September 2025 focused on strengthening API reliability, data integrity, and scalable data modeling across rating and rental services. Delivered two key feature sets, addressed critical data format bugs, and laid groundwork for accurate inventory reporting. Key outcomes included improved API response consistency (Lecturer Ratings), enhanced code quality, robust rental session deadline management with migration-safe changes, and more accurate item availability reporting through a hybrid property. These changes support faster client integrations, reduce downstream data errors, and enable safer migration paths with timezone-aware processing and validation. Technologies demonstrated include Pydantic models, rigorous validation, lint-driven code quality, hybrid properties, and migration-safe schema changes.

August 2025 performance summary for profcomff/rating-api: Delivered migration of rating fields into the main lecturer table with corresponding API schema and route updates; introduced a new endpoint to update lecturer ratings; fixed delete-lecturer endpoint; refined update responses; and completed code cleanup with lint fixes and simplified data fetching logic. Demonstrated solid API design, database migration, data modeling, code refactoring, and testing practices to improve reliability and business value.