preset-io/superset
Jan 2026 – Feb 2026
2 Months active
Languages Used
TypeScriptJavaScriptPython
Technical Skills
TypeScriptfront end developmentFlaskReactdata visualizationfull stack development
Jonathan Alberth Quispe Fuentes
PROFILE
Jonathan Alberth Quispe Fuentes
Jonathan contributed to the preset-io/superset repository by enhancing dashboard accuracy and reliability through targeted feature development and bug fixes. He improved the CurrencyFormatter to maintain D3 formatting semantics, introducing normalization logic for consistent currency and percentage outputs using TypeScript and front end development skills. In subsequent work, Jonathan addressed heatmap visualization issues by ensuring correct rank processing in normalized mode and expanded regression test coverage. He also optimized data loading in the RoleListEditModal, reducing N+1 queries and implementing role-based user filtering with Flask and React. His work demonstrated thoughtful engineering, balancing maintainability, performance, and robust test-driven validation across the stack.
Overall Statistics
Feature vs Bugs
67%Features
Repository Contributions
3Total
Bugs
1
Commits
3
Features
2
Lines of code
366
Activity Months2
Your Network
162 peopleWork History
February 2026
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for preset-io/superset: Focused on delivering precise visual rendering, data loading efficiency, and robust test coverage to support business dashboards and reliability.
2 Commits • 1 Features
Feb 1, 2026February 2026 monthly summary for preset-io/superset: Focused on delivering precise visual rendering, data loading efficiency, and robust test coverage to support business dashboards and reliability.
February 2026
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for preset-io/superset focusing on currency formatting improvements.
January 2026
1 Commits • 1 Features
Jan 1, 2026January 2026 (2026-01) monthly summary for preset-io/superset focusing on currency formatting improvements.
Activity
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Quality Metrics
Correctness93.4%
Maintainability80.0%
Architecture80.0%
Performance86.6%
AI Usage20.0%
Skills & Technologies
Programming Languages
JavaScriptPythonTypeScript
Technical Skills
FlaskReactTypeScriptdata visualizationfront end developmentfull stack developmenttesting
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