add some tests for inventory fxns

tests/test_inventory.py

@@ -0,0 +1,76 @@
+import pandas as pd
+import pytest
+from stactools.noaa_hrrr.constants import (
+    PRODUCT_FORECAST_HOUR_SETS,
+    ForecastCycleType,
+    ForecastHourSet,
+    Product,
+    Region,
+)
+from stactools.noaa_hrrr.inventory import (
+    DATA_COLS,
+    generate_single_inventory_df,
+    load_inventory_df,
+)
+
+product_forecast_hour_combinations = [
+    (product, fh_set)
+    for product, fh_sets in PRODUCT_FORECAST_HOUR_SETS.items()
+    for fh_set in fh_sets
+]
+
+
+@pytest.mark.parametrize("region", list(Region))  # type: ignore
+@pytest.mark.parametrize(
+    "product, forecast_hour_set",
+    product_forecast_hour_combinations,
+)  # type: ignore
+@pytest.mark.parametrize(
+    "forecast_cycle_type",
+    [ForecastCycleType(type) for type in ["standard", "extended"]],
+)  # type: ignore
+def test_load_inventory_df(
+    region: Region,
+    product: Product,
+    forecast_hour_set: ForecastHourSet,
+    forecast_cycle_type: ForecastCycleType,
+) -> None:
+    inventory_df = load_inventory_df(
+        region=region,
+        product=product,
+        forecast_hour_set=forecast_hour_set,
+        forecast_cycle_type=forecast_cycle_type,
+    )
+
+    assert isinstance(inventory_df, pd.DataFrame)
+
+    assert list(inventory_df.keys()) == DATA_COLS + ["description", "unit"]
+
+
+@pytest.mark.parametrize("region", list(Region))  # type: ignore
+@pytest.mark.parametrize(
+    "product, forecast_hour_set",
+    product_forecast_hour_combinations,
+)  # type: ignore
+@pytest.mark.parametrize(
+    "forecast_cycle_type",
+    [ForecastCycleType(type) for type in ["standard", "extended"]],
+)  # type: ignore
+def test_generate_single_inventory_df(
+    region: Region,
+    product: Product,
+    forecast_hour_set: ForecastHourSet,
+    forecast_cycle_type: ForecastCycleType,
+) -> None:
+    inventory_df = generate_single_inventory_df(
+        region=region,
+        product=product,
+        forecast_cycle_type=forecast_cycle_type,
+        forecast_hour_set=forecast_hour_set,
+        cycle_run_hour=0 if forecast_cycle_type.type == "extended" else 3,
+        forecast_hour=0
+        if forecast_hour_set in [ForecastHourSet.FH00, ForecastHourSet.FH01_18]
+        else 3,
+    )
+
+    assert isinstance(inventory_df, pd.DataFrame)