Update mfp tests to use fixtures

tests/test_mfp_to_yaml.py

@@ -7,34 +7,50 @@
 from virtualship.expedition.schedule import Schedule
 from virtualship.utils import mfp_to_yaml
 
-# Sample correct MFP data
-VALID_MFP_DATA = pd.DataFrame(
-    {
-        "Station Type": ["A", "B", "C"],
-        "Name": ["Station1", "Station2", "Station3"],
-        "Latitude": [30, 31, 32],
-        "Longitude": [-44, -45, -46],
-        "Instrument": ["CTD, DRIFTER", "ARGO_FLOAT", "XBT, CTD, DRIFTER"],
-    }
-)
-
-# Missing required columns
-MISSING_HEADERS_DATA = pd.DataFrame(
-    {"Station Type": ["A"], "Name": ["Station1"], "Latitude": [10.5]}
-)
-
-# Extra unexpected columns
-EXTRA_HEADERS_DATA = VALID_MFP_DATA.copy()
-EXTRA_HEADERS_DATA["Unexpected Column"] = ["Extra1", "Extra2", "Extra3"]
-
-
-@patch("pandas.read_excel", return_value=VALID_MFP_DATA)
-def test_mfp_to_yaml_success(mock_read_excel, tmp_path):
+
+def valid_mfp_data():
+    return pd.DataFrame(
+        {
+            "Station Type": ["A", "B", "C"],
+            "Name": ["Station1", "Station2", "Station3"],
+            "Latitude": [30, 31, 32],
+            "Longitude": [-44, -45, -46],
+            "Instrument": ["CTD, DRIFTER", "ARGO_FLOAT", "XBT, CTD, DRIFTER"],
+        }
+    )
+
+
+@pytest.fixture
+def valid_mfp_file(tmp_path):
+    path = tmp_path / "file.xlsx"
+    valid_mfp_data().to_excel(path, index=False)
+    yield path
+
+
+@pytest.fixture
+def missing_columns_mfp_file(tmp_path):
+    path = tmp_path / "file.xlsx"
+    valid_mfp_data().drop(columns=["Longitude", "Instrument"]).to_excel(
+        path, index=False
+    )
+    yield path
+
+
+@pytest.fixture
+def unexpected_header_mfp_file(tmp_path):
+    path = tmp_path / "file.xlsx"
+    df = valid_mfp_data()
+    df["Unexpected Column"] = ["Extra1", "Extra2", "Extra3"]
+    df.to_excel(path, index=False)
+    yield path
+
+
+def test_mfp_to_yaml_success(valid_mfp_file, tmp_path):
     """Test that mfp_to_yaml correctly processes a valid MFP Excel file."""
     yaml_output_path = tmp_path / "schedule.yaml"
 
     # Run function (No need to mock open() for YAML, real file is created)
-    mfp_to_yaml("mock_file.xlsx", yaml_output_path)
+    mfp_to_yaml(valid_mfp_file, yaml_output_path)
 
     # Ensure the YAML file was written
     assert yaml_output_path.exists()
@@ -52,26 +68,24 @@ def test_mfp_to_yaml_success(mock_read_excel, tmp_path):
     ]
 
 
-@patch("pandas.read_excel", return_value=MISSING_HEADERS_DATA)
-def test_mfp_to_yaml_missing_headers(mock_read_excel, tmp_path):
+def test_mfp_to_yaml_missing_headers(missing_columns_mfp_file, tmp_path):
     """Test that mfp_to_yaml raises an error when required columns are missing."""
     yaml_output_path = tmp_path / "schedule.yaml"
 
     with pytest.raises(
         ValueError,
         match="Error: Missing column 'Instrument'. Have you added this column after exporting from MFP?",
     ):
-        mfp_to_yaml("mock_file.xlsx", yaml_output_path)
+        mfp_to_yaml(missing_columns_mfp_file, yaml_output_path)
 
 
-@patch("pandas.read_excel", return_value=EXTRA_HEADERS_DATA)
 @patch("builtins.print")  # Capture printed warnings
-def test_mfp_to_yaml_extra_headers(mock_print, mock_read_excel, tmp_path):
+def test_mfp_to_yaml_extra_headers(mock_print, unexpected_header_mfp_file, tmp_path):
     """Test that mfp_to_yaml prints a warning when extra columns are found."""
     yaml_output_path = tmp_path / "schedule.yaml"
 
     # Run function
-    mfp_to_yaml("mock_file.xlsx", yaml_output_path)
+    mfp_to_yaml(unexpected_header_mfp_file, yaml_output_path)
 
     # Ensure a warning message was printed
     mock_print.assert_any_call(
@@ -82,13 +96,12 @@ def test_mfp_to_yaml_extra_headers(mock_print, mock_read_excel, tmp_path):
     )
 
 
-@patch("pandas.read_excel", return_value=VALID_MFP_DATA)
-def test_mfp_to_yaml_instrument_conversion(mock_read_excel, tmp_path):
+def test_mfp_to_yaml_instrument_conversion(valid_mfp_file, tmp_path):
     """Test that instruments are correctly converted into InstrumentType enums."""
     yaml_output_path = tmp_path / "schedule.yaml"
 
     # Run function
-    mfp_to_yaml("mock_file.xlsx", yaml_output_path)
+    mfp_to_yaml(valid_mfp_file, yaml_output_path)
 
     # Load the generated YAML
     data = Schedule.from_yaml(yaml_output_path)