# Development Process — Test-Develop-Debug

## Local Environment
- Ubuntu dev machine, Python 3.12, virtualenv at `.venv/`
- Always use `.venv/bin/python` or activate with `source .venv/bin/activate` before running Python commands
- Node.js 24 via nvm — always load nvm before running Node/npm/npx commands:
  `export NVM_DIR="$HOME/.nvm" && [ -s "$NVM_DIR/nvm.sh" ] && . "$NVM_DIR/nvm.sh" && nvm use 24`
- For tools not available in `.venv/` (ruff, gh, etc.), install via pip or apt as needed
- Frontend tests: load nvm first, then `cd frontend && npx vitest --run`
- Python tests: `.venv/bin/ruff check services/` then `.venv/bin/python -m pytest tests/ -x --tb=short -q`

## Workflow
1. Write or update tests for the target behavior
2. Implement the minimal code to pass
3. Debug failures, fix, re-run
4. Commit and push — CI builds images automatically
5. Deploy: `helm upgrade --install stonks-oracle infra/helm/stonks-oracle -n stonks-oracle`
6. Restart changed services: `kubectl rollout restart deployment/<name> -n stonks-oracle`

## Testing
- Python: `pytest` with `pytest-asyncio` for async code, tests in `tests/`
- Property-based tests: Hypothesis with `@settings(max_examples=100)`, files prefixed `test_pbt_*`
- Frontend: Vitest + MSW (Mock Service Worker) for deterministic API mocking, tests in `frontend/src/test/`
- Run Python tests: `python -m pytest tests/ -x --tb=short -q`
- Run frontend tests: `cd frontend && npx vitest --run`
- Lint Python: `.venv/bin/ruff check services/`
- Ruff is pinned to `ruff==0.15.10` in `requirements.txt` — CI uses the same version
- Ruff config: `ruff.toml` with `known-first-party = ["services"]` for consistent import sorting
- Pre-existing test failures (not regressions): `test_extractor_prompts.py`, `test_extractor_schemas.py`, `test_filings_adapter.py`, `test_ollama_client.py`

## CI/CD — GitHub Actions
- Workflow: `.github/workflows/build.yml`
- Triggers on push to `main` and PRs
- Jobs:
  - `lint-and-test`: ruff lint + pytest + frontend vitest (Node 24)
  - `build-services`: matrix build of all Python services → GHCR
  - `build-dashboard`: frontend/Dockerfile → GHCR (TypeScript strict mode — catches unused imports)
  - `build-superset`: docker/Dockerfile.superset → GHCR
- CI handles all image builds and pushes — do NOT manually docker push
- Check CI: `gh run list -L 3`
- Re-run failed: `gh run rerun <id> --failed`
- View failure logs: `gh run view <id> --log-failed`

## Deploy
- Full deploy/redeploy: `bash ~/sources/kube/stonks-oracle/runmefirst.sh` (from gremlin-1)
- Full teardown: `bash ~/sources/kube/stonks-oracle/runmelast.sh` (from gremlin-1)
- Quick Helm upgrade: `helm upgrade --install stonks-oracle infra/helm/stonks-oracle -n stonks-oracle`
- Restart single service: `kubectl rollout restart deployment/<name> -n stonks-oracle`
- Restart multiple: `kubectl rollout restart deployment/aggregation deployment/query-api deployment/dashboard -n stonks-oracle`
- Check pods: `kubectl get pods -n stonks-oracle`
- Check logs: `kubectl logs deployment/<name> -n stonks-oracle --tail=30`

## Manually Triggering Ingestion
The scheduler runs on a cadence, but to trigger immediately:
```python
# From a scheduler pod:
kubectl exec -n stonks-oracle <scheduler-pod> -- python -c "
import redis, json, asyncio, asyncpg
async def enqueue():
    pool = await asyncpg.create_pool(dsn='postgresql://stonks:<password>@postgresql-rw.postgresql-service.svc.cluster.local:5432/stonks')
    r = redis.from_url('redis://:<password>@redis-master.redis-service.svc.cluster.local:6379/0')
    rows = await pool.fetch('SELECT s.id AS source_id, s.source_type, s.config, c.id AS company_id, c.ticker FROM sources s JOIN companies c ON c.id = s.company_id WHERE s.active = TRUE AND c.active = TRUE')
    for row in rows:
        cfg = row['config'] if isinstance(row['config'], dict) else {}
        r.rpush('stonks:queue:ingestion', json.dumps({'source_id': str(row['source_id']), 'source_type': row['source_type'], 'ticker': row['ticker'], 'company_id': str(row['company_id']), 'config': cfg}))
    await pool.close()
asyncio.run(enqueue())
"
```
Ingestion jobs MUST include `source_id`, `source_type`, `ticker`, `company_id`, and `config`.

## Git Conventions
- Commit after each completed phase task
- Commit message format: `feat:`, `fix:`, `phase N:` prefix
- Push to `main` triggers CI

## Code Style
- Python 3.12, type hints everywhere
- Pydantic for data validation
- FastAPI for HTTP services
- asyncio + asyncpg/aioredis for async I/O
- Minimal dependencies, prefer stdlib where possible
- Frontend: React 19, TypeScript strict mode, Tailwind CSS, TanStack Router/Query, Recharts for charts
- UUID fields from asyncpg must be converted to str via `_row_dict()` helpers
- asyncpg interval parameters must be Python `timedelta` objects, not SQL strings
- Recharts v3 callbacks: do NOT add explicit type annotations on `formatter`/`tickFormatter` — let TypeScript infer

## Common Pitfalls
- asyncpg expects `timedelta` for `$N::interval` params, not strings like `'7 days'`
- asyncpg expects UUID objects/strings for `$N::uuid` params — synthetic IDs like `pattern:AAPL:earnings:7d` will fail
- The `competitor_relationships` table uses UUID company IDs — queries must join through `companies` to match by ticker
- The dashboard Docker build uses TypeScript strict mode — unused imports that pass local diagnostics will fail in CI
- Ingestion jobs require `source_id` from the `sources` table — don't just pass `ticker`

## Documentation
- Do NOT create large summary/success markdown files after each step
- Keep notes short, concise, and organized under `docs/notes/`
- If a note isn't useful for future reference, don't write it
