MTES-MCT/ecobalyse
Nov 2024 – Jun 2026
14 Months active
Languages Used
ElmJavaScriptPythonShellTypeScriptYAMLJSON
Technical Skills
Backend DevelopmentData AnalysisData EngineeringData IntegrationData ModelingDatabase Management
Christophe Combelles
PROFILE
Christophe Combelles
Worked extensively on the MTES-MCT/ecobalyse repository, delivering robust features and data quality improvements for environmental impact analysis. Focused on backend development and data engineering, they integrated new datasets, refined calculation logic, and stabilized data pipelines using TypeScript, Python, and JSON. Their work included enhancing ingredient and material modeling, optimizing deployment processes, and improving API documentation for clarity and traceability. They addressed data integrity through rigorous validation, synchronized cross-repository updates, and implemented deterministic end-to-end testing with Playwright. These efforts collectively improved analytical accuracy, deployment reliability, and data governance, supporting more reliable sustainability assessments and streamlined collaboration across teams.
Overall Statistics
Feature vs Bugs
57%Features
Repository Contributions
47Total
Bugs
16
Commits
47
Features
21
Lines of code
2,363,865
Activity Months14
Your Network
10 peopleWork History
June 2026
3 Commits • 1 Features
Jun 1, 2026June 2026 — MTES-MCT/ecobalyse: Delivered data-model enhancements for down jacket components and stabilized CI with deterministic e2e testing. Added nonwoven polyester to lci_catalog and object sector, enabling accurate material representation across processes; improved end-to-end test reliability by removing retries and introducing a dedicated email-handling function. These changes reduce data gaps and shorten feedback cycles for material modeling workflows.
3 Commits • 1 Features
Jun 1, 2026June 2026 — MTES-MCT/ecobalyse: Delivered data-model enhancements for down jacket components and stabilized CI with deterministic e2e testing. Added nonwoven polyester to lci_catalog and object sector, enabling accurate material representation across processes; improved end-to-end test reliability by removing retries and introducing a dedicated email-handling function. These changes reduce data gaps and shorten feedback cycles for material modeling workflows.
June 2026
May 2026
1 Commits • 1 Features
May 1, 2026Summary for 2026-05: Delivered HUE Ingredients Dataset Expansion for Ecological Assessments in MTES-MCT/ecobalyse, adding new crops and attributes to enhance ecological analyses and reporting. This work enables richer downstream analyses via the new export linked to ecobalyse-data PR 287. No major bugs fixed this month for this repository. Overall impact includes improved data completeness, higher fidelity ecological models, and better decision support for ecological assessments. Skills demonstrated include data engineering, Git/version control, PR-driven collaboration, and cross-repo data integration.
May 2026
1 Commits • 1 Features
May 1, 2026Summary for 2026-05: Delivered HUE Ingredients Dataset Expansion for Ecological Assessments in MTES-MCT/ecobalyse, adding new crops and attributes to enhance ecological analyses and reporting. This work enables richer downstream analyses via the new export linked to ecobalyse-data PR 287. No major bugs fixed this month for this repository. Overall impact includes improved data completeness, higher fidelity ecological models, and better decision support for ecological assessments. Skills demonstrated include data engineering, Git/version control, PR-driven collaboration, and cross-repo data integration.
April 2026
4 Commits • 2 Features
Apr 1, 2026April 2026 summary for MTES-MCT/ecobalyse focused on reliability improvements and data enrichment to boost deployment velocity and ecological analysis capabilities. Delivered a Deployment Process Optimization that cuts post-deploy DB loading from ~2 hours to seconds, stabilizing releases as process counts scale. Expanded ecological data coverage by adding organic cotton with irrigation data, updating ingredients (including UE options), and introducing new raw ingredients for fruits and vegetables, enabling more robust sustainability analyses. These efforts combined to improve deployment reliability, data quality, and analytical insight, with cross-team collaboration and a stronger data governance posture.
4 Commits • 2 Features
Apr 1, 2026April 2026 summary for MTES-MCT/ecobalyse focused on reliability improvements and data enrichment to boost deployment velocity and ecological analysis capabilities. Delivered a Deployment Process Optimization that cuts post-deploy DB loading from ~2 hours to seconds, stabilizing releases as process counts scale. Expanded ecological data coverage by adding organic cotton with irrigation data, updating ingredients (including UE options), and introducing new raw ingredients for fruits and vegetables, enabling more robust sustainability analyses. These efforts combined to improve deployment reliability, data quality, and analytical insight, with cross-team collaboration and a stronger data governance posture.
April 2026
March 2026
3 Commits • 1 Features
Mar 1, 2026March 2026 – MTES-MCT/ecobalyse: Delivered targeted data quality improvements for France ingredients and expanded the ingredient dataset to support compliance labeling and analytics. Implemented FR data enhancements (density, inedible parts, crop group classifications) and added new ingredients including Origine Inconnue and organic items. Data fixes and exports were integrated via PRs to ecobalyse-data, enabling downstream consumption and traceability (PRs 234, 215, 235). These changes improve accuracy of nutrition models, labeling accuracy, and onboarding speed for new ingredients.
March 2026
3 Commits • 1 Features
Mar 1, 2026March 2026 – MTES-MCT/ecobalyse: Delivered targeted data quality improvements for France ingredients and expanded the ingredient dataset to support compliance labeling and analytics. Implemented FR data enhancements (density, inedible parts, crop group classifications) and added new ingredients including Origine Inconnue and organic items. Data fixes and exports were integrated via PRs to ecobalyse-data, enabling downstream consumption and traceability (PRs 234, 215, 235). These changes improve accuracy of nutrition models, labeling accuracy, and onboarding speed for new ingredients.
February 2026
1 Commits • 1 Features
Feb 1, 2026Month: 2026-02 — Delivered data enrichment feature in MTES-MCT/ecobalyse and reinforced data quality for downstream analytics. Notable new ingredients dataset enrichment with updated 2025 attributes; no major bugs fixed this month. Overall impact includes richer ingredient data enabling improved modeling accuracy and scenario analyses, enhanced data governance, and stronger release discipline. Demonstrated strong data engineering, version control, and cross-repo collaboration.
1 Commits • 1 Features
Feb 1, 2026Month: 2026-02 — Delivered data enrichment feature in MTES-MCT/ecobalyse and reinforced data quality for downstream analytics. Notable new ingredients dataset enrichment with updated 2025 attributes; no major bugs fixed this month. Overall impact includes richer ingredient data enabling improved modeling accuracy and scenario analyses, enhanced data governance, and stronger release discipline. Demonstrated strong data engineering, version control, and cross-repo collaboration.
February 2026
September 2025
4 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for MTES-MCT/ecobalyse. Focused on stabilizing data handling, improving API clarity, and strengthening validation to reduce operational risk. Key deliverables include bug fixes and an API enhancement that improve reliability and developer experience. - Key features delivered: Expose server FQDN and version in versioned API URLs to improve clarity and usability. - Major bugs fixed: Cocoa Butter Issue Fix; Ingredient ID Test Data Synchronization; Enforce Positive Mass Validation. - Overall impact and accomplishments: Strengthened data integrity, reduced risk from invalid mass entries, improved API observability, and ensured test data reflects current data model across ecosystems. - Technologies/skills demonstrated: Cross-stack debugging (Elm/Node.js test suites), validation hardening, API design and observability, commit-driven delivery.
September 2025
4 Commits • 1 Features
Sep 1, 2025September 2025 monthly summary for MTES-MCT/ecobalyse. Focused on stabilizing data handling, improving API clarity, and strengthening validation to reduce operational risk. Key deliverables include bug fixes and an API enhancement that improve reliability and developer experience. - Key features delivered: Expose server FQDN and version in versioned API URLs to improve clarity and usability. - Major bugs fixed: Cocoa Butter Issue Fix; Ingredient ID Test Data Synchronization; Enforce Positive Mass Validation. - Overall impact and accomplishments: Strengthened data integrity, reduced risk from invalid mass entries, improved API observability, and ensured test data reflects current data model across ecosystems. - Technologies/skills demonstrated: Cross-stack debugging (Elm/Node.js test suites), validation hardening, API design and observability, commit-driven delivery.
August 2025
5 Commits • 1 Features
Aug 1, 2025August 2025 — MTES-MCT/ecobalyse: Delivered critical data and quality improvements to strengthen environmental impact calculations. Implemented Agribalyse 3.2 integration with dataset-aligned entries, enhancing data accuracy and coverage for environmental impact assessments; refined impact calculations and tests to better reflect real-world results; fixed data reliability gaps in food identifiers and densities; ensured ingredient IDs remain stable across releases to support smooth version transitions. These efforts reduce data drift, improve decision support for sustainability assessments, and demonstrate strong data engineering and QA discipline.
5 Commits • 1 Features
Aug 1, 2025August 2025 — MTES-MCT/ecobalyse: Delivered critical data and quality improvements to strengthen environmental impact calculations. Implemented Agribalyse 3.2 integration with dataset-aligned entries, enhancing data accuracy and coverage for environmental impact assessments; refined impact calculations and tests to better reflect real-world results; fixed data reliability gaps in food identifiers and densities; ensured ingredient IDs remain stable across releases to support smooth version transitions. These efforts reduce data drift, improve decision support for sustainability assessments, and demonstrate strong data engineering and QA discipline.
August 2025
July 2025
5 Commits • 3 Features
Jul 1, 2025July 2025 monthly summary for MTES-MCT/ecobalyse focusing on delivering dataset updates, API documentation clarity, and stability improvements. Highlights include bug fix for DisplayName duplicates, dataset expansion with pasta and soups, persistent IDs across material/ingredient in API docs, restoration of oilseed-feed export path, and refactoring of cooking process detection to treat invalid/missing as compile errors, improving CI and test reliability.
July 2025
5 Commits • 3 Features
Jul 1, 2025July 2025 monthly summary for MTES-MCT/ecobalyse focusing on delivering dataset updates, API documentation clarity, and stability improvements. Highlights include bug fix for DisplayName duplicates, dataset expansion with pasta and soups, persistent IDs across material/ingredient in API docs, restoration of oilseed-feed export path, and refactoring of cooking process detection to treat invalid/missing as compile errors, improving CI and test reliability.
June 2025
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for MTES-MCT/ecobalyse: Focused on stabilizing core calculations and data integrity. Delivered a feature to improve lentil-related calculations by integrating new external data exports, and fixed key calculation path issues to prevent negative Land Use Density values. Updated and aligned tests to reflect revised calculation logic, ensuring regression resilience across the production data pipeline. These changes collectively enhance analytical accuracy, reliability, and trust in downstream analytics for lentil and land-use metrics.
3 Commits • 1 Features
Jun 1, 2025June 2025 monthly summary for MTES-MCT/ecobalyse: Focused on stabilizing core calculations and data integrity. Delivered a feature to improve lentil-related calculations by integrating new external data exports, and fixed key calculation path issues to prevent negative Land Use Density values. Updated and aligned tests to reflect revised calculation logic, ensuring regression resilience across the production data pipeline. These changes collectively enhance analytical accuracy, reliability, and trust in downstream analytics for lentil and land-use metrics.
June 2025
April 2025
3 Commits
Apr 1, 2025April 2025 — MTES-MCT/ecobalyse: Bug fix and test-validation alignment following impact calculation updates and migration to Brightway. Key changes included aligning test assertions across modules to reflect updated impact calculations, suppressing long-term impacts from the new ecobalyse-data export, and lowering Uranium FRU in the ECS impacts due to updated input data. Implemented via commits: chore: Impacts from brightway switch (#993); chore: Supress long-term impacts (new export from ecobalyse-data#63) (#1010); chore: Lower Uranium FRU (new export from ecobalyse-data#71) (#1018). Business value: stabilized test suite against evolving data/dependencies, reduced regression risk, and ensured reliable, data-driven impact assessments for stakeholders.
April 2025
3 Commits
Apr 1, 2025April 2025 — MTES-MCT/ecobalyse: Bug fix and test-validation alignment following impact calculation updates and migration to Brightway. Key changes included aligning test assertions across modules to reflect updated impact calculations, suppressing long-term impacts from the new ecobalyse-data export, and lowering Uranium FRU in the ECS impacts due to updated input data. Implemented via commits: chore: Impacts from brightway switch (#993); chore: Supress long-term impacts (new export from ecobalyse-data#63) (#1010); chore: Lower Uranium FRU (new export from ecobalyse-data#71) (#1018). Business value: stabilized test suite against evolving data/dependencies, reduced regression risk, and ensured reliable, data-driven impact assessments for stakeholders.
March 2025
1 Commits
Mar 1, 2025March 2025 monthly summary for MTES-MCT/ecobalyse. Focused on stabilizing strategy handling and data processing by fixing explicit strategies and HTC/HTN handling. Integrated improvements from external PRs and reinforced reliability of strategy-based computations across the pipeline.
1 Commits
Mar 1, 2025March 2025 monthly summary for MTES-MCT/ecobalyse. Focused on stabilizing strategy handling and data processing by fixing explicit strategies and HTC/HTN handling. Integrated improvements from external PRs and reinforced reliability of strategy-based computations across the pipeline.
March 2025
February 2025
4 Commits • 4 Features
Feb 1, 2025February 2025 monthly summary for MTES-MCT/ecobalyse focused on risk reduction, data integrity, and cross-repo interoperability. Delivered four core changes that improve release safety, data exchange capabilities, and migration stability, while reinforcing collaboration with the ecobalyse-data repository.
February 2025
4 Commits • 4 Features
Feb 1, 2025February 2025 monthly summary for MTES-MCT/ecobalyse focused on risk reduction, data integrity, and cross-repo interoperability. Delivered four core changes that improve release safety, data exchange capabilities, and migration stability, while reinforcing collaboration with the ecobalyse-data repository.
December 2024
3 Commits • 1 Features
Dec 1, 2024December 2024 — MTES-MCT/ecobalyse: Focused on stabilizing data ingestion, improving performance, and strengthening data integrity. Implemented targeted patching for AGB imports, merged PastoEco CSVs into a single file to speed imports, and linked PastoEco processes to the AGB 3.1.1 database for accurate impact calculations. Added duplicate activity name prevention in the editor to improve data quality. These changes collectively shorten data load times, reduce import errors, and improve reliability for downstream analytics and reporting.
3 Commits • 1 Features
Dec 1, 2024December 2024 — MTES-MCT/ecobalyse: Focused on stabilizing data ingestion, improving performance, and strengthening data integrity. Implemented targeted patching for AGB imports, merged PastoEco CSVs into a single file to speed imports, and linked PastoEco processes to the AGB 3.1.1 database for accurate impact calculations. Added duplicate activity name prevention in the editor to improve data quality. These changes collectively shorten data load times, reduce import errors, and improve reliability for downstream analytics and reporting.
December 2024
November 2024
7 Commits • 4 Features
Nov 1, 2024November 2024 monthly summary for MTES-MCT/ecobalyse. Focused on expanding data export capabilities, strengthening data integration, and improving reliability of large-scale imports. Delivered object-level export and traceability enhancements, integrated Woolmark LCI data with external DB linking, and implemented robust fixes to support parallel imports. Expanded ingredient data import and search, and added dynamic irrigation data for organic cotton to improve accuracy of environmental impact assessments. These efforts improve business value by enabling more accurate, auditable LCAs, smoother data pipelines, and faster, safer data sharing across teams.
November 2024
7 Commits • 4 Features
Nov 1, 2024November 2024 monthly summary for MTES-MCT/ecobalyse. Focused on expanding data export capabilities, strengthening data integration, and improving reliability of large-scale imports. Delivered object-level export and traceability enhancements, integrated Woolmark LCI data with external DB linking, and implemented robust fixes to support parallel imports. Expanded ingredient data import and search, and added dynamic irrigation data for organic cotton to improve accuracy of environmental impact assessments. These efforts improve business value by enabling more accurate, auditable LCAs, smoother data pipelines, and faster, safer data sharing across teams.
Activity
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Quality Metrics
Correctness88.0%
Maintainability84.2%
Architecture79.6%
Performance78.0%
AI Usage21.6%
Skills & Technologies
Programming Languages
ElmJSONJavaScriptPythonShellTypeScriptYAML
Technical Skills
API DevelopmentAPI DocumentationAPI IntegrationAPI integrationBackend DevelopmentBug FixingChoreCode AnalysisCode ManagementCode RefactoringData AnalysisData EngineeringData ExportData ImportData Integration
Repositories Contributed To
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