls by centering on department), DuckDB core data integration with Alembic migrations and export to GPKG, regional/national calculation capability, and WFS-based arrondissement retrieval. Major bugs fixed include an alert for non EPSG:2154 CRS during WMS flux retrieval, PVGIS API cleanup, and data integrity improvements (deduplication of school directory; geometry corrections; Alembic-related fixes). The work delivers tangible business value through more reliable, scalable, and faster solar potential analyses, reduced latency and API overhead, and stronger data governance. Technologies/skills demonstrated include Python data processing (Pandas/GeoPandas), DuckDB with Alembic migrations, GIS CRS management (EPSG:2154), PVGIS/WFS/WMS integration, GPKG export, notebook-driven data exploration, and CI/CD hygiene.
February 2025
30 Commits • 9 Features
Feb 1, 2025February 2025 monthly summary for dataforgoodfr/13_potentiel_solaire. Delivered a cross-platform data access foundation, notebook-driven pipeline integration with environment tooling, improved observability and maintainability, and strengthened data accuracy. These efforts reduce onboarding time, increase pipeline reliability, and enable reproducible analyses for solar potential modelling.
30 Commits • 9 Features
Feb 1, 2025February 2025 monthly summary for dataforgoodfr/13_potentiel_solaire. Delivered a cross-platform data access foundation, notebook-driven pipeline integration with environment tooling, improved observability and maintainability, and strengthened data accuracy. These efforts reduce onboarding time, increase pipeline reliability, and enable reproducible analyses for solar potential modelling.
February 2025
January 2025
17 Commits • 3 Features
Jan 1, 2025January 2025 — Focused on establishing a solid foundation for dataforgoodfr/13_potentiel_solaire to enable scalable development and reliable collaboration. Delivered foundational repository improvements, governance, and tooling to improve maintainability and accelerate delivery: - Core restructuring into a two-part architecture (algo + app) with scaffolding for data, notebooks, tests, and initial docs. - Documentation and contribution workflow enhancements (PR templates, onboarding guidelines, README alignment with external templates). - CI/CD stabilization and pre-commit workflow improvements (Poetry integration, GitHub Actions setup, environment hardening, caching adjustments, and targeted fixes to pre-commit). Major bug fixes related to tooling and environment, including pre-commit reliability, working-directory handling, isolation to the algorithm subfolder, and vulnerability fixes in the CI environment. Overall impact: improved maintainability, faster onboarding, more reliable automated testing and deployment, and clearer governance for contributions. Demonstrated skills in Python project structure, packaging with Poetry, CI/CD (GitHub Actions), pre-commit tooling, and comprehensive documentation.
January 2025
17 Commits • 3 Features
Jan 1, 2025January 2025 — Focused on establishing a solid foundation for dataforgoodfr/13_potentiel_solaire to enable scalable development and reliable collaboration. Delivered foundational repository improvements, governance, and tooling to improve maintainability and accelerate delivery: - Core restructuring into a two-part architecture (algo + app) with scaffolding for data, notebooks, tests, and initial docs. - Documentation and contribution workflow enhancements (PR templates, onboarding guidelines, README alignment with external templates). - CI/CD stabilization and pre-commit workflow improvements (Poetry integration, GitHub Actions setup, environment hardening, caching adjustments, and targeted fixes to pre-commit). Major bug fixes related to tooling and environment, including pre-commit reliability, working-directory handling, isolation to the algorithm subfolder, and vulnerability fixes in the CI environment. Overall impact: improved maintainability, faster onboarding, more reliable automated testing and deployment, and clearer governance for contributions. Demonstrated skills in Python project structure, packaging with Poetry, CI/CD (GitHub Actions), pre-commit tooling, and comprehensive documentation.
Activity
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Quality Metrics
Correctness88.0%
Maintainability88.4%
Architecture86.0%
Performance80.2%
AI Usage20.4%
Skills & Technologies
Programming Languages
BashCSVDockerfileGitGit IgnoreJSONJupyter NotebookMarkdownPythonSQL
Technical Skills
API IntegrationAPI integrationAlembicAlgorithm DevelopmentAsynchronous ProgrammingBackend DevelopmentBest PracticesBug FixingCI/CDCI/CD ConfigurationCLI DevelopmentCLI developmentCode CleanupCode OrganizationCode Quality
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