5f70f13da3
- Remove better-sqlite3, add pg driver - Convert schema to PostgreSQL types (serial, timestamp, boolean, jsonb) - Generate fresh PostgreSQL migrations - Update database connection layer with pg.Pool - Fix all API routes: remove JSON.parse/stringify, use native timestamps and booleans - Update drizzle.config.ts and .env.example for PostgreSQL
53 lines
3.4 KiB
Markdown
53 lines
3.4 KiB
Markdown
## 1. Dependencies and Configuration
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- [x] 1.1 Remove `better-sqlite3` and `@types/better-sqlite3` from package.json
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- [x] 1.2 Add `pg` and `@types/pg` to package.json dependencies
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- [x] 1.3 Run `npm install` to update node_modules and lockfile
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- [x] 1.4 Update `drizzle.config.ts` to target `postgresql` dialect with `DATABASE_URL` env var
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- [x] 1.5 Update `.env.example` — replace `DATABASE_PATH` with `DATABASE_URL=postgresql://ml_user:ml_password@postgres:5432/candle_annotator`
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## 2. Drizzle Schema Migration (SQLite → PostgreSQL)
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- [x] 2.1 Rewrite `src/lib/db/schema.ts` — replace all `sqliteTable` with `pgTable`, apply type mappings (integer→serial, integer→timestamp, integer→boolean, real→doublePrecision, text JSON→jsonb)
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- [x] 2.2 Delete all existing SQLite migration files in `drizzle/` directory
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- [x] 2.3 Run `drizzle-kit generate` to produce fresh PostgreSQL migration SQL
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- [x] 2.4 Review generated migration SQL for correctness
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## 3. Database Connection Layer
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- [x] 3.1 Rewrite `src/lib/db/index.ts` — replace `better-sqlite3` driver with `pg.Pool` (max: 10), read `DATABASE_URL` from env, fail if missing
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- [x] 3.2 Update migration runner to use PostgreSQL-compatible execution (skip during build phase via `NEXT_PHASE` check)
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- [x] 3.3 Update all imports if any changed (verify `db` export still works for API routes)
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## 4. API Route Adjustments
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- [x] 4.1 Audit all Next.js API routes using `db` for SQLite-specific syntax (e.g., integer booleans, raw SQL fragments)
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- [x] 4.2 Fix any SQLite-specific query patterns to work with PostgreSQL (boolean handling, timestamp handling, jsonb operations)
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- [x] 4.3 Update health check endpoint (`/api/health`) to verify PostgreSQL connectivity
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## 5. Docker and Deployment
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- [ ] 5.1 Update `docker-compose.yml` — rename `POSTGRES_DB` to `candle_annotator`, add `DATABASE_URL` env to candle-annotator service, add `depends_on: postgres` with health check condition
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- [ ] 5.2 Remove `candle-data` volume from `docker-compose.yml` (SQLite volume)
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- [ ] 5.3 Update `Dockerfile` if it references SQLite or `DATABASE_PATH`
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- [ ] 5.4 Update ML service database connection — change database name from `ml_db` to `candle_annotator` in environment config
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## 6. ML Service Direct Data Access
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- [ ] 6.1 Add SQLAlchemy table reflections or raw queries in the ML service for reading `candles`, `annotations`, `span_annotations`, `charts` tables
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- [ ] 6.2 Update ML training pipeline to query candle/annotation data from PostgreSQL instead of CSV/JSON exports
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- [ ] 6.3 Remove or deprecate any CSV/JSON export code paths that are no longer needed
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## 7. Data Migration Script
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- [ ] 7.1 Create `scripts/migrate-sqlite-to-postgres.ts` — read all 6 tables from SQLite, apply type conversions (timestamps, booleans, JSON→jsonb), insert into PostgreSQL
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- [ ] 7.2 Make the script idempotent (skip or clear+re-insert with flag)
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- [ ] 7.3 Test migration script with existing SQLite data
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## 8. Testing and Verification
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- [ ] 8.1 Run the full application locally with PostgreSQL — verify all API routes work
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- [ ] 8.2 Verify ML service can query candle/annotation data from shared database
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- [ ] 8.3 Run `docker compose up` and verify all services start correctly with new configuration
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- [ ] 8.4 Update `DEPLOYMENT.md` with new deployment steps (PostgreSQL migration, data migration script, rollback procedure)
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- [ ] 8.5 Update `README.md` and `CLAUDE_DESCRIPTION.md` with database architecture changes
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