Datasets:
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.
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.