Verification
Practical checks when authoring or shipping open-fdd rules.
1. Unit tests (CI)
From the repo root with dev dependencies:
pip install -e ".[dev]"
pytest
2. Rule YAML sanity
- Load each file with
load_rule()or pointRuleRunner(rules_path=...)at the directory. - Confirm every
inputskey has a matching entry incolumn_map(or manifest) before callingrun().
3. Small DataFrame smoke test
from pathlib import Path
import pandas as pd
from open_fdd.engine.runner import RuleRunner
df = pd.read_csv("your_sample.csv", parse_dates=["timestamp"]).set_index("timestamp")
runner = RuleRunner(rules_path=Path("path/to/rules"))
out = runner.run(df, timestamp_col="timestamp", column_map={"Supply_Air_Temperature_Sensor": "SAT"})
assert out.filter(like="_flag").shape[1] >= 1
Platform / database checks
For HTTP APIs, databases, Brick / 223P graph workflows, and observability around a deployed stack, see open-fdd-afdd-stack documentation.