wtg/shubble
Dec 2025 – Dec 2025
1 Month active
Languages Used
Python
Technical Skills
API developmentFlaskPythonalgorithm designbackend developmentcaching strategies
averym16
PROFILE
Averym16
Developed an end-to-end Shuttle Scheduling System in the wtg/shubble repository, focusing on real-time schedule matching that integrates live vehicle locations and robust backend logic. Leveraged Python and Flask to design a simplified single GET API endpoint, streamlining access to matched schedules while reducing maintenance overhead. Implemented a caching layer for schedule data, ensuring efficient data retrieval and freshness through cache invalidation on updates. Enhanced system reliability by adding validation and handling for empty datasets, and enabled real-time recalibration of schedules in response to vehicle data changes. Emphasized algorithm design, data processing, and error handling to deliver a maintainable backend solution.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
9Total
Bugs
0
Commits
9
Features
1
Lines of code
742
Activity Months1
Your Network
16 peopleWork History
December 2025
9 Commits • 1 Features
Dec 1, 2025Month 2025-12: Delivered end-to-end Shuttle Scheduling System in wtg/shubble, featuring core scheduling logic, real-time schedule matching with live vehicle locations, a caching layer for schedule data, a simplified single GET API, and robustness improvements (validation and empty-data handling). Enabled real-time recalibration on vehicle data changes and ensured cache invalidation on data updates to maintain freshness. Updated worker to re-match schedules on every request for up-to-date results.
9 Commits • 1 Features
Dec 1, 2025Month 2025-12: Delivered end-to-end Shuttle Scheduling System in wtg/shubble, featuring core scheduling logic, real-time schedule matching with live vehicle locations, a caching layer for schedule data, a simplified single GET API, and robustness improvements (validation and empty-data handling). Enabled real-time recalibration on vehicle data changes and ensured cache invalidation on data updates to maintain freshness. Updated worker to re-match schedules on every request for up-to-date results.
December 2025
Activity
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Quality Metrics
Correctness88.8%
Maintainability82.2%
Architecture82.2%
Performance84.4%
AI Usage22.2%
Skills & Technologies
Programming Languages
Python
Technical Skills
API developmentFlaskPythonalgorithm designbackend developmentcaching strategiesdata analysisdata cachingdata handlingdata processingdatabase managementerror handlinglogging
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