1357 convert unittest to pytest

test/unit/extract/csv_test.py

@@ -1,7 +1,3 @@
-"""Unit tests for pudl.extract.csv module."""
-
-from unittest.mock import MagicMock, patch
-
 import pandas as pd
 import pytest
 
@@ -16,16 +12,16 @@
 
 
 class FakeExtractor(CsvExtractor):
-    def __init__(self):
+    def __init__(self, mocker):
         # TODO: Make these tests independent of the eia176 implementation
         self.METADATA = GenericMetadata("eia176")
-        super().__init__(ds=MagicMock())
+        super().__init__(ds=mocker.MagicMock())
 
 
 @pytest.fixture
-def extractor():
-    # Create an instance of the CsvExtractor class
-    return FakeExtractor()
+def extractor(mocker):
+    # Create an instance of the CsvExtractor class with mocker
+    return FakeExtractor(mocker)
 
 
 def test_source_filename_valid_partition(extractor):
@@ -45,8 +41,8 @@ def test_source_filename_multiple_selections(extractor):
         extractor.source_filename(PAGE, **multiple_selections)
 
 
-@patch("pudl.extract.csv.pd")
-def test_load_source(mock_pd, extractor):
+def test_load_source(mocker, extractor):
+    mock_pd = mocker.patch("pudl.extract.csv.pd")
     assert extractor.load_source(PAGE, **PARTITION) == mock_pd.read_csv.return_value
     extractor.ds.get_zipfile_resource.assert_called_once_with(DATASET, **PARTITION)
     zipfile = extractor.ds.get_zipfile_resource.return_value.__enter__.return_value
@@ -55,7 +51,7 @@ def test_load_source(mock_pd, extractor):
     mock_pd.read_csv.assert_called_once_with(file)
 
 
-def test_extract(extractor):
+def test_extract(mocker, extractor):
     # Create a sample of data we could expect from an EIA CSV
     company_field = "company"
     company_data = "Total of All Companies"
@@ -64,34 +60,30 @@ def test_extract(extractor):
 
     # TODO: Once FakeExtractor is independent of eia176, mock out populating _column_map for PARTITION_SELECTION;
     #  Also include negative tests, i.e., for partition selections not in the _column_map
-    with (
-        patch.object(CsvExtractor, "load_source", return_value=df),
-        patch.object(
-            # Testing the rename
-            GenericMetadata,
-            "get_column_map",
-            return_value={"company_rename": company_field},
-        ),
-        patch.object(
-            # Transposing the df here to get the orientation we expect get_page_cols to return
-            CsvExtractor,
-            "get_page_cols",
-            return_value=df.T.index,
-        ),
-    ):
-        res = extractor.extract(**PARTITION)
+    mocker.patch.object(CsvExtractor, "load_source", return_value=df)
+    # Testing the rename
+    mocker.patch.object(
+        GenericMetadata,
+        "get_column_map",
+        return_value={"company_rename": company_field},
+    )
+    # Transposing the df here to get the orientation we expect get_page_cols to return
+    mocker.patch.object(
+        CsvExtractor,
+        "get_page_cols",
+        return_value=df.T.index,
+    )
+    res = extractor.extract(**PARTITION)
     assert len(res) == 1  # Assert only one page extracted
     assert list(res.keys()) == [PAGE]  # Assert it is named correctly
     assert (
         res[PAGE][company_field][0] == company_data
     )  # Assert that column correctly renamed and data is there.
 
 
-@patch.object(FakeExtractor, "METADATA")
-def test_validate_exact_columns(mock_metadata, extractor):
+def test_validate_exact_columns(mocker, extractor):
     # Mock the partition selection and page columns
-    # mock_metadata._get_partition_selection.return_value = "partition1"
-    extractor.get_page_cols = MagicMock(return_value={"col1", "col2"})
+    extractor.get_page_cols = mocker.MagicMock(return_value={"col1", "col2"})
 
     # Create a DataFrame with the exact expected columns
     df = pd.DataFrame(columns=["col1", "col2"])
@@ -100,11 +92,9 @@ def test_validate_exact_columns(mock_metadata, extractor):
     extractor.validate(df, "page1", partition="partition1")
 
 
-@patch.object(FakeExtractor, "METADATA")
-def test_validate_extra_columns(mock_metadata, extractor):
+def test_validate_extra_columns(mocker, extractor):
     # Mock the partition selection and page columns
-    mock_metadata._get_partition_selection.return_value = "partition1"
-    extractor.get_page_cols = MagicMock(return_value={"col1", "col2"})
+    extractor.get_page_cols = mocker.MagicMock(return_value={"col1", "col2"})
 
     # Create a DataFrame with extra columns
     df = pd.DataFrame(columns=["col1", "col2", "col3"])
@@ -114,11 +104,9 @@ def test_validate_extra_columns(mock_metadata, extractor):
         extractor.validate(df, "page1", partition="partition1")
 
 
-@patch.object(FakeExtractor, "METADATA")
-def test_validate_missing_columns(mock_metadata, extractor):
+def test_validate_missing_columns(mocker, extractor):
     # Mock the partition selection and page columns
-    mock_metadata._get_partition_selection.return_value = "partition1"
-    extractor.get_page_cols = MagicMock(return_value={"col1", "col2"})
+    extractor.get_page_cols = mocker.MagicMock(return_value={"col1", "col2"})
 
     # Create a DataFrame with missing columns
     df = pd.DataFrame(columns=["col1"])
@@ -130,11 +118,9 @@ def test_validate_missing_columns(mock_metadata, extractor):
         extractor.validate(df, "page1", partition="partition1")
 
 
-@patch.object(FakeExtractor, "METADATA")
-def test_validate_extra_and_missing_columns(mock_metadata, extractor):
+def test_validate_extra_and_missing_columns(mocker, extractor):
     # Mock the partition selection and page columns
-    mock_metadata._get_partition_selection.return_value = "partition1"
-    extractor.get_page_cols = MagicMock(return_value={"col1", "col2"})
+    extractor.get_page_cols = mocker.MagicMock(return_value={"col1", "col2"})
 
     # Create a DataFrame with both extra and missing columns
     df = pd.DataFrame(columns=["col1", "col3"])

test/unit/extract/excel_test.py

@@ -1,35 +1,42 @@
 """Unit tests for pudl.extract.excel module."""
 
-import unittest
-from unittest import mock as mock
-
 import pandas as pd
+import pytest
 
 from pudl.extract import excel
 
 
-class TestMetadata(unittest.TestCase):
+class TestMetadata:
     """Tests basic operation of the excel.Metadata object."""
 
+    @pytest.fixture(autouse=True)
     def setUp(self):
-        """Cosntructs test metadata instance for testing."""
+        """Constructs test metadata instance for testing."""
         self._metadata = excel.ExcelMetadata("test")
 
     def test_basics(self):
         """Test that basic API method return expected results."""
-        self.assertEqual("test", self._metadata.get_dataset_name())
-        self.assertListEqual(
-            ["books", "boxes", "shoes"], self._metadata.get_all_pages()
-        )
-        self.assertListEqual(
-            ["author", "pages", "title"], self._metadata.get_all_columns("books")
-        )
-        self.assertDictEqual(
-            {"book_title": "title", "name": "author", "pages": "pages"},
-            self._metadata.get_column_map("books", year=2010),
-        )
-        self.assertEqual(10, self._metadata.get_skiprows("boxes", year=2011))
-        self.assertEqual(1, self._metadata.get_sheet_name("boxes", year=2011))
+        assert self._metadata.get_dataset_name() == "test"
+        assert self._metadata.get_all_pages() == ["books", "boxes", "shoes"]
+        assert self._metadata.get_all_columns("books") == ["author", "pages", "title"]
+        assert self._metadata.get_column_map("books", year=2010) == {
+            "book_title": "title",
+            "name": "author",
+            "pages": "pages",
+        }
+        assert self._metadata.get_skiprows("boxes", year=2011) == 10
+        assert self._metadata.get_sheet_name("boxes", year=2011) == 1
+
+    def test_metadata_methods(self):
+        """Test various metadata methods."""
+        assert self._metadata.get_all_columns("books") == ["author", "pages", "title"]
+        assert self._metadata.get_column_map("books", year=2010) == {
+            "book_title": "title",
+            "name": "author",
+            "pages": "pages",
+        }
+        assert self._metadata.get_skiprows("boxes", year=2011) == 10
+        assert self._metadata.get_sheet_name("boxes", year=2011) == 1
 
 
 class FakeExtractor(excel.ExcelExtractor):
@@ -77,11 +84,10 @@ def _fake_data_frames(page_name, **kwargs):
     return fake_data[page_name]
 
 
-class TestExtractor(unittest.TestCase):
+class TestExtractor:
     """Test operation of the excel.Extractor class."""
 
-    @staticmethod
-    def test_extract():
+    def test_extract(self):
         extractor = FakeExtractor()
         res = extractor.extract(year=[2010, 2011])
         expected_books = {
@@ -103,7 +109,7 @@ def test_extract():
     # def test_resulting_dataframes(self):
     #     """Checks that pages across years are merged and columns are translated."""
     #     dfs = FakeExtractor().extract([2010, 2011], testing=True)
-    #     self.assertEqual(set(['books', 'boxes']), set(dfs.keys()))
+    #     assert set(['books', 'boxes']) == set(dfs.keys())
     #     pd.testing.assert_frame_equal(
     #         pd.DataFrame(data={
     #             'author': ['Laozi', 'Benjamin Hoff'],
@@ -118,5 +124,5 @@ def test_extract():
     #         }),
     #         dfs['boxes'])
 
-    # TODO([email protected]): need to figure out how to test process_$x methods.
-    # TODO([email protected]): we should test that empty columns are properly added.
+    # TODO: need to figure out how to test process_$x methods.
+    # TODO: we should test that empty columns are properly added.

test/unit/extract/phmsagas_test.py

@@ -1,5 +1,3 @@
-from unittest.mock import MagicMock, patch
-
 import pandas as pd
 import pytest
 
@@ -8,20 +6,20 @@
 
 
 class FakeExtractor(Extractor):
-    def __init__(self):
+    def __init__(self, mocker):
         self.METADATA = ExcelMetadata("phmsagas")
-        super().__init__(ds=MagicMock())
-        self._metadata = MagicMock()
+        super().__init__(ds=mocker.Mock())
+        self._metadata = mocker.Mock()
 
 
 @pytest.fixture
-def extractor():
+def extractor(mocker):
     # Create an instance of the CsvExtractor class
-    return FakeExtractor()
+    return FakeExtractor(mocker)
 
 
-@patch("pudl.extract.phmsagas.logger")
-def test_process_renamed_drop_columns(mock_logger, extractor):
+def test_process_renamed_drop_columns(mocker, extractor):
+    mock_logger = mocker.patch("pudl.extract.phmsagas.logger")
     # Mock metadata methods
     extractor._metadata.get_form.return_value = "gas_transmission_gathering"
     extractor._metadata.get_all_columns.return_value = ["col1", "col2"]
@@ -38,8 +36,8 @@ def test_process_renamed_drop_columns(mock_logger, extractor):
     mock_logger.info.assert_called_once()
 
 
-@patch("pudl.extract.phmsagas.logger")
-def test_process_renamed_keep_columns(mock_logger, extractor):
+def test_process_renamed_keep_columns(mocker, extractor):
+    mock_logger = mocker.patch("pudl.extract.phmsagas.logger")
     # Mock metadata methods
     extractor._metadata.get_form.return_value = "gas_transmission_gathering"
     extractor._metadata.get_all_columns.return_value = ["col1", "col2"]
@@ -56,8 +54,8 @@ def test_process_renamed_keep_columns(mock_logger, extractor):
     mock_logger.info.assert_not_called()
 
 
-@patch("pudl.extract.phmsagas.logger")
-def test_process_renamed_drop_unnamed_columns(mock_logger, extractor):
+def test_process_renamed_drop_unnamed_columns(mocker, extractor):
+    mock_logger = mocker.patch("pudl.extract.phmsagas.logger")
     # Mock metadata methods
     extractor._metadata.get_form.return_value = "some_form"
     extractor._metadata.get_all_columns.return_value = ["col1", "col2"]
@@ -74,8 +72,8 @@ def test_process_renamed_drop_unnamed_columns(mock_logger, extractor):
     mock_logger.warning.assert_not_called()
 
 
-@patch("pudl.extract.phmsagas.logger")
-def test_process_renamed_warn_unnamed_columns(mock_logger, extractor):
+def test_process_renamed_warn_unnamed_columns(mocker, extractor):
+    mock_logger = mocker.patch("pudl.extract.phmsagas.logger")
     # Mock metadata methods
     extractor._metadata.get_form.return_value = "some_form"
     extractor._metadata.get_all_columns.return_value = ["col1", "col2"]

test/unit/output/ferc1_test.py

@@ -19,7 +19,6 @@
 """
 
 import logging
-import unittest
 from io import StringIO
 
 import networkx as nx
@@ -37,10 +36,8 @@
 logger = logging.getLogger(__name__)
 
 
-class TestForestSetup(unittest.TestCase):
-    def setUp(self):
-        # this is where you add nodes you want to use
-        pass
+class TestForestSetup:
+    """Base class for forest testing."""
 
     def _exploded_calcs_from_edges(self, edges: list[tuple[NodeId, NodeId]]):
         records = []
@@ -90,7 +87,9 @@ def build_forest_and_annotated_tags(
 
 
 class TestPrunnedNode(TestForestSetup):
-    def setUp(self):
+    @pytest.fixture(autouse=True)
+    def setup_nodes(self):
+        """Setup nodes for testing."""
         self.root = NodeId(
             table_name="table_1",
             xbrl_factoid="reported_1",
@@ -121,6 +120,7 @@ def setUp(self):
         )
 
     def test_pruned_nodes(self):
+        """Test pruned nodes."""
         edges = [(self.root, self.root_child), (self.root_other, self.root_other_child)]
         tags = pd.DataFrame(columns=list(NodeId._fields)).convert_dtypes()
         forest = XbrlCalculationForestFerc1(
@@ -133,7 +133,11 @@ def test_pruned_nodes(self):
 
 
 class TestTagPropagation(TestForestSetup):
-    def setUp(self):
+    """Test tag propagation functionality."""
+
+    @pytest.fixture(autouse=True)
+    def setup_nodes(self):
+        """Setup nodes for testing."""
         self.parent = NodeId(
             table_name="table_1",
             xbrl_factoid="reported_1",
@@ -185,6 +189,7 @@ def setUp(self):
         )
 
     def test_leafward_prop_undecided_children(self):
+        """Test leadward propagation with undecided children."""
         edges = [(self.parent, self.child1), (self.parent, self.child2)]
         tags = pd.DataFrame([self.parent, self.child1, self.child2]).assign(
             in_rate_base=["yes", pd.NA, pd.NA]
@@ -369,6 +374,7 @@ def test_annotated_forest_propagates_rootward_two_layers_plus_corrections(self):
 
 
 def test_get_core_ferc1_asset_description():
+    """Test core FERC1 asset description extraction."""
     valid_core_ferc1_asset_name = "core_ferc1__yearly_income_statements_sched114"
     valid_core_ferc1_asset_name_result = get_core_ferc1_asset_description(
         valid_core_ferc1_asset_name