tests/cda/locations/physical_locations_CDA_test.py

-Original file line number
+Diff line change
@@ -0,0 +1,112 @@
+    import pytest
+    import cwms.locations.physical_locations as locations
+    TEST_OFFICE = "SPK"
+    TEST_LOCATION_ID = "pytest-loc-123"
+    TEST_LATITUDE = 44.0
+    TEST_LONGITUDE = -93.0
+    BASE_LOCATION_DATA = {
+        "name": TEST_LOCATION_ID,
+        "office-id": TEST_OFFICE,
+        "latitude": TEST_LATITUDE,
+        "longitude": TEST_LONGITUDE,
+        "elevation": 250.0,
+        "horizontal-datum": "NAD83",
+        "vertical-datum": "NAVD88",
+        "location-type": "TESTING",
+        "public-name": "Test Location",
+        "long-name": "A pytest-generated location",
+        "timezone-name": "America/Los_Angeles",
+        "location-kind": "SITE",
+        "nation": "US",
+    }
+    @pytest.fixture(autouse=True)
+    def init_session(request):
+        print("Initializing CWMS API session for locations operations test...")
+    def test_store_location():
+        locations.store_location(BASE_LOCATION_DATA)
+        df = locations.get_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE).df
+        assert TEST_LOCATION_ID in df["name"].values
+    def test_update_location_public_name():
+        updated_data = BASE_LOCATION_DATA.copy()
+        updated_data["public-name"] = "Updated Public Name"
+        locations.store_location(updated_data)
+        df_updated = locations.get_location(
+            location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE
+        ).df
+        row = df_updated[df_updated["name"] == TEST_LOCATION_ID].iloc[0]
+        assert row["public-name"] == "Updated Public Name"
+    def test_delete_location():
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.delete_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE)
+        df_final = locations.get_locations(
+            office_id=TEST_OFFICE, location_ids=TEST_LOCATION_ID
+        ).df
+        assert df_final.empty or TEST_LOCATION_ID not in df_final.get("name", [])
+    def test_get_location_returns_expected_data():
+        locations.store_location(BASE_LOCATION_DATA)
+        result = locations.get_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE)
+        df = result.df
+        # Check returned data matches stored location
+        assert df.shape[0] == 1
+        row = df.iloc[0]
+        assert row["name"] == TEST_LOCATION_ID
+        assert row["office-id"] == TEST_OFFICE
+        assert row["latitude"] == TEST_LATITUDE
+        assert row["longitude"] == TEST_LONGITUDE
+    def test_get_locations_returns_expected_location():
+        # Store both locations
+        second_location_id = "pytest-loc-456"
+        second_location_data = BASE_LOCATION_DATA.copy()
+        second_location_data["name"] = second_location_id
+        second_location_data["longitude"] = -94.0
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.store_location(second_location_data)
+        # Retrieve both locations
+        pattern = f"{TEST_LOCATION_ID}|{second_location_id}"
+        result = locations.get_locations(office_id=TEST_OFFICE, location_ids=pattern)
+        df = result.df
+        for loc_data in [BASE_LOCATION_DATA, second_location_data]:
+            loc_id = loc_data["name"]
+            assert loc_id in df["name"].values
+            row = df[df["name"] == loc_id].iloc[0]
+            for key in ["office-id", "latitude", "longitude"]:
+                assert row[key] == loc_data[key]
+    def test_get_locations_returns_multiple_locations():
+        # Store a second location
+        second_location_id = "pytest-loc-456"
+        second_location_data = BASE_LOCATION_DATA.copy()
+        second_location_data["name"] = second_location_id
+        second_location_data["longitude"] = -94.0
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.store_location(second_location_data)
+        # Retrieve both locations
+        pattern = f"{TEST_LOCATION_ID}|{second_location_id}"
+        result = locations.get_locations(office_id=TEST_OFFICE, location_ids=pattern)
+        df = result.df
+        # Check that both locations are present
+        loc_ids = df["name"].values
+        assert TEST_LOCATION_ID in loc_ids
+        assert second_location_id in loc_ids

tests/cda/timeseries/timeseries_CDA_test.py

Empty file.

Adding physical_locations_CDA_test.py #162

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Merged

tlelv merged 18 commits into main from CDA-testing

Jul 23, 2025

-Original file line number
+Diff line change
@@ -0,0 +1,112 @@
+    import pytest
+    import cwms.locations.physical_locations as locations
+    TEST_OFFICE = "SPK"
+    TEST_LOCATION_ID = "pytest-loc-123"
+    TEST_LATITUDE = 44.0
+    TEST_LONGITUDE = -93.0
+    BASE_LOCATION_DATA = {
+        "name": TEST_LOCATION_ID,
+        "office-id": TEST_OFFICE,
+        "latitude": TEST_LATITUDE,
+        "longitude": TEST_LONGITUDE,
+        "elevation": 250.0,
+        "horizontal-datum": "NAD83",
+        "vertical-datum": "NAVD88",
+        "location-type": "TESTING",
+        "public-name": "Test Location",
+        "long-name": "A pytest-generated location",
+        "timezone-name": "America/Los_Angeles",
+        "location-kind": "SITE",
+        "nation": "US",
+    }
+    @pytest.fixture(autouse=True)
+    def init_session(request):
+        print("Initializing CWMS API session for locations operations test...")
+    def test_store_location():
+        locations.store_location(BASE_LOCATION_DATA)
+        df = locations.get_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE).df
+        assert TEST_LOCATION_ID in df["name"].values
+    def test_update_location_public_name():
+        updated_data = BASE_LOCATION_DATA.copy()
+        updated_data["public-name"] = "Updated Public Name"
+        locations.store_location(updated_data)
+        df_updated = locations.get_location(
+            location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE
+        ).df
+        row = df_updated[df_updated["name"] == TEST_LOCATION_ID].iloc[0]
+        assert row["public-name"] == "Updated Public Name"
+    def test_delete_location():
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.delete_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE)
+        df_final = locations.get_locations(
+            office_id=TEST_OFFICE, location_ids=TEST_LOCATION_ID
+        ).df
+        assert df_final.empty or TEST_LOCATION_ID not in df_final.get("name", [])
+    def test_get_location_returns_expected_data():
+        locations.store_location(BASE_LOCATION_DATA)
+        result = locations.get_location(location_id=TEST_LOCATION_ID, office_id=TEST_OFFICE)
+        df = result.df
+        # Check returned data matches stored location
+        assert df.shape[0] == 1
+        row = df.iloc[0]
+        assert row["name"] == TEST_LOCATION_ID
+        assert row["office-id"] == TEST_OFFICE
+        assert row["latitude"] == TEST_LATITUDE
+        assert row["longitude"] == TEST_LONGITUDE
+    def test_get_locations_returns_expected_location():
+        # Store both locations
+        second_location_id = "pytest-loc-456"
+        second_location_data = BASE_LOCATION_DATA.copy()
+        second_location_data["name"] = second_location_id
+        second_location_data["longitude"] = -94.0
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.store_location(second_location_data)
+        # Retrieve both locations
+        pattern = f"{TEST_LOCATION_ID}|{second_location_id}"
+        result = locations.get_locations(office_id=TEST_OFFICE, location_ids=pattern)
+        df = result.df
+        for loc_data in [BASE_LOCATION_DATA, second_location_data]:
+            loc_id = loc_data["name"]
+            assert loc_id in df["name"].values
+            row = df[df["name"] == loc_id].iloc[0]
+            for key in ["office-id", "latitude", "longitude"]:
+                assert row[key] == loc_data[key]
+    def test_get_locations_returns_multiple_locations():
+        # Store a second location
+        second_location_id = "pytest-loc-456"
+        second_location_data = BASE_LOCATION_DATA.copy()
+        second_location_data["name"] = second_location_id
+        second_location_data["longitude"] = -94.0
+        locations.store_location(BASE_LOCATION_DATA)
+        locations.store_location(second_location_data)
+        # Retrieve both locations
+        pattern = f"{TEST_LOCATION_ID}|{second_location_id}"
+        result = locations.get_locations(office_id=TEST_OFFICE, location_ids=pattern)
+        df = result.df
+        # Check that both locations are present
+        loc_ids = df["name"].values
+        assert TEST_LOCATION_ID in loc_ids
+        assert second_location_id in loc_ids

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