Freshness Dry Run

Dry-run a freshness threshold against historical data.

Tests a proposed freshness threshold against a table's actual update history to predict how many alerts would fire. This helps users tune thresholds before enabling monitoring.

SDK Usage:

from anomalyarmor import Client
client = Client()

result = client.freshness.dry_run(
    asset_id="my-asset-uuid",
    table_path="public.orders",
    expected_interval_hours=2.0,
    lookback_days=7,
)

print(f"Alert rate: {result.alert_rate_percent}%")
print(f"Recommendation: {result.recommendation}")