TonyKat007/Astral-trails
Jul 2025 – Jul 2025
1 Month active
Languages Used
CSVPython
Technical Skills
Data ProcessingData VisualizationFoliumFront-end DevelopmentFull Stack DevelopmentPandas
mahi
PROFILE
Mahi
Developed two core features for the Astral-trails repository, focusing on real-time visualization of cosmic ray shower events. Leveraging Python, Pandas, and Folium, the work integrated live CSV data ingestion with timestamped event mapping, enabling users to filter and explore intensity-categorized, color-coded markers on an interactive map. The implementation included UI and tile layer refinements to improve map reliability, data attribution, and user experience. Updates to app.py and data source management enhanced maintainability and scalability, while clear attribution and data handling reduced ambiguity for future analytics. The project established a robust foundation for ongoing data-driven feature development.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
11Total
Bugs
0
Commits
11
Features
2
Lines of code
1,542
Activity Months1
Your Network
11 peopleWork History
July 2025
11 Commits • 2 Features
Jul 1, 2025July 2025 — TonyKat007/Astral-trails: Delivered two major enhancements for the Live Cosmic Ray Shower Map with robust data integration, tile/UI refinements, and real-time CSV-based visualization. This work improves data visibility, user experience, and data attribution while strengthening the foundation for future analytics. Key features delivered: - Cosmic Ray Shower Map Visualization — Tile & UI Refinements: Refined map tile source, initialization, attribution, and UI defaults (intensity filter, layout) to improve map reliability and user experience. - Real-time Cosmic Ray Data Visualization from CSV: Implemented real-time data display using a CSV data source with timestamped events, intensity categorization, color-coded markers, and user filtering; added/updated data file and attribution/renaming updates. Major bugs fixed: - No explicit major bugs documented this month. Stability improvements were applied to app.py and data ingestion to support feature delivery and ensure reliable map rendering and CSV data handling. Overall impact and accomplishments: - Faster time-to-insight for live cosmic ray events through real-time CSV visualization and improved map UI. - Improved data attribution integrity and source management, reducing ambiguity for downstream analytics. - Enhanced maintainability with focused app.py changes and clearer data source handling, setting the stage for future feature work and scalability. Technologies/skills demonstrated: - Python backend updates (app.py) for map initialization and data ingestion. - CSV data processing and real-time data rendering. - Front-end map visualization using tile layers and UI controls. - Data source management and attribution handling. - Version control hygiene through incremental commits across multiple updates.
11 Commits • 2 Features
Jul 1, 2025July 2025 — TonyKat007/Astral-trails: Delivered two major enhancements for the Live Cosmic Ray Shower Map with robust data integration, tile/UI refinements, and real-time CSV-based visualization. This work improves data visibility, user experience, and data attribution while strengthening the foundation for future analytics. Key features delivered: - Cosmic Ray Shower Map Visualization — Tile & UI Refinements: Refined map tile source, initialization, attribution, and UI defaults (intensity filter, layout) to improve map reliability and user experience. - Real-time Cosmic Ray Data Visualization from CSV: Implemented real-time data display using a CSV data source with timestamped events, intensity categorization, color-coded markers, and user filtering; added/updated data file and attribution/renaming updates. Major bugs fixed: - No explicit major bugs documented this month. Stability improvements were applied to app.py and data ingestion to support feature delivery and ensure reliable map rendering and CSV data handling. Overall impact and accomplishments: - Faster time-to-insight for live cosmic ray events through real-time CSV visualization and improved map UI. - Improved data attribution integrity and source management, reducing ambiguity for downstream analytics. - Enhanced maintainability with focused app.py changes and clearer data source handling, setting the stage for future feature work and scalability. Technologies/skills demonstrated: - Python backend updates (app.py) for map initialization and data ingestion. - CSV data processing and real-time data rendering. - Front-end map visualization using tile layers and UI controls. - Data source management and attribution handling. - Version control hygiene through incremental commits across multiple updates.
July 2025
Activity
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Quality Metrics
Correctness87.2%
Maintainability91.0%
Architecture76.4%
Performance78.2%
AI Usage20.0%
Skills & Technologies
Programming Languages
CSVPython
Technical Skills
Data ProcessingData VisualizationFoliumFront-end DevelopmentFull Stack DevelopmentPandasPythonStreamlitWeb Development
Repositories Contributed To
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