# Replaying the synthetic fixture

`meters.jsonl` and `readings.jsonl` are exports of the actual PostgreSQL fixture used to validate the dataset. Timestamps use UTC. The evaluation clock is fixed at `2026-10-09T05:00:00.000Z` with `Asia/Bangkok` timezone. These original synthetic rows and generation files are CC0-1.0, as described in `../meter/LICENSE`.

`data.sql` defines the tables and cumulative-reading interval view. `data-fixture.ts`, `data-config.ts`, and `data-schema.ts` document the deterministic generator. The fixture and generator source fingerprints are recorded in `../meter_validation_report.json`. There are no production connections or credentials in this release.

To replay, use a new empty PostgreSQL database. The commands below assume the dataset repository is your working directory and `psql` is installed. `PGDATABASE` selects your disposable test database and normal PostgreSQL environment variables supply your own connection settings. The final two GRANT statements in `data.sql` refer to the application's `analyst` role; omit those grants if that role does not exist in your test database.

```sh
python3 -c 'from pathlib import Path; print("\n".join(line for line in Path("meter_fixture/data.sql").read_text().splitlines() if not line.startswith("GRANT ")))' | psql --set=ON_ERROR_STOP=1
psql --set=ON_ERROR_STOP=1 --file=meter_fixture/replay.sql
```

The replay inserts all rows in a single transaction, so an interrupted or failed replay rolls back. It expects empty fixture tables and fails on duplicate primary keys. Rerun after an interrupted transaction; after a successful replay, reuse that database rather than inserting again.

Example gold query records contain PostgreSQL SQL plus positional parameters. Bind the `parameters` values to the SQL rather than interpolating them. Result hashes include the runtime evidence structure and cannot be recreated by merely concatenating SQL result files; evaluate the individual rows and aggregates when using another client.