fix(test): Correct forecast/all horizon test

Author: devsjc

pyproject.toml

@@ -56,9 +56,9 @@ dev = [
     "types-grpcio>=1.0.0.20251009",
     "sqlalchemy-stubs>=0.4",
     "psycopg2-binary>=2.9.11",
-    "freezegun>=1.5.5",
     "ty>=0.0.25",
     "pyinstrument>=5.1.2",
+    "time-machine[dateutil]>=3.2.0",
 ]
 
 [tool.uv.sources]

src/quartz_api/internal/backends/test_utils.py

@@ -1,12 +1,12 @@
 import datetime as dt
 
-from freezegun import freeze_time
+import time_machine
 
 from quartz_api.internal.backends.utils import get_window
 
 
+@time_machine.travel(dt.datetime(2023, 1, 1), tick=False)
 def test_get_window_defaults() -> None:
-    with freeze_time("2023-01-01"):
-        start, end = get_window()
-        assert start == dt.datetime(2022, 12, 30, tzinfo=dt.UTC)
-        assert end == dt.datetime(2023, 1, 3, tzinfo=dt.UTC)
+    start, end = get_window()
+    assert start == dt.datetime(2022, 12, 30, tzinfo=dt.UTC)
+    assert end == dt.datetime(2023, 1, 3, tzinfo=dt.UTC)

src/quartz_api/tests/integration/conftest.py

@@ -123,8 +123,10 @@ async def gsp_locations(dp_client: service_pb2_grpc.DataPlatformDataServiceStub)
     """Make national location."""
     # add location gsp 1 to 10
     location_uuids = []
+    gsp_id_map.clear()
     for i in range(1, 11):
-        metadata = Struct(fields={"gsp_id": Value(number_value=i)})
+        metadata = Struct()
+        metadata.update({"gsp_id": i})
         create_location_request = make_location(
             name=f"gsp_{i}",
             gsp_id=i,
@@ -134,7 +136,6 @@ async def gsp_locations(dp_client: service_pb2_grpc.DataPlatformDataServiceStub)
         res = await dp_client.CreateLocation(create_location_request)
         location_uuids.append(res.location_uuid)
 
-        gsp_id_map.clear()
         gsp_id_map[i] = models.Location(
             uuid=UUID(res.location_uuid),
             metadata={"gsp_id": i},
@@ -153,7 +154,8 @@ async def national_location(
 ) -> messages_pb2.CreateLocationResponse:
     """Make national location."""
     # add location gsp 0
-    metadata = Struct(fields={"gsp_id": Value(number_value=0)})
+    metadata = Struct()
+    metadata.update({"gsp_id": 0})
     create_location_request = make_location(name="uk", gsp_id=0, metadata=metadata)
     create_location_response = await dp_client.CreateLocation(create_location_request)
 

src/quartz_api/tests/integration/uk_national/test_app.py

@@ -1,7 +1,9 @@
+import datetime as dt
+
 import pandas as pd
 import pytest
 from fastapi_cache import FastAPICache
-
+import time_machine
 
 # 1. Does the app start up, and can we use health
 @pytest.mark.asyncio(loop_scope="session")
@@ -41,14 +43,20 @@ async def test_national_forecast_horizon_minutes(
 
     We are testing for forecast_horizon of 120 minutes
     """
+    # make_national_forecast_values makes forecasts from now floored to 30 minutes
+    # in half hour intervals back to -7 hours ago. Each forecast is 4.5 hours of 30-minute
+    # seperated values. This is a total of 24 unique timestamps. With a horizon of 120,
+    # we should lose four of these.
+    future_time = dt.datetime.now(tz=dt.UTC) + dt.timedelta(minutes=120, milliseconds=-1)
+    with time_machine.travel(future_time, tick=False):
+        response = await api_client_uk_national.get(
+            "/v0/solar/GB/national/forecast?forecast_horizon_minutes=120"
+        )
 
-    response = await api_client_uk_national.get(
-        "/v0/solar/GB/national/forecast?forecast_horizon_minutes=120",
-    )
     assert response.status_code == 200
     data = response.json()
     assert isinstance(data, list)
-    assert len(data) == 16
+    assert len(data) == 20
 
 
 # 2.2 Test the National Forecast, include metadata
@@ -350,8 +358,8 @@ async def test_gsp_forecast_all_for_one_timestamp_compact(
 async def test_gsp_pvlive_all(
     api_client_uk_national,
     gsp_locations,  # noqa arg001
-    make_forecasters,  # noqa arg001
-    make_gsp_forecast_values,  # noqa arg001
+    make_observers, # noqa arg001
+    make_gsp_observation_values,  # noqa arg001
 ) -> None:
     """Test a sample endpoint for UK National forecast data."""