MTES-MCT/ecobalyse
Dec 2024 – Jun 2026
19 Months active
Languages Used
ElmHTMLJavaScriptMakefilePythonJSONShellYAML
Technical Skills
Backend DevelopmentCode RefactoringCode StandardizationData EngineeringData ProcessingFrontend Development
paulboosz
PROFILE
Paulboosz
Over 19 months, contributed to MTES-MCT/ecobalyse by designing and delivering 44 features and resolving 16 bugs, focusing on environmental data modeling, API development, and data integrity. Built and refactored core backend and frontend components using Python, Elm, and JavaScript, enabling robust lifecycle assessments and streamlined data exports. Implemented modular data pipelines, standardized JSON handling, and enhanced CI/CD workflows to improve calculation accuracy and release reliability. Addressed complex data synchronization, environmental impact analysis, and cross-domain data integration challenges. The work emphasized maintainable code, rigorous testing, and clear documentation, supporting scalable analytics, regulatory compliance, and collaborative development across evolving datasets.
Overall Statistics
Feature vs Bugs
73%Features
Repository Contributions
100Total
Bugs
16
Commits
100
Features
44
Lines of code
6,090,020
Activity Months19
Your Network
10 peopleWork History
June 2026
5 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary for MTES-MCT/ecobalyse: - Key features delivered: 1) Moved food complements coefficients from frontend to a dedicated data pipeline module, with a dedicated complements.py for clarity, improving accuracy and maintainability; introduced a GitHub Action to validate ingredient impact hierarchy and generate violation reports/visualizations. 2) Process alias support in UI: added alias field, updated encoding/decoding logic, and enhanced explorer view to display alias for better process context. - Major bugs fixed: 1) Environmental calculation precision fixes: reduced land occupation precision from 5 to 4 decimals to reduce computation discrepancies and corrected forest complement factor values; tests updated to reflect changes. 2) Additional test coverage around precision and factor corrections. - Overall impact and accomplishments: Improved calculation accuracy and data governance, reduced numerical diffs in environmental impact results, automated data-quality checks, and a more contextual UI. These changes enhance reliability for decision-makers and streamline future maintenance. - Technologies/skills demonstrated: data-pipeline refactor and modularization (complements.py), Python data modeling, GitHub Actions CI/CD for validation and reporting, test maintenance and updates, UI/UX enhancements, and data visualization/reporting integration.
5 Commits • 2 Features
Jun 1, 2026June 2026 monthly summary for MTES-MCT/ecobalyse: - Key features delivered: 1) Moved food complements coefficients from frontend to a dedicated data pipeline module, with a dedicated complements.py for clarity, improving accuracy and maintainability; introduced a GitHub Action to validate ingredient impact hierarchy and generate violation reports/visualizations. 2) Process alias support in UI: added alias field, updated encoding/decoding logic, and enhanced explorer view to display alias for better process context. - Major bugs fixed: 1) Environmental calculation precision fixes: reduced land occupation precision from 5 to 4 decimals to reduce computation discrepancies and corrected forest complement factor values; tests updated to reflect changes. 2) Additional test coverage around precision and factor corrections. - Overall impact and accomplishments: Improved calculation accuracy and data governance, reduced numerical diffs in environmental impact results, automated data-quality checks, and a more contextual UI. These changes enhance reliability for decision-makers and streamline future maintenance. - Technologies/skills demonstrated: data-pipeline refactor and modularization (complements.py), Python data modeling, GitHub Actions CI/CD for validation and reporting, test maintenance and updates, UI/UX enhancements, and data visualization/reporting integration.
June 2026
May 2026
9 Commits • 2 Features
May 1, 2026May 2026 was a productive sprint for MTES-MCT/ecobalyse, delivering expanded data coverage, strengthened data integrity, and improved traceability across data pipelines. The dataset enrichment and catalog expansion work adds new food ingredients with detailed attributes (environmental impact, processing details) and introduces battery cell production activities into the LCI catalog, enabling more complete life-cycle assessments and scenario analyses. This was supported by targeted commits that add cmaps transformed ingredients and battery cells to the LCI catalog, laying groundwork for richer analytics and reporting. In addition, data consistency and accuracy improvements were implemented to reduce data drift. This included removing obsolete data, adjusting coefficients for grazed grass, updating ingredient origins, and refining the data model with qtyVariationRatio for clarity and accuracy. These changes improve result reliability and make future updates more maintainable. Regression fixes for cooking metrics and feed data ensured stable, trustworthy metrics. Cooking impacts were restored after a regression, and feed data regressions were addressed by updating ingredient names and adding organic feed types for 2025 data, stabilizing historical analyses. Finally, data workflow visibility was enhanced by adding a changes-tracking file to the ecobalyse-data sync workflow, improving traceability between the data repository and the main repo. Overall, the month delivered measurable business value: broader data coverage for ESG insights, more accurate and traceable metrics, and stronger data governance across the data lifecycle. The work demonstrates proficiency in data modeling, data quality, regression testing, and CI/CD workflow improvements.
May 2026
9 Commits • 2 Features
May 1, 2026May 2026 was a productive sprint for MTES-MCT/ecobalyse, delivering expanded data coverage, strengthened data integrity, and improved traceability across data pipelines. The dataset enrichment and catalog expansion work adds new food ingredients with detailed attributes (environmental impact, processing details) and introduces battery cell production activities into the LCI catalog, enabling more complete life-cycle assessments and scenario analyses. This was supported by targeted commits that add cmaps transformed ingredients and battery cells to the LCI catalog, laying groundwork for richer analytics and reporting. In addition, data consistency and accuracy improvements were implemented to reduce data drift. This included removing obsolete data, adjusting coefficients for grazed grass, updating ingredient origins, and refining the data model with qtyVariationRatio for clarity and accuracy. These changes improve result reliability and make future updates more maintainable. Regression fixes for cooking metrics and feed data ensured stable, trustworthy metrics. Cooking impacts were restored after a regression, and feed data regressions were addressed by updating ingredient names and adding organic feed types for 2025 data, stabilizing historical analyses. Finally, data workflow visibility was enhanced by adding a changes-tracking file to the ecobalyse-data sync workflow, improving traceability between the data repository and the main repo. Overall, the month delivered measurable business value: broader data coverage for ESG insights, more accurate and traceable metrics, and stronger data governance across the data lifecycle. The work demonstrates proficiency in data modeling, data quality, regression testing, and CI/CD workflow improvements.
April 2026
8 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for MTES-MCT/ecobalyse focusing on features delivered, bugs fixed, and overall impact. Highlights include ecosystemic services data modeling and calculation improvements, metadata standardization, and privacy enhancements, with UI/data accuracy fixes.
8 Commits • 2 Features
Apr 1, 2026April 2026 monthly summary for MTES-MCT/ecobalyse focusing on features delivered, bugs fixed, and overall impact. Highlights include ecosystemic services data modeling and calculation improvements, metadata standardization, and privacy enhancements, with UI/data accuracy fixes.
April 2026
March 2026
9 Commits • 3 Features
Mar 1, 2026March 2026 monthly summary for MTES-MCT/ecobalyse: Delivered key data-model and dataset improvements, fixed critical sync and explorer issues, and expanded environmental datasets to broaden assessment coverage. Focused on delivering business value through data integrity, reliable exports, and improved communication across teams. Key points: - Data model and data integrity improvements (features): unified alias naming across ingredients and activities; updated processes JSON to include metadata and landOccupation fields; cleaned legacy references and streamlined exports to improve data integrity. - Commits: 98740aa160c0c00035c3053fc821199c6a30fe2c; 163b87d81af36d3ee7e3d3e32d8493fefe114bbd; b1ba42123a4bb62bacea2fe25135815a67f94743; af8b2a724084ccca882e8f8de4d1df699dc048db; 1fbae73f23b94dd1ca659b54d4ff0e58f8808a7c; 1e707b17152403921812c0620ee4a7c5b890e844 - Ingredient alias display in explorer (feature): Added the ability to display ingredient aliases in the explorer to improve communication and debugging. - Commit: 619e1f277f32a4c23bb2a18e024f08349374aa67 - Dataset enrichment: aluminium extrusion process and live animal data (feature): Expanded dataset with a new aluminium extrusion process and added data entries for live animals (beef cattle, broilers, pigs, lambs) to support environmental assessments. - Commits: 03bf7c5c6b888a1e92d9dd2b782038f7d98179ea; 90f7a4931b8502e2232c43c9203666f30ed2e2d9 Major bugs fixed: - ecobalyse-data sync (fix): Resolved out-of-sync state between ecobalyse and ecobalyse-data. - Commit: af8b2a724084ccca882e8f8de4d1df699dc048db - Duplicates in explorer (fix): Removed non-generic scopes from the generic export to prevent duplicate processes. - Commit: 1fbae73f23b94dd1ca659b54d4ff0e58f8808a7c - Update object/veli example ids (fix): Updated IDs to reference the new processes_generic.json to avoid broken links. - Commit: 1e707b17152403921812c0620ee4a7c5b890e844 - Remove object/veli from processes.json (chore): Clean up references to object/veli in processes.json. - Commit: b1ba42123a4bb62bacea2fe25135815a67f94743 Overall impact and accomplishments: - Improved data integrity and export reliability, enabling more accurate reporting for environmental assessments. - Faster debugging and cross-team collaboration thanks to explicit ingredient alias visibility in the explorer. - Expanded dataset coverage for aluminium extrusion and live animal data, empowering broader scenario analysis and compliance reporting. Technologies/skills demonstrated: - Data modeling and schema alignment, JSON migrations, and data synchronization. - UI/UX debugging enhancements (explorer alias display). - Cross-repo coordination with ecobalyse and ecobalyse-data teams; composable data pipelines and robust data exports.
March 2026
9 Commits • 3 Features
Mar 1, 2026March 2026 monthly summary for MTES-MCT/ecobalyse: Delivered key data-model and dataset improvements, fixed critical sync and explorer issues, and expanded environmental datasets to broaden assessment coverage. Focused on delivering business value through data integrity, reliable exports, and improved communication across teams. Key points: - Data model and data integrity improvements (features): unified alias naming across ingredients and activities; updated processes JSON to include metadata and landOccupation fields; cleaned legacy references and streamlined exports to improve data integrity. - Commits: 98740aa160c0c00035c3053fc821199c6a30fe2c; 163b87d81af36d3ee7e3d3e32d8493fefe114bbd; b1ba42123a4bb62bacea2fe25135815a67f94743; af8b2a724084ccca882e8f8de4d1df699dc048db; 1fbae73f23b94dd1ca659b54d4ff0e58f8808a7c; 1e707b17152403921812c0620ee4a7c5b890e844 - Ingredient alias display in explorer (feature): Added the ability to display ingredient aliases in the explorer to improve communication and debugging. - Commit: 619e1f277f32a4c23bb2a18e024f08349374aa67 - Dataset enrichment: aluminium extrusion process and live animal data (feature): Expanded dataset with a new aluminium extrusion process and added data entries for live animals (beef cattle, broilers, pigs, lambs) to support environmental assessments. - Commits: 03bf7c5c6b888a1e92d9dd2b782038f7d98179ea; 90f7a4931b8502e2232c43c9203666f30ed2e2d9 Major bugs fixed: - ecobalyse-data sync (fix): Resolved out-of-sync state between ecobalyse and ecobalyse-data. - Commit: af8b2a724084ccca882e8f8de4d1df699dc048db - Duplicates in explorer (fix): Removed non-generic scopes from the generic export to prevent duplicate processes. - Commit: 1fbae73f23b94dd1ca659b54d4ff0e58f8808a7c - Update object/veli example ids (fix): Updated IDs to reference the new processes_generic.json to avoid broken links. - Commit: 1e707b17152403921812c0620ee4a7c5b890e844 - Remove object/veli from processes.json (chore): Clean up references to object/veli in processes.json. - Commit: b1ba42123a4bb62bacea2fe25135815a67f94743 Overall impact and accomplishments: - Improved data integrity and export reliability, enabling more accurate reporting for environmental assessments. - Faster debugging and cross-team collaboration thanks to explicit ingredient alias visibility in the explorer. - Expanded dataset coverage for aluminium extrusion and live animal data, empowering broader scenario analysis and compliance reporting. Technologies/skills demonstrated: - Data modeling and schema alignment, JSON migrations, and data synchronization. - UI/UX debugging enhancements (explorer alias display). - Cross-repo coordination with ecobalyse and ecobalyse-data teams; composable data pipelines and robust data exports.
February 2026
2 Commits • 2 Features
Feb 1, 2026February 2026 performance summary for MTES-MCT/ecobalyse. Focused on clarifying product identification and expanding environmental data modeling. Delivered two features with direct business value and prepared groundwork for future analytics.
2 Commits • 2 Features
Feb 1, 2026February 2026 performance summary for MTES-MCT/ecobalyse. Focused on clarifying product identification and expanding environmental data modeling. Delivered two features with direct business value and prepared groundwork for future analytics.
February 2026
January 2026
6 Commits • 3 Features
Jan 1, 2026January 2026 performance for MTES-MCT/ecobalyse: Delivered core enhancements to packaging and material data, improved UI usability for the food comparator, and fixed a key bug affecting detailed impacts processing. These changes strengthen data quality for lifecycle assessments, enhance calculation accuracy, and improve user workflows.
January 2026
6 Commits • 3 Features
Jan 1, 2026January 2026 performance for MTES-MCT/ecobalyse: Delivered core enhancements to packaging and material data, improved UI usability for the food comparator, and fixed a key bug affecting detailed impacts processing. These changes strengthen data quality for lifecycle assessments, enhance calculation accuracy, and improve user workflows.
December 2025
6 Commits • 1 Features
Dec 1, 2025December 2025 performance summary for MTES-MCT/ecobalyse: Delivered data quality fixes for export data and product visibility, and completed ecological data model enhancements with naming consistency. These efforts improved data integrity for exports, corrected dataset inaccuracies by filtering out incorrect beef products, standardized unit handling for wood processes, introduced new ecological fields (e.g., livestock density, permanent pasture), and aligned the database schema and naming conventions. The work reduces downstream data corrections, supports better analytics and reporting, and lays groundwork for scalable data capture, dashboards, and compliance.
6 Commits • 1 Features
Dec 1, 2025December 2025 performance summary for MTES-MCT/ecobalyse: Delivered data quality fixes for export data and product visibility, and completed ecological data model enhancements with naming consistency. These efforts improved data integrity for exports, corrected dataset inaccuracies by filtering out incorrect beef products, standardized unit handling for wood processes, introduced new ecological fields (e.g., livestock density, permanent pasture), and aligned the database schema and naming conventions. The work reduces downstream data corrections, supports better analytics and reporting, and lays groundwork for scalable data capture, dashboards, and compliance.
December 2025
November 2025
6 Commits • 1 Features
Nov 1, 2025November 2025: MTES-MCT/ecobalyse delivered substantive data model enhancements and environmental data improvements, enabling clearer data, more reliable exports, and richer environmental impact analysis. Implemented targeted data categorization, transformation processes, and governance updates to improve data clarity, maintainability, and analytics readiness. Key outcomes include stabilization of processing IDs, scope extension for transport processes, and improved data asset hygiene. Technologies demonstrated include data modeling, JSON management, and refactoring with naming consistency.
November 2025
6 Commits • 1 Features
Nov 1, 2025November 2025: MTES-MCT/ecobalyse delivered substantive data model enhancements and environmental data improvements, enabling clearer data, more reliable exports, and richer environmental impact analysis. Implemented targeted data categorization, transformation processes, and governance updates to improve data clarity, maintainability, and analytics readiness. Key outcomes include stabilization of processing IDs, scope extension for transport processes, and improved data asset hygiene. Technologies demonstrated include data modeling, JSON management, and refactoring with naming consistency.
October 2025
6 Commits • 4 Features
Oct 1, 2025October 2025 (MTES-MCT/ecobalyse): Delivered stability fixes, new processing capabilities, and a data-model overhaul that enhances reliability and global usability. Key outcomes include cross-architecture precision fixes, restoration of essential paraffin processes, and new UUID-based material identifiers, along with metal incineration and vehicle processing features.
6 Commits • 4 Features
Oct 1, 2025October 2025 (MTES-MCT/ecobalyse): Delivered stability fixes, new processing capabilities, and a data-model overhaul that enhances reliability and global usability. Key outcomes include cross-architecture precision fixes, restoration of essential paraffin processes, and new UUID-based material identifiers, along with metal incineration and vehicle processing features.
October 2025
September 2025
1 Commits • 1 Features
Sep 1, 2025In September 2025, MTES-MCT/ecobalyse delivered a targeted refactor to standardize end-of-life terminology across Python and Elm, improving data clarity and consistency for end-of-life handling. The change aligns terminology with product expectations and lays groundwork for material-type specific processing, with minimal risk to existing workflows. Commit-driven change supported by updated tests ensures ongoing data quality and maintainability.
September 2025
1 Commits • 1 Features
Sep 1, 2025In September 2025, MTES-MCT/ecobalyse delivered a targeted refactor to standardize end-of-life terminology across Python and Elm, improving data clarity and consistency for end-of-life handling. The change aligns terminology with product expectations and lays groundwork for material-type specific processing, with minimal risk to existing workflows. Commit-driven change supported by updated tests ensures ongoing data quality and maintainability.
August 2025
1 Commits
Aug 1, 2025Month 2025-08: Focused on improving data integrity in Ecobalyse by correcting material property inputs used in environmental impact calculations. Delivered a precise fix to density values for oil and seed/nuts, preventing potential inaccuracies in downstream results and strengthening the reliability of model outputs used for stakeholder reporting and regulatory assessments.
1 Commits
Aug 1, 2025Month 2025-08: Focused on improving data integrity in Ecobalyse by correcting material property inputs used in environmental impact calculations. Delivered a precise fix to density values for oil and seed/nuts, preventing potential inaccuracies in downstream results and strengthening the reliability of model outputs used for stakeholder reporting and regulatory assessments.
August 2025
July 2025
8 Commits • 4 Features
Jul 1, 2025July 2025 summary: In July 2025, MTES-MCT/ecobalyse delivered key frontend and data-model enhancements to strengthen environmental impact analysis and reporting. Delivered new Ingredient Explorer capabilities displaying cropGroup and Scenario, added CropGroup and Scenario modules, updated Ingredient decoding, and extended FoodIngredients with new fields to align UI with data model. Implemented sawing process support for environmental impact analysis/resource management. Improved energy calculations by using low-voltage French electricity in the utilization step and standardizing electricity naming in France. Introduced the average aquatic pollution scenario for pretreatment dyeing. Fixed configuration and labeling issues, correcting WTU unit representation (m3 eq) and updating default trim values for accuracy and usability.
July 2025
8 Commits • 4 Features
Jul 1, 2025July 2025 summary: In July 2025, MTES-MCT/ecobalyse delivered key frontend and data-model enhancements to strengthen environmental impact analysis and reporting. Delivered new Ingredient Explorer capabilities displaying cropGroup and Scenario, added CropGroup and Scenario modules, updated Ingredient decoding, and extended FoodIngredients with new fields to align UI with data model. Implemented sawing process support for environmental impact analysis/resource management. Improved energy calculations by using low-voltage French electricity in the utilization step and standardizing electricity naming in France. Introduced the average aquatic pollution scenario for pretreatment dyeing. Fixed configuration and labeling issues, correcting WTU unit representation (m3 eq) and updating default trim values for accuracy and usability.
June 2025
5 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for MTES-MCT/ecobalyse focusing on delivery of core features, bug fixes, and cross-repo data integration, with emphasis on business value and technical impact. Deliverables include expanded modeling capabilities, improved data visibility in explorers, and alignment of environmental impact calculations across tests and configurations.
5 Commits • 3 Features
Jun 1, 2025June 2025 monthly summary for MTES-MCT/ecobalyse focusing on delivery of core features, bug fixes, and cross-repo data integration, with emphasis on business value and technical impact. Deliverables include expanded modeling capabilities, improved data visibility in explorers, and alignment of environmental impact calculations across tests and configurations.
June 2025
May 2025
5 Commits • 2 Features
May 1, 2025May 2025 performance summary: Delivered key architectural and data-management improvements in MTES-MCT/ecobalyse, enabling cross-domain reuse and faster releases, fixed critical data processing bug, and expanded object processing and material classification with robust test coverage. The month focused on business value through streamlined release pipelines, data consolidation, and elevated data integrity, while showcasing strong software craftsmanship and cross-functional collaboration.
May 2025
5 Commits • 2 Features
May 1, 2025May 2025 performance summary: Delivered key architectural and data-management improvements in MTES-MCT/ecobalyse, enabling cross-domain reuse and faster releases, fixed critical data processing bug, and expanded object processing and material classification with robust test coverage. The month focused on business value through streamlined release pipelines, data consolidation, and elevated data integrity, while showcasing strong software craftsmanship and cross-functional collaboration.
April 2025
4 Commits • 3 Features
Apr 1, 2025April 2025: Achievements focused on data integrity, API stability, and user-relevant features in Ecobalyse. Implemented a hardened process data model with mandatory sourceId and displayName, introduced deterministic process IDs for ingredients to stabilize IDs across shared processes, added ingredient visibility controls, and aligned test data and material descriptions. Result: reduced ID drift, improved selection relevance, and more reliable test coverage, delivering tangible business value and preparing the platform for broader collaboration.
4 Commits • 3 Features
Apr 1, 2025April 2025: Achievements focused on data integrity, API stability, and user-relevant features in Ecobalyse. Implemented a hardened process data model with mandatory sourceId and displayName, introduced deterministic process IDs for ingredients to stabilize IDs across shared processes, added ingredient visibility controls, and aligned test data and material descriptions. Result: reduced ID drift, improved selection relevance, and more reliable test coverage, delivering tangible business value and preparing the platform for broader collaboration.
April 2025
March 2025
4 Commits • 3 Features
Mar 1, 2025March 2025: Delivered three key initiatives in MTES-MCT/ecobalyse that strengthen testing, data quality, and processing capabilities. Enabled all verticals in review environments to broaden testing scope without production risk. Standardized naming across score history and ingredients to improve test stability and reduce ambiguity. Introduced plastic transformation processing in the ecobalyse data/processing layer to close a missing capability and enable end-to-end data workflows. These changes collectively accelerate QA cycles, reduce misconfigurations, and lay groundwork for ongoing feature delivery.
March 2025
4 Commits • 3 Features
Mar 1, 2025March 2025: Delivered three key initiatives in MTES-MCT/ecobalyse that strengthen testing, data quality, and processing capabilities. Enabled all verticals in review environments to broaden testing scope without production risk. Standardized naming across score history and ingredients to improve test stability and reduce ambiguity. Introduced plastic transformation processing in the ecobalyse data/processing layer to close a missing capability and enable end-to-end data workflows. These changes collectively accelerate QA cycles, reduce misconfigurations, and lay groundwork for ongoing feature delivery.
February 2025
7 Commits • 5 Features
Feb 1, 2025February 2025 — MTES-MCT/ecobalyse monthly summary: Delivered five core features across data integrity, data modeling, calculation accuracy, and API consistency, complemented by data quality improvements and CI/CD reliability enhancements. These changes reduce PR data-discrepancy risks, improve model/test alignment, and standardize API responses, driving faster, more trustworthy releases.
7 Commits • 5 Features
Feb 1, 2025February 2025 — MTES-MCT/ecobalyse monthly summary: Delivered five core features across data integrity, data modeling, calculation accuracy, and API consistency, complemented by data quality improvements and CI/CD reliability enhancements. These changes reduce PR data-discrepancy risks, improve model/test alignment, and standardize API responses, driving faster, more trustworthy releases.
February 2025
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 — MTES-MCT/ecobalyse: Key enhancements and fixes delivered across code quality, data integrity, and simulation accuracy. Tech debt reduction achieved via CI and pre-commit improvements; data corrections improved materials handling accuracy; simulator updates aligned with updated pre-treatments and bleaching logic, with tests adjusted. These changes improved build reliability, data integrity, and the fidelity of processing simulations, enabling more reliable decisions and faster release readiness.
January 2025
5 Commits • 1 Features
Jan 1, 2025January 2025 — MTES-MCT/ecobalyse: Key enhancements and fixes delivered across code quality, data integrity, and simulation accuracy. Tech debt reduction achieved via CI and pre-commit improvements; data corrections improved materials handling accuracy; simulator updates aligned with updated pre-treatments and bleaching logic, with tests adjusted. These changes improved build reliability, data integrity, and the fidelity of processing simulations, enabling more reliable decisions and faster release readiness.
December 2024
3 Commits • 2 Features
Dec 1, 2024December 2024 — MTES-MCT/ecobalyse: Key features delivered include Data Formatting Consistency Across Exports and Units, and Textile Data Processing Enhancements: Trim Workflow. No major bugs fixed; stabilization efforts focused on formatting and unit normalization to ensure reliable exports and calculations. Overall impact: improved export readability, reduced diffs and calculation inconsistencies, and groundwork for a robust textile data processing pipeline. Technologies/skills demonstrated: JSON encoding standardization, unit normalization (t⋅km), data structure refactors, and modular component design.
3 Commits • 2 Features
Dec 1, 2024December 2024 — MTES-MCT/ecobalyse: Key features delivered include Data Formatting Consistency Across Exports and Units, and Textile Data Processing Enhancements: Trim Workflow. No major bugs fixed; stabilization efforts focused on formatting and unit normalization to ensure reliable exports and calculations. Overall impact: improved export readability, reduced diffs and calculation inconsistencies, and groundwork for a robust textile data processing pipeline. Technologies/skills demonstrated: JSON encoding standardization, unit normalization (t⋅km), data structure refactors, and modular component design.
December 2024
Activity
Loading activity data...
Quality Metrics
Correctness91.8%
Maintainability89.2%
Architecture87.8%
Performance85.8%
AI Usage24.8%
Skills & Technologies
Programming Languages
BashCSSElmHTMLJSONJavaScriptMakefileMarkdownPythonShell
Technical Skills
API DesignAPI DevelopmentAPI IntegrationAPI developmentAPI integrationBackend DevelopmentBackend developmentBuild AutomationCI/CDCode CleanupCode RefactoringCode StandardizationConfiguration ManagementCross-domain ReusabilityData Analysis
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline