hotosm/drone-tm
Jan 2025 – Apr 2025
4 Months active
Languages Used
PythonTOMLSQLYAMLenvJavaScriptTypeScript
Technical Skills
API DevelopmentAPI IntegrationAsynchronous ProgrammingBackend DevelopmentCloud StorageCloud Storage Integration
Niraj Adhikari
PROFILE
Niraj Adhikari
Over four months, N.R. Jadkry engineered core backend and infrastructure improvements for the hotosm/drone-tm repository, focusing on drone imagery processing, asset management, and workflow stability. He migrated image processing to asynchronous ARQ worker tasks, implemented S3-based asset management, and enhanced API endpoints for direct asset access. Using Python, FastAPI, and AWS S3, he introduced robust error handling, concurrency controls, and security hardening for drone operations. His work included database schema updates, CI/CD workflow enhancements, and integration with OpenAerialMap. These contributions improved processing throughput, data integrity, and system reliability, reflecting a deep, hands-on approach to scalable backend development.
Overall Statistics
Feature vs Bugs
70%Features
Repository Contributions
75Total
Bugs
13
Commits
75
Features
30
Lines of code
3,235
Activity Months4
Your Network
10 people
Work History
April 2025
2 Commits
Apr 1, 2025Monthly summary for 2025-04 focusing on stabilizing the core drone-tm flight planning workflow by addressing import-related runtime errors in waypoint routes and flight plan generation. Resolved incorrect imports of calculate_parameters and create_placemarks from the drone-flightplan package, ensuring correct module references and usage. This work improves reliability, repeatability, and downstream automation for flight planning.
2 Commits
Apr 1, 2025Monthly summary for 2025-04 focusing on stabilizing the core drone-tm flight planning workflow by addressing import-related runtime errors in waypoint routes and flight plan generation. Resolved incorrect imports of calculate_parameters and create_placemarks from the drone-flightplan package, ensuring correct module references and usage. This work improves reliability, repeatability, and downstream automation for flight planning.
April 2025
March 2025
9 Commits • 4 Features
Mar 1, 2025March 2025 highlights for hotosm/drone-tm: major drone imagery processing overhaul with ARQ worker tasks and S3-based asset management, security hardening for drone operations, enhanced project visibility with a status filter, and stability improvements to ensure data integrity. Release version was bumped to 2025.3.1 to align with production. These changes delivered faster imagery processing, reduced storage usage, stronger governance, improved project tracking, and reliable event history.
March 2025
9 Commits • 4 Features
Mar 1, 2025March 2025 highlights for hotosm/drone-tm: major drone imagery processing overhaul with ARQ worker tasks and S3-based asset management, security hardening for drone operations, enhanced project visibility with a status filter, and stability improvements to ensure data integrity. Release version was bumped to 2025.3.1 to align with production. These changes delivered faster imagery processing, reduced storage usage, stronger governance, improved project tracking, and reliable event history.
February 2025
56 Commits • 24 Features
Feb 1, 2025February 2025 monthly summary for hotosm/drone-tm focused on delivering observable business value, improving stability, and laying groundwork for scalable operations. Key activities spanned feature delivery, reliability enhancements, security hardening, and deployment/observability improvements.
56 Commits • 24 Features
Feb 1, 2025February 2025 monthly summary for hotosm/drone-tm focused on delivering observable business value, improving stability, and laying groundwork for scalable operations. Key activities spanned feature delivery, reliability enhancements, security hardening, and deployment/observability improvements.
February 2025
January 2025
8 Commits • 2 Features
Jan 1, 2025Performance-driven month focused on modernizing the image ingestion and asset delivery for hotosm/drone-tm. Implemented an aiohttp-based async image download and batch processing pipeline with a 4-worker concurrency limit to prevent S3 overload, added robust URL handling with a configurable S3 root, and enhanced batch naming. Extended the Project API to expose direct assets and orthophoto URLs, ensuring reliable access via dynamically generated endpoints aligned with processing status. Hardened image processing failure handling to accurately reflect success/failure in system status. These changes collectively reduce S3 load, improve processing throughput, improve asset accessibility, and strengthen system observability.
January 2025
8 Commits • 2 Features
Jan 1, 2025Performance-driven month focused on modernizing the image ingestion and asset delivery for hotosm/drone-tm. Implemented an aiohttp-based async image download and batch processing pipeline with a 4-worker concurrency limit to prevent S3 overload, added robust URL handling with a configurable S3 root, and enhanced batch naming. Extended the Project API to expose direct assets and orthophoto URLs, ensuring reliable access via dynamically generated endpoints aligned with processing status. Hardened image processing failure handling to accurately reflect success/failure in system status. These changes collectively reduce S3 load, improve processing throughput, improve asset accessibility, and strengthen system observability.
Activity
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Quality Metrics
Correctness87.4%
Maintainability87.6%
Architecture84.2%
Performance82.4%
AI Usage21.4%
Skills & Technologies
Programming Languages
JavaScriptPythonSQLTOMLTypeScriptYAMLenv
Technical Skills
API DevelopmentAPI IntegrationARQAWS S3Asynchronous ProgrammingAsynchronous Task ProcessingAsynchronous Task QueuesAuthenticationBackend DevelopmentCI/CDCachingCloud IntegrationCloud ServicesCloud StorageCloud Storage Integration
Repositories Contributed To
Overview of all repositories you've contributed to across your timeline