Houjio/HarmoniQ
Mar 2025 – Apr 2025
2 Months active
Languages Used
CSVMakefilePythonShellSQL
Technical Skills
Backend DevelopmentCSV ManipulationData EngineeringData LoadingDatabase DesignDatabase Integration
Yanis Aksas
PROFILE
Yanis Aksas
Developed core backend infrastructure for the Houjio/HarmoniQ repository, delivering an end-to-end power grid data model and database population framework. Leveraged Python, SQLAlchemy, and Pandas to design database schemas for buses, lines, and line types, and implemented CSV-driven data loading pipelines to automate and scale network data population. Enhanced simulation fidelity by introducing selective data loading, wind time-series generation, and demand data integration, while optimizing network import/export through caching and robustness improvements. Established REST API groundwork to support future backend extensibility. The work focused on reliability, maintainability, and production readiness, providing a solid foundation for scalable energy systems modeling.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
20Total
Bugs
0
Commits
20
Features
4
Lines of code
15,111
Activity Months2
Your Network
9 peopleShared Repositories
9
Work History
April 2025
13 Commits • 3 Features
Apr 1, 2025April 2025 – Houjio/HarmoniQ: Focused on expanding simulation fidelity, data efficiency, and API readiness. Key work included enhancements to energy network simulations with selective data loading, wind time-series generation, demand data integration, and new production endpoints; network data caching and robustness improvements for faster, more reliable imports/exports; and REST API groundwork to position the backend for future functionality. These efforts improved data processing throughput, reduced load times, and established production endpoint readiness for broader deployment.
13 Commits • 3 Features
Apr 1, 2025April 2025 – Houjio/HarmoniQ: Focused on expanding simulation fidelity, data efficiency, and API readiness. Key work included enhancements to energy network simulations with selective data loading, wind time-series generation, demand data integration, and new production endpoints; network data caching and robustness improvements for faster, more reliable imports/exports; and REST API groundwork to position the backend for future functionality. These efforts improved data processing throughput, reduced load times, and established production endpoint readiness for broader deployment.
April 2025
March 2025
7 Commits • 1 Features
Mar 1, 2025In March 2025, delivered an end-to-end Power Grid Data Model and Database Population Framework for Houjio/HarmoniQ, establishing core modeling constructs and ready-to-load DB schemas for buses, lines, and line types with integer primary keys. Implemented CSV-driven data population scripts and integrated loading with the database to populate lines, line_type, and bus data, enabling automated, scalable population of network data. Updated the static network data loading path, added IDs to the network schema, and corrected hydro data routing to improve data integrity. This work provides a production-ready data pipeline foundation and a solid platform for future topology extensions and power flow modeling. No critical bugs were reported this month; the focus was on feature delivery, reliability, and maintainability.
March 2025
7 Commits • 1 Features
Mar 1, 2025In March 2025, delivered an end-to-end Power Grid Data Model and Database Population Framework for Houjio/HarmoniQ, establishing core modeling constructs and ready-to-load DB schemas for buses, lines, and line types with integer primary keys. Implemented CSV-driven data population scripts and integrated loading with the database to populate lines, line_type, and bus data, enabling automated, scalable population of network data. Updated the static network data loading path, added IDs to the network schema, and corrected hydro data routing to improve data integrity. This work provides a production-ready data pipeline foundation and a solid platform for future topology extensions and power flow modeling. No critical bugs were reported this month; the focus was on feature delivery, reliability, and maintainability.
Activity
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Quality Metrics
Correctness86.4%
Maintainability84.0%
Architecture85.0%
Performance76.0%
AI Usage21.0%
Skills & Technologies
Programming Languages
CSVMakefilePythonSQLShell
Technical Skills
API DevelopmentAPI IntegrationAsyncioBackend DevelopmentCSV ManipulationData EngineeringData LoadingData ManagementData ModelingDatabase DesignDatabase IntegrationDatabase InteractionDatabase ManagementEnergy SystemsEnergy Systems Modeling
Repositories Contributed To
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