From 1500153db81f7b0a1c1dc751e80a6c4d87435c8d Mon Sep 17 00:00:00 2001 From: Alex Corrie Date: Sun, 15 Mar 2026 01:31:15 +0000 Subject: [PATCH 1/3] build(deps)!: drop <3.11, add 3.12, 3.13; bump pandas/numpy - drops pytz (unused), clear out old compat variants in lock - bump pytest BREAKING CHANGE: 3.11+ required --- .github/workflows/ci.yaml | 10 +- pyproject.toml | 13 +- uv.lock | 1229 +++++++++---------------------------- 3 files changed, 310 insertions(+), 942 deletions(-) diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml index 418f78f..1e0d508 100644 --- a/.github/workflows/ci.yaml +++ b/.github/workflows/ci.yaml @@ -13,7 +13,7 @@ permissions: env: - DEFAULT_PYTHON_VERSION: '3.11' + DEFAULT_PYTHON_VERSION: '3.13' jobs: @@ -23,7 +23,7 @@ jobs: strategy: fail-fast: false matrix: - python-version: ${{ github.ref == 'refs/heads/main' && fromJson('["3.8", "3.9", "3.10", "3.11"]') || fromJson('["default"]') }} + python-version: ${{ github.ref == 'refs/heads/main' && fromJson('["3.11", "3.12", "3.13"]') || fromJson('["default"]') }} os: ${{ github.ref == 'refs/heads/main' && fromJson('["ubuntu-latest", "macos-latest", "windows-latest"]') || fromJson('["ubuntu-latest"]') }} runs-on: ${{ matrix.os }} @@ -37,11 +37,9 @@ jobs: steps: - uses: actions/checkout@v5 - - uses: actions/setup-python@v6 - with: - python-version: ${{ matrix.python-version == 'default' && env.DEFAULT_PYTHON_VERSION || matrix.python-version }} - - uses: corriander/gha/uv/test@main + env: + UV_PYTHON: ${{ matrix.python-version == 'default' && env.DEFAULT_PYTHON_VERSION || matrix.python-version }} release: name: 🚀 Release diff --git a/pyproject.toml b/pyproject.toml index 1921f29..4066055 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -7,23 +7,22 @@ authors = [ ] license = {text = "MIT"} readme = "README.md" -requires-python = ">=3.8,<3.13" +requires-python = ">=3.11" dependencies = [ "platformdirs>=2.6.2", "pygsheets>=2.0.5,<3", - "pandas>=1.3.5", - "numpy>=1.21.1", + "pandas>=2.0", + "numpy>=1.26", "xlrd>=2.0,<3", - "pytz>=2022.6", "openpyxl>=3.0.10,<4", ] [dependency-groups] dev = [ - "pytest>=7.1.2,<8", - "pytest-mock>=3.8.2,<4", + "pytest>=8", + "pytest-mock>=3.8.2", "coverage>=7", - "ddt>=1.6.0,<2", + "ddt>=1.6.0", "pytest-cov>=4", ] diff --git a/uv.lock b/uv.lock index 2846e91..6ee699d 100644 --- a/uv.lock +++ b/uv.lock @@ -1,13 +1,16 @@ version = 1 revision = 3 -requires-python = ">=3.8, <3.13" +requires-python = ">=3.11" resolution-markers = [ - "python_full_version >= '3.11' and sys_platform == 'win32'", - "python_full_version >= '3.11' and sys_platform == 'emscripten'", - "python_full_version >= '3.11' and sys_platform != 'emscripten' and sys_platform != 'win32'", - "python_full_version == '3.10.*'", - "python_full_version == '3.9.*'", - "python_full_version < '3.9'", + "python_full_version >= '3.14' and sys_platform == 'win32'", + "python_full_version >= '3.14' and sys_platform == 'emscripten'", + "python_full_version >= '3.14' and 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}, - { name = "pytest", specifier = ">=7.1.2,<8" }, + { name = "ddt", specifier = ">=1.6.0" }, + { name = "pytest", specifier = ">=8" }, { name = "pytest-cov", specifier = ">=4" }, - { name = "pytest-mock", specifier = ">=3.8.2,<4" }, + { name = "pytest-mock", specifier = ">=3.8.2" }, ] [[package]] From 45ced59c11e0ac5e6c240ff8f81bd4fbf39e8cb2 Mon Sep 17 00:00:00 2001 From: Alex Corrie Date: Sun, 15 Mar 2026 01:55:51 +0000 Subject: [PATCH 2/3] test: modernise test suite for Python 3.11+ Drop ddt in favour of pytest.mark.parametrize, remove all unittest.TestCase inheritance, replace unittest.mock with pytest-mock fixtures, and convert self.assert* to plain assert. pytest upgraded from 7 to 9. --- pyproject.toml | 1 - uv.lock | 11 - vdd/coda/tests/test_io.py | 165 ++++----- vdd/coda/tests/test_models.py | 482 +++++++++++++------------- vdd/common/tests/test_io.py | 89 ++--- vdd/requirements/tests/test_io.py | 104 +++--- vdd/requirements/tests/test_models.py | 132 +++---- 7 files changed, 436 insertions(+), 548 deletions(-) diff --git a/pyproject.toml b/pyproject.toml index 4066055..fdcf212 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -22,7 +22,6 @@ dev = [ "pytest>=8", "pytest-mock>=3.8.2", "coverage>=7", - "ddt>=1.6.0", "pytest-cov>=4", ] diff --git a/uv.lock b/uv.lock index 6ee699d..e42c2ee 100644 --- a/uv.lock +++ b/uv.lock @@ -337,15 +337,6 @@ wheels = [ { url = "https://files.pythonhosted.org/packages/bc/58/6b3d24e6b9bc474a2dcdee65dfd1f008867015408a271562e4b690561a4d/cryptography-46.0.5-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:8456928655f856c6e1533ff59d5be76578a7157224dbd9ce6872f25055ab9ab7", size = 3407605, upload-time = "2026-02-10T19:18:29.233Z" }, ] -[[package]] -name = "ddt" -version = "1.7.2" -source = { registry = "https://pypi.org/simple" } -sdist = { url = "https://files.pythonhosted.org/packages/51/d4/bdea45c5c1f1f0ae55844d841101b00905c9863ee1004da37d911253abb2/ddt-1.7.2.tar.gz", hash = "sha256:d215d6b083963013c4a19b1e4dcd6a96e80e43ab77519597a6acfcf2e9a3e04b", size = 13673, upload-time = "2024-02-26T01:36:33.737Z" } -wheels = [ - { url = "https://files.pythonhosted.org/packages/61/7c/38d1aec205833096eddefcbb3492fbb2c886e74174c72bc160da9522b2f0/ddt-1.7.2-py2.py3-none-any.whl", hash = "sha256:6adcfaf9785f0a36f9e73a89b91e412de9ef8649e289b750e3683bc79d5e2354", size = 7065, upload-time = "2024-02-26T01:36:32.45Z" }, -] - [[package]] name = "et-xmlfile" version = "2.0.0" @@ -931,7 +922,6 @@ dependencies = [ [package.dev-dependencies] dev = [ { name = "coverage" }, - { name = "ddt" }, { name = "pytest" }, { name = "pytest-cov" }, { name = "pytest-mock" }, @@ -950,7 +940,6 @@ requires-dist = [ [package.metadata.requires-dev] dev = [ { name = "coverage", specifier = ">=7" }, - { name = "ddt", specifier = ">=1.6.0" }, { name = "pytest", specifier = ">=8" }, { name = "pytest-cov", specifier = ">=4" }, { name = "pytest-mock", specifier = ">=3.8.2" }, diff --git a/vdd/coda/tests/test_io.py b/vdd/coda/tests/test_io.py index 9ad7582..60f04df 100644 --- a/vdd/coda/tests/test_io.py +++ b/vdd/coda/tests/test_io.py @@ -1,9 +1,7 @@ -import unittest import os -import sys -from unittest import mock import numpy as np +import pytest try: import pandas as pd import xlrd @@ -16,22 +14,16 @@ from . import DATA_DIR -class TestExcelParser(unittest.TestCase): +@pytest.mark.skipif(not deps_present, + reason="`pandas` package required for tests.") +class TestExcelParser: """Test case for importing a coda model definition from Excel.""" - @classmethod - def setUpClass(cls): - cls.path = path = os.path.join(DATA_DIR, 'demo_model.xlsx') - cls.parser = io.ExcelParser(path) - - def __getattr__(self, attr): - # Helper to support both Python 2 and 3 - if attr == 'assertCountEqual' and sys.version_info[0] == 2: - return getattr(self, 'assertItemsEqual') - - def setUp(self): - if not deps_present: - self.skipTest("`pandas` package required for tests.") + @pytest.fixture(autouse=True, scope='class') + def setup_class(self): + path = os.path.join(DATA_DIR, 'demo_model.xlsx') + self.__class__.parser = io.ExcelParser(path) + self.__class__.path = path def test_cdf(self): """This should return a pandas dataframe. @@ -40,9 +32,9 @@ def test_cdf(self): """ df = self.parser.cdf - self.assertIsInstance(df, pd.DataFrame) - self.assertEqual(df.index.shape, (3,)) # 2 chars - self.assertEqual(len(df.columns), 3) # name, min, max + assert isinstance(df, pd.DataFrame) + assert df.index.shape == (3,) # 2 chars + assert len(df.columns) == 3 # name, min, max def test_df(self): """This should return a pandas dataframe. @@ -51,90 +43,84 @@ def test_df(self): """ df = self.parser.df - self.assertIsInstance(df, pd.DataFrame) - self.assertEqual(df.index.shape, (3,)) # 3 reqts + assert isinstance(df, pd.DataFrame) + assert df.index.shape == (3,) # 3 reqts def test_get_requirements(self): """Should return requisite information for requirements.""" retval = self.parser.get_requirements() - self.assertCountEqual(retval, [('Stiffness', 0.2), - ('Friction', 0.3), - ('Weight', 0.5)]) + assert sorted(retval) == sorted([ + ('Stiffness', 0.2), + ('Friction', 0.3), + ('Weight', 0.5), + ]) def test_get_characteristics(self): retval = self.parser.get_characteristics() - self.assertCountEqual(retval[:2], [('Tyre Diameter', 24, 29), - ('Tyre Width', 11, 18)]) + assert sorted(retval[:2]) == sorted([ + ('Tyre Diameter', 24, 29), + ('Tyre Width', 11, 18), + ]) - # Check the dummpy which contains NaNs. - self.assertEqual(retval[2][0], 'Dummy Characteristic') - self.assertTrue(np.isnan(retval[2][1])) - self.assertTrue(np.isnan(retval[2][2])) + # Check the dummy which contains NaNs. + assert retval[2][0] == 'Dummy Characteristic' + assert np.isnan(retval[2][1]) + assert np.isnan(retval[2][2]) def test_get_relationships(self): - """Three relationships are defined in the source spreadsheet. - """ + """Three relationships are defined in the source spreadsheet.""" # NOTE: The Weight-Tyre Width relationship is artificial for - # testing optimial relationships. + # testing optimal relationships. retval = self.parser.get_relationships() - self.assertCountEqual( - retval, - [('Stiffness', 'Tyre Diameter', 'min', 0.9, 29), - ('Friction', 'Tyre Diameter', 'max', 0.3, 12), - ('Weight', 'Tyre Width', 'opt', 0.1, 14, 1)] - ) + assert sorted(retval) == sorted([ + ('Stiffness', 'Tyre Diameter', 'min', 0.9, 29), + ('Friction', 'Tyre Diameter', 'max', 0.3, 12), + ('Weight', 'Tyre Width', 'opt', 0.1, 14, 1), + ]) -class TestCompactExcelParser(unittest.TestCase): - """Functionally similar, but diff. source format to io.ExcelParser. - """ +@pytest.mark.skipif(not deps_present, + reason="`pandas` package required for tests.") +class TestCompactExcelParser: + """Functionally similar, but diff. source format to io.ExcelParser.""" - @classmethod - def setUpClass(cls): - cls.regular = io.ExcelParser( + @pytest.fixture(autouse=True, scope='class') + def setup_class(self): + self.__class__.regular = io.ExcelParser( os.path.join(DATA_DIR, 'demo_model.xlsx') ) - cls.compact = io.CompactExcelParser( + self.__class__.compact = io.CompactExcelParser( os.path.join(DATA_DIR, 'demo_model_compact.xlsx') ) - def setUp(self): - if not deps_present: - self.skipTest("`pandas` package required for tests.") - def test_get_requirements(self): - self.assertEqual(self.regular.get_requirements(), - self.compact.get_requirements()) + assert self.regular.get_requirements() == self.compact.get_requirements() def test_get_characteristics(self): l1 = self.regular.get_characteristics() l2 = self.compact.get_characteristics() - self.assertEqual(l1[:2], l2[:2]) + assert l1[:2] == l2[:2] # Now check the last characteristic spec, as it contains NaNs. for i in 1, 2: - self.assertTrue( - np.isnan(l1[-1][i]) and np.isnan(l1[-1][i]) - ) - self.assertEqual(l1[-1][0], l2[-1][0]) + assert np.isnan(l1[-1][i]) and np.isnan(l1[-1][i]) + assert l1[-1][0] == l2[-1][0] def test_get_relationships(self): - self.maxDiff = None l1 = self.regular.get_relationships() l2 = self.compact.get_relationships() for t1, t2 in zip(l1, l2): - self.assertEqual(t1[:3], t2[:3]) - self.assertAlmostEqual(t1[3], - [0.1, 0.3, 0.9][len(t2[3])-1]) - self.assertAlmostEqual(t1[4], t2[4]) + assert t1[:3] == t2[:3] + assert t1[3] == pytest.approx([0.1, 0.3, 0.9][len(t2[3])-1]) + assert t1[4] == pytest.approx(t2[4]) -@mock.patch.object(io.GSheetCODA, 'df', - new_callable=mock.PropertyMock) -class TestGSheetCODA(unittest.TestCase): +@pytest.mark.skipif(not deps_present, + reason="`pandas` package required for tests.") +class TestGSheetCODA: """Provides an interface to a compact form model in Google Sheets. The adapter behaves similarly to CompactExcelParser with scope for @@ -146,11 +132,10 @@ class TestGSheetCODA(unittest.TestCase): (specifics of the format it returns, etc.). """ - @classmethod - def setUpClass(cls): - demo_model_path = os.path.join(DATA_DIR, - 'demo_model_compact.xlsx') - cls.compact_excel_parser = io.CompactExcelParser( + @pytest.fixture(autouse=True, scope='class') + def setup_class(self): + demo_model_path = os.path.join(DATA_DIR, 'demo_model_compact.xlsx') + self.__class__.compact_excel_parser = io.CompactExcelParser( demo_model_path ) @@ -162,16 +147,19 @@ def setUpClass(cls): column if not column.startswith('Unnamed') else '' for column in df.columns ] - cls.reference_df = df + self.__class__.reference_df = df - def setUp(self): - self.mock_facade = mock.MagicMock( - spec_set=common.io.GSheetsFacade - ) + @pytest.fixture(autouse=True) + def setup_sut(self, mocker): + """Create the subject under test with a mock facade and a patched df property.""" + self.mock_facade = mocker.MagicMock(spec_set=common.io.GSheetsFacade) self.sut = io.GSheetCODA('dummy workbook name') self.sut._facade = self.mock_facade + self.mock_df_property = mocker.patch.object( + io.GSheetCODA, 'df', new_callable=mocker.PropertyMock + ) - def test_get_characteristics(self, mock_df_property): + def test_get_characteristics(self): """Expect a list of 3-tuples describing characteristics. The 3-tuples contain the name, and the min and max values of @@ -180,7 +168,7 @@ def test_get_characteristics(self, mock_df_property): There are three characteristics in the source, with the third having no min/max values (NaN). """ - mock_df_property.return_value = self.reference_df + self.mock_df_property.return_value = self.reference_df actual = self.sut.get_characteristics() expected = self.compact_excel_parser.get_characteristics() @@ -188,18 +176,18 @@ def test_get_characteristics(self, mock_df_property): np.testing.assert_array_equal(np.array(actual), np.array(expected)) - def test_get_requirements(self, mock_df_property): + def test_get_requirements(self): """Expect a list of 2-tuples describing requirements. The 2-tuples contain each requirement and its weighting/scoring. """ - mock_df_property.return_value = self.reference_df + self.mock_df_property.return_value = self.reference_df actual = self.sut.get_requirements() expected = self.compact_excel_parser.get_requirements() - self.assertEqual(actual, expected) + assert actual == expected - def test_get_relationships(self, mock_df_property): + def test_get_relationships(self): """Expect a list of 5/6-tuples describing relationships. The tuples take one of two forms depending on the type of @@ -210,8 +198,7 @@ def test_get_relationships(self, mock_df_property): 2. Optimum: Correlation strength, relationship type, optimum point, tolerance. """ - self.maxDiff = None - mock_df_property.return_value = self.reference_df + self.mock_df_property.return_value = self.reference_df actual = self.sut.get_relationships() expected = self.compact_excel_parser.get_relationships() @@ -220,15 +207,11 @@ def test_get_relationships(self, mock_df_property): np.array(expected, dtype=object) ) - def test_is_valid(self, mock_df_property): + def test_is_valid(self): """Check the source sheet is valid. Note that only relationship_type fields are checks for symbol correctness currently. """ - mock_df_property.return_value = self.reference_df - self.assertTrue(self.sut.is_valid()) - - -if __name__ == '__main__': - unittest.main() + self.mock_df_property.return_value = self.reference_df + assert self.sut.is_valid() diff --git a/vdd/coda/tests/test_models.py b/vdd/coda/tests/test_models.py index 636d7f1..3cc3151 100644 --- a/vdd/coda/tests/test_models.py +++ b/vdd/coda/tests/test_models.py @@ -1,26 +1,23 @@ import os -import unittest -from unittest import mock import numpy as np - -from ddt import data, unpack, ddt +import pytest from .. import models from .. import io from . import DATA_DIR -@ddt -class TestCODA(unittest.TestCase): +class TestCODA: - def setUp(self): + @pytest.fixture(autouse=True) + def setup(self, mocker): self.inst = inst = models.CODA() characteristics = [] self.values = values = 1, 10, 2, 7.5, 0.3 for x in values: - char = mock.Mock() + char = mocker.Mock() char.value = x characteristics.append(char) @@ -29,7 +26,7 @@ def setUp(self): requirements = [] self.weights = weights = 0.2, 0.1, 0.4, 0.3 for wt in weights: - reqt = mock.Mock() + reqt = mocker.Mock() reqt.weight = wt requirements.append(reqt) @@ -52,71 +49,69 @@ class MockRelationship(object): def __call__(self, x): return self._merit_preset - for i in range(correlation.shape[0]): + for i in range(correlation.shape[0]): for j in range(correlation.shape[1]): relationship = MockRelationship() - relationship.correlation = correlation[i,j] - relationship._merit_preset = self.merit[i,j] - inst.matrix[i,j] = relationship + relationship.correlation = correlation[i, j] + relationship._merit_preset = self.merit[i, j] + inst.matrix[i, j] = relationship # ---------------------------------------------------------------- # Test properties # ---------------------------------------------------------------- def test_matrix__unset(self): - """Matrix should match shape and contain CODANull by default. - """ + """Matrix should match shape and contain CODANull by default.""" temp_inst = models.CODA() - self.assertEqual(temp_inst.matrix.shape, (0, 0)) - - self.assertEqual(self.inst.matrix.shape, (4, 5)) + assert temp_inst.matrix.shape == (0, 0) + assert self.inst.matrix.shape == (4, 5) temp_inst._requirements += (object(),) - self.assertEqual(temp_inst.matrix.shape, (1, 0)) + assert temp_inst.matrix.shape == (1, 0) for i, j in zip(*map(range, temp_inst.matrix.shape)): - self.assertIsInstance(temp_inst.matrix[i,j], models.CODANull) + assert isinstance(temp_inst.matrix[i, j], models.CODANull) def test_characteristics__default(self): """Should be an empty tuple by default.""" temp_inst = models.CODA() - self.assertIsInstance(temp_inst.characteristics, tuple) - self.assertEqual(len(temp_inst.characteristics), 0.0) - self.assertEqual(len(self.inst.requirements), 4) + assert isinstance(temp_inst.characteristics, tuple) + assert len(temp_inst.characteristics) == 0 + assert len(self.inst.requirements) == 4 def test_correlation(self): """Property converts correlation values in array to a matrix. Each design relationship models a correlation between a - requirement and a characteristic parameter. This should + requirement and a characteristic parameter. This should therefore be the same dimensions as the overall coda model, i.e. (n, m) where n is the number of requirements, and m the number of characteristics. """ - self.assertIsInstance(self.inst.correlation, np.ndarray) - self.assertEqual(self.inst.correlation.ndim, 2) - self.assertEqual(self.inst.correlation.shape, self.inst.shape) - self.assertTrue((self.inst.correlation==self.correlation).all()) - - @mock.patch.object(models.CODA, 'satisfaction', - new_callable=mock.PropertyMock) - def test_merit(self, patch): + assert isinstance(self.inst.correlation, np.ndarray) + assert self.inst.correlation.ndim == 2 + assert self.inst.correlation.shape == self.inst.shape + assert (self.inst.correlation == self.correlation).all() + + def test_merit(self, mocker): """Sum total of weighted requirement satisfaction.""" + patch = mocker.patch.object( + models.CODA, 'satisfaction', new_callable=mocker.PropertyMock + ) patch.return_value = np.arange(5) - self.assertAlmostEqual(self.inst.merit, 10) + assert self.inst.merit == pytest.approx(10) def test_parameter_value(self): """A row vector containing characteristic parameter values. Characteristics are considered to be columns in the underlying - coda matrix, so characterstic parameter values should reflect + coda matrix, so characteristic parameter values should reflect this to be unambiguous. """ - self.assertIsInstance(self.inst.parameter_value, np.ndarray) - self.assertEqual(self.inst.parameter_value.shape, - (1, self.inst.shape[1])) - self.assertTrue((self.inst.parameter_value==self.values).all()) + assert isinstance(self.inst.parameter_value, np.ndarray) + assert self.inst.parameter_value.shape == (1, self.inst.shape[1]) + assert (self.inst.parameter_value == self.values).all() - @data( + @pytest.mark.parametrize("value, exception", [ (np.array([2.0, 10, 2, 7.5, 0.3]), None), (np.array([[2.0, 10, 2, 7.5, 0.3]]), None), (np.array([[2.0, 10, 2, 7.5, 0.3]]).T, None), @@ -124,35 +119,32 @@ def test_parameter_value(self): (tuple([2.0, 10, 2, 7.5, 0.3]), None), (set([2.0, 10, 2, 7.5, 0.3]), ValueError), ([2.0, 10, 2, 7.5], ValueError), - ) - @unpack + ]) def test_parameter_value__set(self, value, exception): - self.assertEqual(self.inst.parameter_value[0,0], 1.0) + assert self.inst.parameter_value[0, 0] == 1.0 if exception is not None: - self.assertRaises(exception, setattr, self.inst, - 'parameter_value', value) + with pytest.raises(exception): + setattr(self.inst, 'parameter_value', value) else: setattr(self.inst, 'parameter_value', value) - self.assertEqual(self.inst.parameter_value[0,0], 2.0) + assert self.inst.parameter_value[0, 0] == 2.0 def test_requirements__default(self): """Should be an empty tuple by default.""" temp_inst = models.CODA() - self.assertIsInstance(temp_inst.characteristics, tuple) - self.assertEqual(len(temp_inst.characteristics), 0.0) - self.assertEqual(len(self.inst.requirements), 4) - - @mock.patch.object(models.CODA, '_merit') - @mock.patch.object(models.CODA, 'correlation', - new_callable=mock.PropertyMock) - def test_satisfaction(self, *mocks): + assert isinstance(temp_inst.characteristics, tuple) + assert len(temp_inst.characteristics) == 0 + assert len(self.inst.requirements) == 4 + + def test_satisfaction(self, mocker): """Weighted requirement satisfactions. This is the merit of each characteristic parameter value for each requirement, weighted by correlation factors. - .. math: - \frac{\sum_{j=1}^{M} cf .* \eta}{{scf}_i} + .. math:: + + \\frac{\\sum_{j=1}^{M} cf .* \\eta}{{scf}_i} Where @@ -164,10 +156,13 @@ def test_satisfaction(self, *mocks): n = number of requirements m = number of characteristics """ - correlation, merit = mocks + mock_merit = mocker.patch.object(models.CODA, '_merit') + mock_correlation = mocker.patch.object( + models.CODA, 'correlation', new_callable=mocker.PropertyMock + ) - a = np.random.rand(3,2) - correlation.return_value = merit.return_value = a + a = np.random.rand(3, 2) + mock_correlation.return_value = mock_merit.return_value = a # numerator num = np.multiply(a, a).sum(axis=1, keepdims=True) @@ -177,10 +172,9 @@ def test_satisfaction(self, *mocks): expected = np.divide(num, den) - self.assertIsInstance(self.inst.satisfaction, np.ndarray) - self.assertEqual(self.inst.satisfaction.shape, (3, 1)) - np.testing.assert_array_almost_equal(self.inst.satisfaction, - expected) + assert isinstance(self.inst.satisfaction, np.ndarray) + assert self.inst.satisfaction.shape == (3, 1) + np.testing.assert_array_almost_equal(self.inst.satisfaction, expected) def test_shape(self): """Reflects the number of characteristics & requirements. @@ -188,7 +182,7 @@ def test_shape(self): A CODA model involves n requirements and m characteristics, modelled as an (n, m) array/matrix. """ - self.assertEqual(self.inst.shape, (4, 5)) + assert self.inst.shape == (4, 5) def test_weight(self): """A column vector containing requirement weightings. @@ -197,18 +191,17 @@ def test_weight(self): coda matrix, so requirement weights should reflect this to be unambiguous. """ - self.assertIsInstance(self.inst.weight, np.ndarray) - self.assertEqual(self.inst.weight.shape, - (self.inst.shape[0], 1)) + assert isinstance(self.inst.weight, np.ndarray) + assert self.inst.weight.shape == (self.inst.shape[0], 1) # Note we must transpose the weight column vector to compare # it properly with the simple input weights tuple because of # numpy broadcasting producing a boolean matrix. - self.assertTrue((self.inst.weight.T==self.weights).all()) + assert (self.inst.weight.T == self.weights).all() # ---------------------------------------------------------------- # Test methods # ---------------------------------------------------------------- - @data( + @pytest.mark.parametrize("reqts", [ #[('Irrelevant requirement', 0.0, ValueError),], # not enforced [('Unimportant requirement', 0.1, None),], [('Important requirement', 0.9, None),], @@ -217,7 +210,7 @@ def test_weight(self): [('Sole requirement', 1.0, None),], [('Sole requirement', 1.0, None), ('Another requirement', 0.1, RuntimeError)], - ) + ]) def test_add_requirement__prenormalised(self, reqts): inst = models.CODA() i = 0 @@ -225,34 +218,30 @@ def test_add_requirement__prenormalised(self, reqts): if exception is None: inst.add_requirement(name, normwt, normalise=False) i += 1 - self.assertEqual(len(inst.requirements), i) - self.assertEqual(inst.requirements[i-1].name, name) - self.assertEqual(inst.requirements[i-1].weight, - normwt) + assert len(inst.requirements) == i + assert inst.requirements[i-1].name == name + assert inst.requirements[i-1].weight == normwt else: - self.assertRaises(exception, inst.add_requirement, - name, normwt, normalise=False) + with pytest.raises(exception): + inst.add_requirement(name, normwt, normalise=False) - @data( + @pytest.mark.parametrize("weights", [ (1.0, 1.0), (1.0, 1.0, 1.0, 1.0), (0.1, 0.2, 0.3, 0.4) - ) + ]) def test_add_requirement__unnormalised(self, weights): inst = models.CODA() for i, wt in enumerate(weights): inst.add_requirement('Blah'+str(i), wt, normalise=True) - self.assertAlmostEqual( - sum([r.weight for r in inst.requirements]), - 1.0 - ) + assert sum([r.weight for r in inst.requirements]) == pytest.approx(1.0) - @data( + @pytest.mark.parametrize("chars", [ [('Characteristic', 0.0, 1.0, None, None),], [('Characteristic', 0.0, 1.0, 1.0, None), ('Another characteristic', -1.0, 11.0, None, None),], - ) + ]) def test_add_characteristic(self, chars): inst = models.CODA() i = 0 @@ -260,25 +249,23 @@ def test_add_characteristic(self, chars): if exception is None: inst.add_characteristic(name, (llim, ulim), value) i += 1 - self.assertEqual(len(inst.characteristics), i) - self.assertEqual(inst.characteristics[i-1].name, name) - self.assertEqual(inst.characteristics[i-1].limits, - (llim, ulim)) + assert len(inst.characteristics) == i + assert inst.characteristics[i-1].name == name + assert inst.characteristics[i-1].limits == (llim, ulim) # Value not set in these test data. - #self.assertEqual(inst.characteristics[i-1].value, - # value) + #assert inst.characteristics[i-1].value == value else: - self.assertRaises(exception, inst.add_characteristic, - name, normwt) + with pytest.raises(exception): + inst.add_characteristic(name, (llim, ulim), value) - @data( + @pytest.mark.parametrize("rels", [ [(0, 0, 'max', 0.1, 1.0, None, None),], [(0, 0, 'min', 0.1, 1.0, None, None),], [(0, 0, 'opt', 0.1, 1.0, 1.0, None),], [(0, 5, 'opt', 0.1, 1.0, 1.0, KeyError),], [(0, 0, 'max', 0.1, 1.0, None, None), (0, 1, 'max', 0.1, 1.0, None, None),], - ) + ]) def test_add_relationship(self, rels): inst = self.inst for (r, c, type_, corr, tv, tol, exception) in rels: @@ -295,52 +282,45 @@ def test_add_relationship(self, rels): if exception is None: inst.add_relationship(*args) else: - self.assertRaises(exception, inst.add_relationship, - *args) + with pytest.raises(exception): + inst.add_relationship(*args) continue - self.assertIsInstance(inst.matrix[r,c], cls) - self.assertEqual(inst.matrix[r,c].correlation, corr) + assert isinstance(inst.matrix[r, c], cls) + assert inst.matrix[r, c].correlation == corr - @data( + @pytest.mark.parametrize("rlkup, clkup, exception", [ ['Requirement0', 0, None], [0, 'Characteristic0', None], - ['requirement0', 0, KeyError], # Case-sensitive for now. - ['Requirement2', 0, KeyError], # Not present. + ['requirement0', 0, KeyError], # Case-sensitive for now. + ['Requirement2', 0, KeyError], # Not present. ['Requirement0', 'Characteristic0', None], ['Requirement1', 'Characteristic0', None], [1, 'Characteristic0', None], - ) - @unpack - def test_add_relationship__by_name(self, rlkup, clkup, exception): - """Given two requirements, 1 characteristic - add relations. - """ + ]) + def test_add_relationship__by_name(self, rlkup, clkup, exception, mocker): + """Given two requirements, 1 characteristic - add relations.""" inst = models.CODA() - mock1 = mock.Mock() + mock1 = mocker.Mock() mock1.name = 'Requirement0' - mock3 = mock.Mock() + mock3 = mocker.Mock() mock3.name = 'Requirement1' - inst._requirements = (mock1,mock3) + inst._requirements = (mock1, mock3) - mock2 = mock.Mock() + mock2 = mocker.Mock() mock2.name = 'Characteristic0' inst._characteristics = (mock2,) if exception is None: inst.add_relationship(rlkup, clkup, 'max', 1.0, 1.0) r = rlkup if isinstance(rlkup, int) else int(rlkup[-1]) - self.assertIsInstance(inst.matrix[r,0], models.CODAMaximise) + assert isinstance(inst.matrix[r, 0], models.CODAMaximise) else: - self.assertRaises(exception, inst.add_relationship, - rlkup, clkup, 'max', 1.0, 1.0) - - @mock.patch.object(models.CODA, 'add_relationship') - @mock.patch.object(models.CODA, 'add_characteristic') - @mock.patch.object(models.CODA, 'add_requirement') - def test_read_excel(self, mock_add_requirement, - mock_add_characteristic, - mock_add_relationship): + with pytest.raises(exception): + inst.add_relationship(rlkup, clkup, 'max', 1.0, 1.0) + + def test_read_excel(self, mocker): """Constructor adds elements in turn from the parser. The parser provides three methods: @@ -360,6 +340,16 @@ def test_read_excel(self, mock_add_requirement, values for these get methods are passed to the add methods in the correct fashion. """ + mock_add_requirement = mocker.patch.object( + models.CODA, 'add_requirement' + ) + mock_add_characteristic = mocker.patch.object( + models.CODA, 'add_characteristic' + ) + mock_add_relationship = mocker.patch.object( + models.CODA, 'add_relationship' + ) + dummy_records = { 'requirements': [ io.CODASheet.ReqRecord('Requirement 1', 0.33), @@ -375,7 +365,7 @@ def test_read_excel(self, mock_add_requirement, 'Requirement 1', 'Characteristic 1', 'min', - '---', # TODO: Remove redundant information + '---', # TODO: Remove redundant information 3 ), io.CODASheet.OptRelRecord( @@ -396,11 +386,11 @@ def test_read_excel(self, mock_add_requirement, ] } - stub_parser = mock.MagicMock(spec_set=io.CompactExcelParser) + stub_parser = mocker.MagicMock(spec_set=io.CompactExcelParser) for s in 'requirements', 'characteristics', 'relationships': method = getattr(stub_parser, 'get_{}'.format(s)) method.return_value = dummy_records[s] - mock_parser_class = mock.Mock() + mock_parser_class = mocker.Mock() mock_parser_class.return_value = stub_parser sut = models.CODA.read_excel('/dummy/path', @@ -408,21 +398,21 @@ def test_read_excel(self, mock_add_requirement, mock_parser_class.assert_called_once_with('/dummy/path') mock_add_requirement.assert_has_calls([ - mock.call('Requirement 1', 0.33), - mock.call('Requirement 2', 0.5), - mock.call('Requirement 3', 0.17), + mocker.call('Requirement 1', 0.33), + mocker.call('Requirement 2', 0.5), + mocker.call('Requirement 3', 0.17), ]) mock_add_characteristic.assert_has_calls([ - mock.call('Characteristic 1', (1, 5)), - mock.call('Characteristic 2', (10, 20)), + mocker.call('Characteristic 1', (1, 5)), + mocker.call('Characteristic 2', (10, 20)), ]) mock_add_relationship.assert_has_calls([ - mock.call('Requirement 1', 'Characteristic 1', 'min', - '---', 3), - mock.call('Requirement 2', 'Characteristic 1', 'opt', - 'ooo', 13, 1), - mock.call('Requirement 3', 'Characteristic 2', 'max', - '+++', 3), + mocker.call('Requirement 1', 'Characteristic 1', 'min', + '---', 3), + mocker.call('Requirement 2', 'Characteristic 1', 'opt', + 'ooo', 13, 1), + mocker.call('Requirement 3', 'Characteristic 2', 'max', + '+++', 3), ]) def test__merit(self): @@ -438,38 +428,34 @@ def test__merit(self): "Internal" method because raw merit values are not considered particularly useful on their own at this point. """ - self.assertIsInstance(self.inst._merit(), np.ndarray) - self.assertEqual(self.inst._merit().ndim, 2) - self.assertEqual(self.inst._merit().shape, self.inst.shape) - self.assertTrue((self.inst._merit()==self.merit).all()) + assert isinstance(self.inst._merit(), np.ndarray) + assert self.inst._merit().ndim == 2 + assert self.inst._merit().shape == self.inst.shape + assert (self.inst._merit() == self.merit).all() -class TestCODACaseStudy1(unittest.TestCase): +class TestCODACaseStudy1: """Case study of a bicycle wheel design based on ref 1.""" - def setUp(self): - wheel = self.wheel = models.CODA() - self._setup_requirements() - self._setup_characteristics() - self._setup_relationships() + @pytest.fixture(autouse=True) + def setup(self): + self.wheel = wheel = models.CODA() + self._setup_requirements(wheel) + self._setup_characteristics(wheel) + self._setup_relationships(wheel) - def _setup_requirements(self): - wheel = self.wheel + def _setup_requirements(self, wheel): for name in ('Stiffness', 'Friction', 'Weight', 'Manufacturability', 'Repairability'): wheel.add_requirement(name, 0.2) - def _setup_characteristics(self): - wheel = self.wheel + def _setup_characteristics(self, wheel): wheel.add_characteristic('Tyre Diameter', (24, 29), 24) wheel.add_characteristic('Tyre Width', (11, 18), 13) wheel.add_characteristic('Spoke Thickness', (2.8, 5), 4.3) - wheel.add_characteristic('Use of Composites', (0.05, 0.8), - 0.2) - - def _setup_relationships(self): - wheel = self.wheel + wheel.add_characteristic('Use of Composites', (0.05, 0.8), 0.2) + def _setup_relationships(self, wheel): reqt = 'Stiffness' wheel.add_relationship(reqt, 0, 'min', 'strong', 29) wheel.add_relationship(reqt, 1, 'max', 'moderate', 12) @@ -507,7 +493,7 @@ def _setup_relationships(self): 'strong', 0.25) def test_merit(self): - self.assertAlmostEqual(self.wheel.merit, .5788, places=4) + assert self.wheel.merit == pytest.approx(0.5788, abs=1e-4) def test_sum_of_correlations(self): """Sum of correlation factors for all requirements.""" @@ -517,12 +503,8 @@ def test_sum_of_correlations(self): ) def test_read_excel(self): - try: - import pandas - import xlrd - except ImportError: - self.skipTest("`pandas` and `xlrd` required for " - "spreadsheet parsing") + pytest.importorskip('pandas', reason="`pandas` required for spreadsheet parsing") + pytest.importorskip('xlrd', reason="`xlrd` required for spreadsheet parsing") model = models.CODA.read_excel( os.path.join(DATA_DIR, 'demo_model_casestudy1.xlsx') ) @@ -530,13 +512,13 @@ def test_read_excel(self): for char, ref in zip(model.characteristics, self.wheel.characteristics): char.value = ref.value - self.assertEqual(self.wheel.merit, model.merit) + assert self.wheel.merit == model.merit -@ddt -class TestCODACharacteristic(unittest.TestCase): +class TestCODACharacteristic: - def setUp(self): + @pytest.fixture(autouse=True) + def setup(self): class CODACharacteristic(models.CODACharacteristic): def __init__(self): pass @@ -551,46 +533,48 @@ def test___init____omit_value(self): inst = models.CODACharacteristic('Name') # This might want to be None? Requires everything supporting # that as an input though. - self.assertRaises(AttributeError, getattr, inst, 'value') + with pytest.raises(AttributeError): + _ = inst.value - @data( + @pytest.mark.parametrize("value, exception", [ (-0.01, ValueError), (0.0, None), (0.5, None), (1.0, None), (1.01, ValueError), - ) - @unpack + ]) def test_value__set_with_default_limits(self, value, exception): if exception is not None: - self.assertRaises(exception, setattr, self.inst, 'value', - value) - + with pytest.raises(exception): + setattr(self.inst, 'value', value) else: self.inst.value = value - self.assertEqual(self.inst.value, value) + assert self.inst.value == value def test_limits__get__default(self): - self.assertEqual(self.inst.limits, self.inst._default_limits) + assert self.inst.limits == self.inst._default_limits - @data((0.0, 1.0), [0.0, 1.0], (None, None), (0, None), (None, 1)) + @pytest.mark.parametrize("value", [ + (0.0, 1.0), [0.0, 1.0], (None, None), (0, None), (None, 1) + ]) def test_limits__set__valid(self, value): self.inst.limits = value - self.assertEqual(self.inst.limits, tuple(value)) + assert self.inst.limits == tuple(value) -@ddt -class TestCODARequirement(unittest.TestCase): +class TestCODARequirement: - def setUp(self): + @pytest.fixture(autouse=True) + def setup(self): class CODARequirement(models.CODARequirement): def __init__(self): pass self.inst = CODARequirement() - @data((-0.01, False), (0.0, True), (0.5, True), (1.0, True), - (1.1, False)) - @unpack + @pytest.mark.parametrize("wt, valid", [ + (-0.01, False), (0.0, True), (0.5, True), (1.0, True), + (1.1, False) + ]) def test_weight__set(self, wt, valid): # Prototypes used context to allow weights to be provided in a # non-normalised form and this property would handle the @@ -598,17 +582,17 @@ def test_weight__set(self, wt, valid): # requirements. This functionality isn't implemented here, but # might still be useful. if not valid: - self.assertRaises(ValueError, setattr, self.inst, - 'weight', wt) + with pytest.raises(ValueError): + setattr(self.inst, 'weight', wt) else: self.inst.weight = wt - self.assertEqual(self.inst.weight, wt) + assert self.inst.weight == wt -@ddt -class TestCODARelationship(unittest.TestCase): +class TestCODARelationship: - def setUp(self): + @pytest.fixture(autouse=True) + def setup(self): class Concrete(models.CODARelationship): def __init__(self): pass @@ -619,109 +603,107 @@ def __call__(self, x): self.cls = Concrete self.inst = Concrete() - @data([0.0, 0.0, True], - [0.1, 0.1, True], - [0.3, 0.3, True], - [0.9, 0.9, True], - [1.0, 0.1, True], - [0.25, None, False], - [-0.1, None, False], - [0, 0.0, True], - [1, 0.1, True], - [3, 0.3, True], - [9, 0.9, True], - ['none', 0.0, True], - [None, 0.0, True], - ['weak', 0.1, True], - ['moderate', 0.3, True], - ['medium', 0.3, True], - ['strong', 0.9, True], - ['---', 0.9, True], - ['+++', 0.9, True], - ['ooo', 0.9, True], - ['--', 0.3, True], - ['++', 0.3, True], - ['oo', 0.3, True], - ['o', 0.1, True], - ['o', 0.1, True], - ['o', 0.1, True], - ) - @unpack + @pytest.mark.parametrize("value, internal_value, valid", [ + [0.0, 0.0, True], + [0.1, 0.1, True], + [0.3, 0.3, True], + [0.9, 0.9, True], + [1.0, 0.1, True], + [0.25, None, False], + [-0.1, None, False], + [0, 0.0, True], + [1, 0.1, True], + [3, 0.3, True], + [9, 0.9, True], + ['none', 0.0, True], + [None, 0.0, True], + ['weak', 0.1, True], + ['moderate', 0.3, True], + ['medium', 0.3, True], + ['strong', 0.9, True], + ['---', 0.9, True], + ['+++', 0.9, True], + ['ooo', 0.9, True], + ['--', 0.3, True], + ['++', 0.3, True], + ['oo', 0.3, True], + ['o', 0.1, True], + ['o', 0.1, True], + ['o', 0.1, True], + ]) def test_correlation(self, value, internal_value, valid): """Correlation value must be one of a restricted set.""" # TODO: It might be more flexible to enforce this further up - # for different scaling systems. Could also be done with - # a mixin implementation implementation - self.assertRaises(AttributeError, getattr, self.inst, - 'correlation') + # for different scaling systems. Could also be done with + # a mixin implementation + with pytest.raises(AttributeError): + _ = self.inst.correlation if valid: self.inst.correlation = value - self.assertEqual(self.inst.correlation, internal_value) + assert self.inst.correlation == internal_value else: - self.assertRaises(ValueError, setattr, self.inst, - 'correlation', value) + with pytest.raises(ValueError): + setattr(self.inst, 'correlation', value) def test_target(self): """Target value may be anything, but check it's settable.""" - self.assertRaises(AttributeError, getattr, self.inst, - 'target') + with pytest.raises(AttributeError): + _ = self.inst.target self.inst.target = 0.0 - self.assertEqual(self.inst.target, 0.0) + assert self.inst.target == 0.0 -class TestCODANull(unittest.TestCase): +class TestCODANull: def test___init__(self): """Takes no arguments, has a correlation and merit of zero.""" null = models.CODANull() - self.assertEqual(null.correlation, 0.0) - self.assertIs(null.target, None) - self.assertEqual(null(None), 0.0) + assert null.correlation == 0.0 + assert null.target is None + assert null(None) == 0.0 def test__attributes_not_settable(self): null = models.CODANull() - self.assertRaises(TypeError, setattr, null, 'correlation', 1) - self.assertRaises(TypeError, setattr, null, 'target', 1) + with pytest.raises(TypeError): + null.correlation = 1 + with pytest.raises(TypeError): + null.target = 1 -class TestCODAMaximise(unittest.TestCase): +class TestCODAMaximise: # TODO: compare function over range. def test_merit(self): inst = models.CODAMaximise(target=1.0, correlation=None) - self.assertAlmostEqual(inst(1.0), 0.5) - self.assertLess(inst(0.1), 0.5) - self.assertGreater(inst(2.0), 0.5) + assert inst(1.0) == pytest.approx(0.5) + assert inst(0.1) < 0.5 + assert inst(2.0) > 0.5 -class TestCODAMinimise(unittest.TestCase): +class TestCODAMinimise: # TODO: compare function over range. def test_merit(self): inst = models.CODAMinimise(target=1.0, correlation=None) - self.assertAlmostEqual(inst(1.0), 0.5) - self.assertGreater(inst(0.1), 0.5) - self.assertLess(inst(2.0), 0.5) + assert inst(1.0) == pytest.approx(0.5) + assert inst(0.1) > 0.5 + assert inst(2.0) < 0.5 -class TestCODAOptimise(unittest.TestCase): +class TestCODAOptimise: # TODO: compare function over range. def test_merit(self): inst = models.CODAOptimise(target=1.0, correlation=None, tolerance=0.2) - self.assertAlmostEqual(inst(0.8), 0.5) - self.assertAlmostEqual(inst(1.2), 0.5) - self.assertAlmostEqual(inst(1.0), 1.0) - self.assertGreater(inst(1.1), 0.5) - self.assertGreater(inst(0.9), 0.5) - self.assertLess(inst(2.0), 0.5) - self.assertLess(inst(0.0), 0.5) - - -if __name__ == '__main__': - unittest.main() + assert inst(0.8) == pytest.approx(0.5) + assert inst(1.2) == pytest.approx(0.5) + assert inst(1.0) == pytest.approx(1.0) + assert inst(1.1) > 0.5 + assert inst(0.9) > 0.5 + assert inst(2.0) < 0.5 + assert inst(0.0) < 0.5 diff --git a/vdd/common/tests/test_io.py b/vdd/common/tests/test_io.py index 1f72e46..fc7de34 100644 --- a/vdd/common/tests/test_io.py +++ b/vdd/common/tests/test_io.py @@ -1,75 +1,66 @@ -import unittest -from unittest import mock - +import pytest import pygsheets import pandas as pd from .. import io -@mock.patch.object(io.GSheetsFacade, '_sheet', - new_callable=mock.PropertyMock) -class TestGSheetsFacade(unittest.TestCase): +class TestGSheetsFacade: - def setup_mock_sheet(self, mock_property): - mock_property.return_value = mock_sheet = mock.MagicMock( - spec=io.WorksheetAdapter + @pytest.fixture(autouse=True) + def setup(self, mocker): + self.sut = io.GSheetsFacade('dummy workbook name') + self.mock_sheet_property = mocker.patch.object( + io.GSheetsFacade, '_sheet', new_callable=mocker.PropertyMock ) + mock_sheet = mocker.MagicMock(spec=io.WorksheetAdapter) # Ensure we can call the methods we actually use in the facade # because the adapter passes through attribute lookups to the # underlying implementation. mock doesn't know this so will # complain (rightfully). Using spec (rather than spec_set) # allows this and balances between strict and useful. - mock_sheet.set_dataframe = mock.Mock() - return mock_sheet + mock_sheet.set_dataframe = mocker.Mock() + self.mock_sheet_property.return_value = mock_sheet + self.mock_sheet = mock_sheet - def setUp(self): - self.sut = io.GSheetsFacade('dummy workbook name') - - def test_get_rows(self, mock_sheet_property): + def test_get_rows(self): """Utilises our adaptation of 'Worksheet.get_all_values'.""" - mock_sheet = self.setup_mock_sheet(mock_sheet_property) - retval = self.sut.get_rows() - mock_sheet.get_all_values.assert_called_once_with() - self.assertIs(retval, mock_sheet.get_all_values.return_value) + self.mock_sheet.get_all_values.assert_called_once_with() + assert retval is self.mock_sheet.get_all_values.return_value - def test_write_dataframe(self, mock_sheet_property): + def test_write_dataframe(self, mocker): """Utilises the pygsheets method 'Worksheet.set_dataframe'""" - mock_sheet = self.setup_mock_sheet(mock_sheet_property) - - dummy_df = mock.MagicMock(spec_set=pd.DataFrame) + dummy_df = mocker.MagicMock(spec_set=pd.DataFrame) retval = self.sut.write_dataframe(dummy_df, 'A1') - mock_sheet.set_dataframe.assert_called_once_with( - dummy_df, - start='A1', - copy_index=True, - copy_head=True, - fit=True + self.mock_sheet.set_dataframe.assert_called_once_with( + dummy_df, + start='A1', + copy_index=True, + copy_head=True, + fit=True ) - self.assertIs(retval, None) + assert retval is None -class TestWorksheetAdapter(unittest.TestCase): +class TestWorksheetAdapter: """Adapter for external (pygsheets) worksheet model.""" - def setUp(self): - self.mock_sheet = mock.MagicMock( + @pytest.fixture(autouse=True) + def setup(self, mocker): + self.mock_sheet = mocker.MagicMock( spec_set=pygsheets.worksheet.Worksheet ) self.sut = io.WorksheetAdapter(self.mock_sheet) def test_attribute_passthrough(self): """Attributes not explicitly overriden are passed through.""" - mock_sheet = self.mock_sheet - - adapter = self.sut - adapter.refresh(update_grid=True) + self.sut.refresh(update_grid=True) - mock_sheet.refresh.assert_called_once_with(update_grid=True) + self.mock_sheet.refresh.assert_called_once_with(update_grid=True) def test_get_all_values__binwm_source_structure(self): """Method papers over some deficiencies in the wrapped method. @@ -94,8 +85,7 @@ def test_get_all_values__binwm_source_structure(self): ['Requirement 3', '', '', '', '', '', '', ''] ] - adapter = self.sut - actual = adapter.get_all_values() + actual = self.sut.get_all_values() expected = [ ['Requirements', 'Requirement 1', @@ -106,7 +96,7 @@ def test_get_all_values__binwm_source_structure(self): ['Requirement 3', '', '', ''] ] - self.assertEqual(actual, expected) + assert actual == expected def test_get_all_values__coda_source_structure(self): """Method papers over some deficiencies in the wrapped method. @@ -118,14 +108,13 @@ def test_get_all_values__coda_source_structure(self): coda model. """ self.mock_sheet.get_all_values.return_value = [ - [ '', 'B1', 'C1', '', 'E1', '', ''], - ['A2', 'B2', 'C2', 'D2', 'E2', 'F2', ''], - ['A3', 'B3', 'C3', '', 'E3', 'F3', ''], - ['A4', 'B4', 'C4', 'D4', 'E4', '', ''], + [ '', 'B1', 'C1', '', 'E1', '', ''], + ['A2', 'B2', 'C2', 'D2', 'E2', 'F2', ''], + ['A3', 'B3', 'C3', '', 'E3', 'F3', ''], + ['A4', 'B4', 'C4', 'D4', 'E4', '', ''], ] - adapter = self.sut - actual = adapter.get_all_values() + actual = self.sut.get_all_values() expected = [ [ '', 'B1', 'C1', '', 'E1', ''], ['A2', 'B2', 'C2', 'D2', 'E2', 'F2'], @@ -133,8 +122,4 @@ def test_get_all_values__coda_source_structure(self): ['A4', 'B4', 'C4', 'D4', 'E4', ''], ] - self.assertEqual(actual, expected) - - -if __name__ == '__main__': - unittest.main() + assert actual == expected diff --git a/vdd/requirements/tests/test_io.py b/vdd/requirements/tests/test_io.py index cf92ef1..70871b1 100644 --- a/vdd/requirements/tests/test_io.py +++ b/vdd/requirements/tests/test_io.py @@ -1,40 +1,31 @@ import json import os -import unittest -from unittest import mock import numpy as np import pandas as pd import pygsheets -from ddt import ddt, data, unpack - +import pytest from ... import common from .. import io from . import DATA_DIR, FIXTURES_DIR -class TestBinWMSource(unittest.TestCase): - """Test case uses a concrete impl to test shared behaviour.""" - pass - +class TestGSheetBinWM: -@ddt -class TestGSheetBinWM(unittest.TestCase): - - def get_mock_facade(self, fixture): - mock_facade = mock.Mock(spec_set=common.io.GSheetsFacade) + def get_mock_facade(self, fixture, mocker): + mock_facade = mocker.Mock(spec_set=common.io.GSheetsFacade) fixture_path = os.path.join(FIXTURES_DIR, fixture) with open(fixture_path) as fhandle: mock_facade.get_rows.return_value = json.load(fhandle) return mock_facade - def get_subject_under_test(self, fixture): + def get_subject_under_test(self, fixture, mocker): sut = io.GSheetBinWM('dummy_workbook_name') - sut._facade = self.get_mock_facade(fixture) + sut._facade = self.get_mock_facade(fixture, mocker) return sut - @data( + @pytest.mark.parametrize("fixture, expected", [ ('minimal_example_incomplete_triu.json', False), ('minimal_example_incomplete_tril.json', True), ('minimal_example_populated.json', True), @@ -46,15 +37,13 @@ def get_subject_under_test(self, fixture): ('minimal_example_duplicate_requirement.json', False), ('minimal_example_misaligned_requirements.json', False), ('minimal_example_score_column.json', True), - ) - @unpack - def test_is_valid(self, fixture, expected): - """Method returns a boolean indicating source is valid. - """ - sut = self.get_subject_under_test(fixture) - self.assertIs(sut.is_valid(), expected) + ]) + def test_is_valid(self, fixture, expected, mocker): + """Method returns a boolean indicating source is valid.""" + sut = self.get_subject_under_test(fixture, mocker) + assert sut.is_valid() is expected - def test_get_label(self): + def test_get_label(self, mocker): """Check the custom label is picked up properly. This is critical functionality for easy copy pasting in @@ -63,50 +52,47 @@ def test_get_label(self): missing cell in the dataframe visualisation. """ sut = self.get_subject_under_test( - 'minimal_example_custom_label.json' + 'minimal_example_custom_label.json', mocker ) actual = sut.get_label() expected = 'Custom Label' - self.assertEqual(actual, expected) + assert actual == expected - @data( + @pytest.mark.parametrize("fixture", [ 'minimal_example_incomplete_tril.json', 'minimal_example_populated.json', 'minimal_example_zeros.json', 'minimal_example_blank.json', 'minimal_example_different_cell_a1.json', - ) - def test_get_requirements__valid(self, fixture): + ]) + def test_get_requirements__valid(self, fixture, mocker): """A list of requirements is obtainable from valid sources.""" expected = ['Requirement {}'.format(x) for x in range(1, 4)] - sut = self.get_subject_under_test(fixture) - self.assertEqual(sut.get_requirements(), expected) + sut = self.get_subject_under_test(fixture, mocker) + assert sut.get_requirements() == expected - @data( + @pytest.mark.parametrize("fixture", [ 'minimal_example_incomplete_triu.json', 'minimal_example_extra_column.json', 'minimal_example_extra_row.json', 'minimal_example_tril_ones.json' - ) - def test_get_requirements__invalid(self, fixture): + ]) + def test_get_requirements__invalid(self, fixture, mocker): """The requirements list can't be read; raise an exception.""" - sut = self.get_subject_under_test(fixture) - self.assertRaises( - io.GSheetBinWM.InvalidSource, - sut.get_requirements - ) + sut = self.get_subject_under_test(fixture, mocker) + with pytest.raises(io.GSheetBinWM.InvalidSource): + sut.get_requirements() - @data( + @pytest.mark.parametrize("fixture, expected_triu", [ ('minimal_example_incomplete_tril.json', (0, 1, 1)), ('minimal_example_populated.json', (0, 1, 1)), ('minimal_example_zeros.json', (0, 0, 0)), - ('minimal_example_blank.json', (0, 0 ,0)), + ('minimal_example_blank.json', (0, 0, 0)), ('minimal_example_different_cell_a1.json', (0, 1, 1)) - ) - @unpack - def test_get_value_matrix__valid(self, fixture, expected_triu): + ]) + def test_get_value_matrix__valid(self, fixture, expected_triu, mocker): """The binary matrix is obtained from valid sources.""" a, b, c = expected_triu expected = np.array([ @@ -115,41 +101,39 @@ def test_get_value_matrix__valid(self, fixture, expected_triu): [0, 0, 0] ]) - sut = self.get_subject_under_test(fixture) + sut = self.get_subject_under_test(fixture, mocker) np.testing.assert_array_almost_equal(sut.get_value_matrix(), expected) - @data( + @pytest.mark.parametrize("fixture", [ 'minimal_example_incomplete_triu.json', 'minimal_example_extra_column.json', 'minimal_example_extra_row.json', 'minimal_example_tril_ones.json' - ) - def test_get_value_matrix__invalid(self, fixture): + ]) + def test_get_value_matrix__invalid(self, fixture, mocker): """The binary matrix can't be read; raise an exception.""" - sut = self.get_subject_under_test(fixture) - self.assertRaises( - io.GSheetBinWM.InvalidSource, - sut.get_value_matrix - ) + sut = self.get_subject_under_test(fixture, mocker) + with pytest.raises(io.GSheetBinWM.InvalidSource): + sut.get_value_matrix() - def test_update(self): + def test_update(self, mocker): fixture = 'case__minimal_example.json' - sut = self.get_subject_under_test(fixture) + sut = self.get_subject_under_test(fixture, mocker) - dummy_df = mock.MagicMock(spec_set=pd.DataFrame) + dummy_df = mocker.MagicMock(spec_set=pd.DataFrame) sut.update(dummy_df) sut._facade.write_dataframe.assert_called_once_with( dummy_df, position='A1' ) - def test__score_column_is_ignored(self): + def test__score_column_is_ignored(self, mocker): """Score columns in the source spreadsheet are dropped. This is so they can be re-created in a controlled fashion. """ sut = self.get_subject_under_test( - 'minimal_example_score_column.json' + 'minimal_example_score_column.json', mocker ) actual = sut.df.columns.values @@ -164,7 +148,3 @@ def test__score_column_is_ignored(self): # And just to check the pathological case where our test data # has got out of whack and we've missed this: assert 'Score' in sut._facade.get_rows()[0] - - -if __name__ == '__main__': - unittest.main() diff --git a/vdd/requirements/tests/test_models.py b/vdd/requirements/tests/test_models.py index 9c51820..299428d 100644 --- a/vdd/requirements/tests/test_models.py +++ b/vdd/requirements/tests/test_models.py @@ -1,11 +1,9 @@ import json import os -import unittest -from unittest import mock import numpy as np import pandas as pd -from ddt import ddt, unpack, data +import pytest from .. import io from .. import models @@ -13,16 +11,14 @@ from . import FIXTURES_DIR -class TestCase(unittest.TestCase): +def get_fixture_data(fname): + """Load a JSON fixture file and return its parsed contents.""" + path = os.path.join(FIXTURES_DIR, fname) + with open(path) as f: + return json.load(f) - def get_fixture_data(self, fname): - path = os.path.join(FIXTURES_DIR, fname) - with open(path) as f: - return json.load(f) - -@ddt -class TestBinWM(TestCase): +class TestBinWM: model_data_fixtures = { 'Minimal Example': 'case__minimal_example.json', @@ -32,7 +28,7 @@ class TestBinWM(TestCase): def setup_binary_weighting_matrix(self, key): fixture_fname = self.model_data_fixtures[key] - data = self.get_fixture_data(fixture_fname) + data = get_fixture_data(fixture_fname) bwm = models.BinWM(*data['requirements']) bwm._matrix = np.array(data['binary_matrix']) bwm.label = "My Requirements" @@ -43,7 +39,7 @@ def test_score__motorcycle_helmet(self): np.testing.assert_allclose( bwm.score, - np.array([0.095, 0.286, 0.143, 0.143, 0.143, 0.19]), + np.array([0.095, 0.286, 0.143, 0.143, 0.143, 0.19]), atol=0.01 ) @@ -56,37 +52,36 @@ def test_score__simple_aircraft(self): atol=0.1 ) - @data( + @pytest.mark.parametrize("answers, score", [ [('n', 'n', 'n'), (0.17, 0.33, 0.5)], [('y', 'n', 'n'), (0.33, 0.17, 0.5)], [('n', 'y', 'n'), (0.33, 0.33, 0.33)], [('n', 'y', 'y'), (0.33, 0.5, 0.17)], [('y', 'y', 'y'), (0.5, 0.33, 0.17)] - ) - @unpack - @mock.patch.object(models.BinWM, '_print') - @mock.patch.object(models.BinWM, '_input') - def test_prompt(self, answers, score, mock_input, mock_print): + ]) + def test_prompt(self, answers, score, mocker): + mock_input = mocker.patch.object(models.BinWM, '_input') + mocker.patch.object(models.BinWM, '_print') mock_input.side_effect = answers bwm = self.setup_binary_weighting_matrix('Minimal Example') bwm.prompt(shuffle=False) mock_input.assert_has_calls([ - mock.call("'Requirement 1' is more important than " - "'Requirement 2': "), - mock.call("'Requirement 1' is more important than " - "'Requirement 3': "), - mock.call("'Requirement 2' is more important than " - "'Requirement 3': ") + mocker.call("'Requirement 1' is more important than " + "'Requirement 2': "), + mocker.call("'Requirement 1' is more important than " + "'Requirement 3': "), + mocker.call("'Requirement 2' is more important than " + "'Requirement 3': ") ]) np.testing.assert_allclose(bwm.score, np.array(score), atol=0.01) - @mock.patch('random.shuffle') - @mock.patch.object(models.BinWM, '_print') - @mock.patch.object(models.BinWM, '_input') - def test_prompt__shuffle(self, mock_input, mock_print, mock_shuffle): + def test_prompt__shuffle(self, mocker): + mock_input = mocker.patch.object(models.BinWM, '_input') + mocker.patch.object(models.BinWM, '_print') + mock_shuffle = mocker.patch('random.shuffle') mock_input.side_effect = ['y'] * 3 bwm = self.setup_binary_weighting_matrix('Minimal Example') @@ -113,7 +108,6 @@ def test_to_dataframe(self): 'Requirement ' + str(x) for x in range(1, 4) ] - expected = pd.DataFrame( data=[ [0, 0, 1, expected_scores[0]], @@ -125,92 +119,68 @@ def test_to_dataframe(self): ) expected.index.name = 'My Requirements' - try: - pd.testing.assert_frame_equal(actual, expected) - except AssertionError: - # Ugh. mix of unicode and str causing a comparison failure - # in Python 2. Don't actually care about this so this is a - # little trap to check that's what's happening and let it - # go. - # TODO: remove >= January 2020 - if not (actual.columns == expected.columns).all(): - raise - else: - pass - + pd.testing.assert_frame_equal(actual, expected) def test_save(self): """Method is only implemented in special cases.""" bwm = self.setup_binary_weighting_matrix('Minimal Example') bwm._matrix[2, 0] = 1 - self.assertRaises(NotImplementedError, bwm.save) + with pytest.raises(NotImplementedError): + bwm.save() -@mock.patch.object(models.BinWM, '_get_sheet') -class TestBinWM_GoogleSheetsIntegration(TestCase): +class TestBinWM_GoogleSheetsIntegration: - def setup_mock_sheet(self, mock_getter): - # Get reference data - data = self.get_fixture_data('case__minimal_example.json') + @pytest.fixture(autouse=True) + def setup(self, mocker): + """Patch _get_sheet and configure a mock sheet from fixture data.""" + self.mock_getter = mocker.patch.object(models.BinWM, '_get_sheet') + self._setup_mock_sheet(mocker) + + def _setup_mock_sheet(self, mocker): + data = get_fixture_data('case__minimal_example.json') requirements = data['requirements'] binary_matrix = np.array(data['binary_matrix']) - # Set up mock - mock_sheet = mock.MagicMock(spec_set=io.GSheetBinWM) - mock_getter.return_value = mock_sheet + mock_sheet = mocker.MagicMock(spec_set=io.GSheetBinWM) + self.mock_getter.return_value = mock_sheet mock_sheet.get_requirements.return_value = requirements mock_sheet.get_value_matrix.return_value = binary_matrix + self.mock_sheet = mock_sheet - return mock_sheet - - def test_from_google_sheet(self, mock_getter): + def test_from_google_sheet(self): """Constructor uses and links a google sheet to instantiate. Requirements and binary matrix are fetched from the io.BinWMSheet interface to populate the object. """ - mock_sheet = self.setup_mock_sheet(mock_getter) - bwm = models.BinWM.from_google_sheet('dummy name') actual_requirements = bwm.requirements - expected_requirements = tuple(mock_sheet.get_requirements()) - self.assertEqual(actual_requirements, expected_requirements) + expected_requirements = tuple(self.mock_sheet.get_requirements()) + assert actual_requirements == expected_requirements actual_matrix = bwm.matrix - expected_matrix = mock_sheet.get_value_matrix() + expected_matrix = self.mock_sheet.get_value_matrix() np.testing.assert_allclose(actual_matrix, expected_matrix) - def test_access_sheet_model(self, mock_getter): - """Instances access linked sheets through a generic interface. - """ - mock_sheet = self.setup_mock_sheet(mock_getter) - + def test_access_sheet_model(self): + """Instances access linked sheets through a generic interface.""" bwm = models.BinWM.from_google_sheet('dummy name') - actual = bwm._sheet - expected = mock_sheet - self.assertIs(actual, expected) + assert bwm._sheet is self.mock_sheet - @mock.patch.object(models.BinWM, 'to_dataframe') - def test_save__triggers_update(self, mock_to_dataframe, - mock_getter): + def test_save__triggers_update(self, mocker): """Save method wraps the google sheet update method.""" - mock_sheet = self.setup_mock_sheet(mock_getter) - + mock_to_dataframe = mocker.patch.object(models.BinWM, 'to_dataframe') mock_to_dataframe.return_value = blank_df = pd.DataFrame() bwm = models.BinWM.from_google_sheet('dummy name') bwm.save() - mock_sheet.update.assert_called_once_with(blank_df) + self.mock_sheet.update.assert_called_once_with(blank_df) -class TestBinWM_ExcelIntegration(unittest.TestCase): - # TODO: BinWM is not current integrated with Excel +class TestBinWM_ExcelIntegration: + # TODO: BinWM is not currently integrated with Excel pass - - - -if __name__ == '__main__': - unittest.main() From 1e41e9ee1ea07c44459e8b028f0285b4f6ace0f2 Mon Sep 17 00:00:00 2001 From: Alex Corrie Date: Sun, 15 Mar 2026 02:31:05 +0000 Subject: [PATCH 3/3] feat!: add a simple cli BREAKING CHANGE: comes with dropping python 3.8-3.10 support --- README.md | 34 +++++++++++-- pyproject.toml | 4 ++ uv.lock | 81 ++++++++++++++++++++++++++++++ vdd/cli.py | 75 +++++++++++++++++++++++++++ vdd/coda/data/sample_compact.xlsx | Bin 9799 -> 8707 bytes vdd/requirements/models.py | 8 --- 6 files changed, 191 insertions(+), 11 deletions(-) create mode 100644 vdd/cli.py diff --git a/README.md b/README.md index 34cfedc..a39e488 100644 --- a/README.md +++ b/README.md @@ -22,6 +22,7 @@ Features - Requirements weighting with a Binary Weighting Matrix - Programmatic or Spreadsheet based model creation (via Excel workbooks or Google Sheets). + - Command-line interface for quick model inspection and interactive weighting Install @@ -30,6 +31,34 @@ Install pip install vdd +CLI +--- + +`vdd` ships with a command-line interface for the two core workflows. + +### Inspect a CODA model + +Load a CODA model from an Excel file and print the overall design merit +alongside a per-requirement satisfaction summary: + + vdd coda path/to/model.xlsx + +By default the compact Excel format is assumed. Pass `--parser full` for the +standard format: + + vdd coda path/to/model.xlsx --parser full + +### Weight requirements interactively + +Step through a pairwise comparison of requirements and print the resulting +normalised scores: + + vdd requirements weight "Lightweight" "Stiff" "Durable" + +Questions are shuffled by default. Pass `--no-shuffle` to work through them +in a fixed order. + + Documentation ------- @@ -42,10 +71,9 @@ Currently just stored in the repo. Development ----------- -`poetry` must be installed in the local development environment as a pre-requisite. In the repository root: - +In the repository root: - poetry install + uv sync ### Releases diff --git a/pyproject.toml b/pyproject.toml index fdcf212..5bc907b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -15,8 +15,12 @@ dependencies = [ "numpy>=1.26", "xlrd>=2.0,<3", "openpyxl>=3.0.10,<4", + "typer[all]>=0.12", ] +[project.scripts] +vdd = "vdd.cli:app" + [dependency-groups] dev = [ "pytest>=8", diff --git a/uv.lock b/uv.lock index e42c2ee..f9f0443 100644 --- a/uv.lock +++ b/uv.lock @@ -13,6 +13,15 @@ resolution-markers = [ "python_full_version < '3.13' and sys_platform != 'emscripten' and sys_platform != 'win32'", ] +[[package]] +name = "annotated-doc" +version = "0.0.4" +source = { registry = "https://pypi.org/simple" } +sdist = { url = "https://files.pythonhosted.org/packages/57/ba/046ceea27344560984e26a590f90bc7f4a75b06701f653222458922b558c/annotated_doc-0.0.4.tar.gz", hash = "sha256:fbcda96e87e9c92ad167c2e53839e57503ecfda18804ea28102353485033faa4", size = 7288, upload-time = 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specifier = ">=0.12" }, { name = "xlrd", specifier = ">=2.0,<3" }, ] diff --git a/vdd/cli.py b/vdd/cli.py new file mode 100644 index 0000000..b80c319 --- /dev/null +++ b/vdd/cli.py @@ -0,0 +1,75 @@ +"""vdd command-line interface.""" +from pathlib import Path +from typing import Annotated + +import typer +from rich.console import Console +from rich.table import Table + +app = typer.Typer(help="Value-Driven Design tools.") +requirements_app = typer.Typer(help="Requirements weighting tools.") +app.add_typer(requirements_app, name="requirements") + +console = Console() + + +def _bar(value: float, width: int = 10) -> str: + filled = round(value * width) + return "█" * filled + "░" * (width - filled) + f" {value:.2f}" + + +@app.command() +def coda( + file: Annotated[Path, typer.Argument(help="Excel model file")], + parser: Annotated[str, typer.Option(help="Parser: compact or full")] = "compact", +) -> None: + """Load a CODA model from an Excel file and display results.""" + from vdd.coda import CODA + from vdd.coda.io import CompactExcelParser, ExcelParser + + parser_cls = CompactExcelParser if parser == "compact" else ExcelParser + model = CODA.from_excel(file, parser_class=parser_cls) + + # Default unset characteristic values to the midpoint of their bounds. + for char in model.characteristics: + try: + char.value # noqa: B018 + except AttributeError: + lo, hi = char.limits + char.value = ((lo or 0.0) + (hi or 1.0)) / 2 + + console.print(f"Merit: {model.merit:.2f}") + + table = Table(show_header=True, header_style="bold") + table.add_column("Requirement") + table.add_column("Weight", justify="right") + table.add_column("Satisfaction") + + weights = model.weight[:, 0] + satisfactions = model.satisfaction[:, 0] + + for req, w, s in zip(model.requirements, weights, satisfactions): + table.add_row(req.name, f"{w:.2f}", _bar(s)) + + console.print(table) + + +@requirements_app.command("weight") +def weight( + reqs: Annotated[list[str], typer.Argument(help="Requirement names")], + shuffle: Annotated[bool, typer.Option(help="Shuffle question order")] = True, +) -> None: + """Interactively weight requirements using pairwise comparison.""" + from vdd.requirements.models import BinWM + + bwm = BinWM(*reqs) + bwm.prompt(shuffle=shuffle) + + table = Table(show_header=True, header_style="bold") + table.add_column("Requirement") + table.add_column("Score") + + for req, score in zip(bwm.requirements, bwm.score): + table.add_row(req, _bar(score)) + + console.print(table) diff --git a/vdd/coda/data/sample_compact.xlsx b/vdd/coda/data/sample_compact.xlsx index 1cf9601a6f597e0a8095dff9f5673a4c0dc92f97..8fd9b250196d76ff9e877a4b00c7735ee87f87bb 100644 GIT binary patch literal 8707 zcmcgxbzEG@vL2kl8QdL0a0?Qg;BJB75Zv88Sg_#k7JNu>cL_ED65N8jLvY??_ubvQ zdH4N$XMX3L?wKGhscLD8RxF^ee3;d%?~W&%Sw(D+8z8f$jH zu}WFEK~ls$J`1SQ_pWJk3w&ars8}RL!P@qw6OO`>=TBuqc#2XV!BfxK8g{rhMd(Co zAyD~;2}gM4Vn{Fmz&7;4{&y4JIyjsCvLQ5HRlb)UH}q+E$0wtx8$*0Lobk4RQd`9r 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+87,6 @@ def _print(string): # Wrapper for testing print(string) - properties = {'width':'15em', 'text-align':'center'} - styles = [{ - 'selector': 'th', - 'props': [('text-align', 'center')] - }] - df.style.set_properties(**properties).set_table_styles(styles) - return df - def get_score_as_series(self): # Glue method until API changes; see score TODO try: