Cavitation Experiment Database
Database Design and Python API Development for High Frequency Experiment Data.
A team project replacing an HDF5/JSON-based ad-hoc storage setup for cavitation experiment data with a proper database. Raw sensor readings and run metadata previously lived in scattered files with no shared schema, which made cross-experiment queries and downstream analysis painful. We modeled the data in TimescaleDB — a PostgreSQL extension built for time-series workloads — under a unified schema covering both high-frequency sensor data and experiment metadata.
On top of the database, I built a documented Python API for ingesting new experiment runs and querying existing ones, so the rest of the team could pull data without hand-writing SQL. The project also set up unit and integration tests plus GitLab CI/CD for linting, testing, and documentation deployment, since the database was meant to be a shared, maintained piece of lab infrastructure rather than a one-off script.