stonks-oracle/.kiro/steering/development-process.md

Development Process — Test-Develop-Debug

Local Environment

• Python 3.12 via NixOS, virtualenv at .venv/
• Always use .venv/bin/python or activate with source .venv/bin/activate before running Python commands
• For tools not available in .venv/ (ruff, gh, etc.), use nix-shell -p <pkg> --run "<cmd>"
• Node.js 24 for frontend; frontend/ has its own node_modules/
• Frontend tests: cd frontend && npx vitest --run
• Python tests: nix-shell -p ruff --run "ruff check services/" then 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: nix-shell -p ruff --run "ruff check services/"
• 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: nix-shell -p gh --run "gh run list -L 3" or gh run list -L 3
• Re-run failed: nix-shell -p gh --run "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:

# 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