
Umidjon Miakiev developed and enhanced backend APIs for the profcomff/rental-api and profcomff/rating-api repositories, focusing on robust item management, session workflows, and dynamic data retrieval. He applied Python, FastAPI, and SQLAlchemy to implement and refine features such as item update flows, session lifecycle handling, and lecturer filtering with FastAPI-Filter. His work included extensive test suite refactoring using Pytest and Docker-based environments, improving reliability and maintainability. By addressing race conditions, optimizing database migrations with Alembic, and enforcing code quality through refactoring and documentation, Umidjon delivered stable, well-tested APIs that support business logic and efficient release cycles.

August 2025: Delivered reliability, performance, and data-access improvements across rental-api and rating-api, focusing on correct business workflows, stable test infrastructure, and maintainable code. Key fixes ensure correct session lifecycle, robust test environment, and race-condition prevention in external API calls, while the API surface gained enhanced filtering, sorting, and maintainability.
August 2025: Delivered reliability, performance, and data-access improvements across rental-api and rating-api, focusing on correct business workflows, stable test infrastructure, and maintainable code. Key fixes ensure correct session lifecycle, robust test environment, and race-condition prevention in external API calls, while the API surface gained enhanced filtering, sorting, and maintainability.
July 2025 highlights: Stability improvements to rental-api session handling, robust test suite and environment configuration, and API enhancement in rating-api with a new filter parameter. These changes reduce production risk, improve CI reliability, and deliver faster, more precise data retrieval for clients. Demonstrated skills include test hygiene, environment configuration, and API design with a focus on business value.
July 2025 highlights: Stability improvements to rental-api session handling, robust test suite and environment configuration, and API enhancement in rating-api with a new filter parameter. These changes reduce production risk, improve CI reliability, and deliver faster, more precise data retrieval for clients. Demonstrated skills include test hygiene, environment configuration, and API design with a focus on business value.
May 2025 summary for profcomff/rental-api: Upgraded test reliability and maintainability through Rental Session Test Suite Refactor and Fixture Improvements. Key actions include consolidating and refactoring tests, introducing parametrization for creation/start/return paths, isolating tests for item availability vs non-availability, removing unused fields, reworking fixture scope and database setup, adding a Docker-based test DB, and standardizing ID handling. Expanded edge-case coverage across rental session workflows (availability, non-availability, reservations) with improved test data management.
May 2025 summary for profcomff/rental-api: Upgraded test reliability and maintainability through Rental Session Test Suite Refactor and Fixture Improvements. Key actions include consolidating and refactoring tests, introducing parametrization for creation/start/return paths, isolating tests for item availability vs non-availability, removing unused fields, reworking fixture scope and database setup, adding a Docker-based test DB, and standardizing ID handling. Expanded edge-case coverage across rental session workflows (availability, non-availability, reservations) with improved test data management.
April 2025 monthly summary for profcomff/rental-api focusing on delivering robust item management APIs, strengthening test coverage, and improving code quality. Key outcomes include feature delivery, bug fixes, and groundwork for runtime improvements that collectively increase reliability, speed of release cycles, and business value.
April 2025 monthly summary for profcomff/rental-api focusing on delivering robust item management APIs, strengthening test coverage, and improving code quality. Key outcomes include feature delivery, bug fixes, and groundwork for runtime improvements that collectively increase reliability, speed of release cycles, and business value.
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