fix(test): test_output's monkeypatching of pd.read_csv

python/ngen_cal/src/ngen/cal/calibration_cathment.py

@@ -1,11 +1,10 @@
 from __future__ import annotations
 
-from pandas import DataFrame, read_csv # type: ignore
+import pandas as pd
 import shutil
 from typing import TYPE_CHECKING
 
 if TYPE_CHECKING:
-    from pandas import DataFrame
     from pathlib import Path
     from geopandas import GeoSeries
     from datetime import datetime
@@ -33,7 +32,7 @@ def __init__(self,  workdir: Path, id: str, nexus, params: dict = {}):
         """
 
         FormulatableCatchment.__init__(self=self, catchment_id=id, params=params, outflow=nexus)
-        Adjustable.__init__(self=self, df=DataFrame(params).rename(columns={'init': '0'}))
+        Adjustable.__init__(self=self, df=pd.DataFrame(params).rename(columns={'init': '0'}))
         #FIXME paramterize
         self._output_file = workdir/f'{self.id}.csv'
         self._workdir = workdir
@@ -86,15 +85,15 @@ def evaluation_range(self) -> tuple[datetime, datetime] | None:
         return self._eval_range
 
     @property
-    def output(self) -> DataFrame:
+    def output(self) -> pd.DataFrame:
         """
             The model output hydrograph for this catchment
             This re-reads the output file each call, as the output for given calibration catchment changes
             for each calibration iteration.  If it doesn't exist, should return None
         """
         try:
             #FIXME get the output variable from config
-            self._output = read_csv(self._output_file, usecols=["Time", self._output_var], parse_dates=['Time'], index_col='Time', dtype={self._output_var: 'float64'})
+            self._output = pd.read_csv(self._output_file, usecols=["Time", self._output_var], parse_dates=['Time'], index_col='Time', dtype={self._output_var: 'float64'})
             self._output.rename(columns={self._output_var:'sim_flow'}, inplace=True)
             #FIXME make sure units are correct here...
             #Assumes model catchment outputs are in m/hr, convert to m^3/s
@@ -113,7 +112,7 @@ def output(self, df):
         self._output = df
 
     @property
-    def observed(self) -> DataFrame:
+    def observed(self) -> pd.DataFrame:
         """
             The observed hydrograph for this catchment FIXME move output/observed to calibratable?
         """

python/ngen_cal/tests/conftest.py

@@ -175,7 +175,7 @@ def catchment(nexus, fabric, workdir, mocker) -> Generator[CalibrationCatchment,
     return catchment
 
 @pytest.fixture
-def catchment2(nexus, fabric, workdir) -> Generator[CalibrationCatchment, None, None]:
+def catchment2(nexus, fabric, workdir) -> CalibrationCatchment:
     """
         A hy_features catchment implementing the calibratable interface
         Doesn't mock output, can be used to test semantics of erronous output

python/ngen_cal/tests/test_calibration_catchment.py

@@ -1,41 +1,52 @@
-import pytest
+"""
+Test suite for calibratable_catchment
+"""
+
+from __future__ import annotations
+
 from typing import TYPE_CHECKING
 
+import pytest
+
 if TYPE_CHECKING:
     from ngen.cal.calibration_cathment import CalibrationCatchment
 
-"""
-    Test suite for calibratable_catchment
-"""
 
-@pytest.mark.usefixtures("catchment")
-def test_df(catchment: 'CalibrationCatchment') -> None:
+def test_df(catchment: CalibrationCatchment) -> None:
     """
-        Test the catchments proper construction of the parameter dataframe
+    Test the catchments proper construction of the parameter dataframe
     """
-    assert catchment.df.iloc[0]['param'] == 'some_param'
-    assert catchment.df.iloc[0]['0'] == 0.5
-    assert catchment.df.iloc[0]['min'] == 0.0
-    assert catchment.df.iloc[0]['max'] == 1.0
+    assert catchment.df.iloc[0]["param"] == "some_param"
+    assert catchment.df.iloc[0]["0"] == 0.5
+    assert catchment.df.iloc[0]["min"] == 0.0
+    assert catchment.df.iloc[0]["max"] == 1.0
 
-@pytest.mark.usefixtures("catchment2")
-def test_output(catchment2: 'CalibrationCatchment', monkeypatch) -> None:
+
+def test_output(
+    catchment2: CalibrationCatchment,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
     """
-        Test proper handling of non-existent output
+    Test proper handling of non-existent output
     """
     import pandas as pd
-    monkeypatch.setattr(pd, "read_csv", lambda *args, **kwargs: FileNotFoundError())
+
+    def file_not_found(*args, **kwargs):
+        raise FileNotFoundError
+
+    monkeypatch.setattr(pd, "read_csv", file_not_found)
     output = catchment2.output
-    assert output == None
+    assert output is None
+
 
-@pytest.mark.usefixtures("catchment")
-def test_observed(catchment: 'CalibrationCatchment') -> None:
+def test_observed(catchment: CalibrationCatchment) -> None:
     """
-        Test proper handling of non-existent output
+    Test proper handling of non-existent output
     """
     catchment.observed = None
     with pytest.raises(RuntimeError):
-        obs = catchment.observed
+        catchment.observed
+
 
-#TODO test catchment_set
-#TODO test evaluation_range?
+# TODO test catchment_set
+# TODO test evaluation_range?