fix: resolve numpy type conversion issues in ML service data access

- Convert numpy.int64 to Python int before passing to SQLAlchemy queries
- Prevents psycopg2.ProgrammingError: can't adapt type 'numpy.int64'
- Applied to get_candles(), get_span_annotations(), and get_point_annotations()
- All ML service database access tests now passing successfully
This commit is contained in:
Marko Djordjevic 2026-02-17 14:10:21 +01:00
parent 5377431c9d
commit d1557a3846
6 changed files with 437 additions and 119 deletions

View file

@ -47,7 +47,7 @@
## 8. Testing and Verification
- [x] 8.1 Run the full application locally with PostgreSQL — verify all API routes work
- [ ] 8.2 Verify ML service can query candle/annotation data from shared database
- [ ] 8.3 Run `docker compose up` and verify all services start correctly with new configuration
- [ ] 8.4 Update `DEPLOYMENT.md` with new deployment steps (PostgreSQL migration, data migration script, rollback procedure)
- [ ] 8.5 Update `README.md` and `CLAUDE_DESCRIPTION.md` with database architecture changes
- [x] 8.2 Verify ML service can query candle/annotation data from shared database
- [x] 8.3 Run `docker compose up` and verify all services start correctly with new configuration
- [x] 8.4 Update `DEPLOYMENT.md` with new deployment steps (PostgreSQL migration, data migration script, rollback procedure)
- [x] 8.5 Update `README.md` and `CLAUDE_DESCRIPTION.md` with database architecture changes