forked from pool/python-pytest-regressions
Matej Cepl
8b55f37225
- Update to 2.2.0: - #45: num_regression.check now accepts any object that can be coerced to a 1d numpy array with numeric dtype (e.g. list, tuple, etc). - #35: New dataframe_regression fixture to check pandas DataFrames directly. - #34: Fix data_regression bug that creates empty file on serializing error. - Add np_num-deprecated.patch to avoid tests failing on using deprecated data types (gh#ESSS/pytest-regressions#63). OBS-URL: https://build.opensuse.org/request/show/909017 OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:pytest/python-pytest-regressions?expand=0&rev=1
98 lines
3.9 KiB
Diff
98 lines
3.9 KiB
Diff
---
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src/pytest_regressions/dataframe_regression.py | 4 ++--
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tests/test_dataframe_regression.py | 8 ++++----
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tests/test_num_regression.py | 10 +++++-----
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3 files changed, 11 insertions(+), 11 deletions(-)
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--- a/src/pytest_regressions/dataframe_regression.py
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+++ b/src/pytest_regressions/dataframe_regression.py
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@@ -123,7 +123,7 @@ class DataFrameRegressionFixture:
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self._check_data_shapes(obtained_column, expected_column)
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data_type = obtained_column.values.dtype
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- if data_type in [float, np.float, np.float16, np.float32, np.float64]:
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+ if data_type in [float, np.float16, np.float32, np.float64]:
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not_close_mask = ~np.isclose(
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obtained_column.values,
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expected_column.values,
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@@ -137,7 +137,7 @@ class DataFrameRegressionFixture:
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diff_ids = np.where(not_close_mask)[0]
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diff_obtained_data = obtained_column[diff_ids]
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diff_expected_data = expected_column[diff_ids]
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- if data_type == np.bool:
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+ if data_type == bool:
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diffs = np.logical_xor(obtained_column, expected_column)[diff_ids]
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else:
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diffs = np.abs(obtained_column - expected_column)[diff_ids]
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--- a/tests/test_dataframe_regression.py
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+++ b/tests/test_dataframe_regression.py
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@@ -193,7 +193,7 @@ def test_arrays_with_different_sizes(dat
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def test_integer_values_smoke_test(dataframe_regression, no_regen):
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- data1 = np.ones(11, dtype=np.int)
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+ data1 = np.ones(11, dtype=int)
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dataframe_regression.check(pd.DataFrame.from_dict({"data1": data1}))
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@@ -203,7 +203,7 @@ def test_number_formats(dataframe_regres
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def test_bool_array(dataframe_regression, no_regen):
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- data1 = np.array([True, True, True], dtype=np.bool)
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+ data1 = np.array([True, True, True], dtype=bool)
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with pytest.raises(AssertionError) as excinfo:
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dataframe_regression.check(pd.DataFrame.from_dict({"data1": data1}))
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obtained_error_msg = str(excinfo.value)
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@@ -228,8 +228,8 @@ def test_bool_array(dataframe_regression
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def test_arrays_of_same_size(dataframe_regression):
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same_size_int_arrays = {
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- "hello": np.zeros((1,), dtype=np.int),
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- "world": np.zeros((1,), dtype=np.int),
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+ "hello": np.zeros((1,), dtype=int),
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+ "world": np.zeros((1,), dtype=int),
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}
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dataframe_regression.check(pd.DataFrame.from_dict(same_size_int_arrays))
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--- a/tests/test_num_regression.py
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+++ b/tests/test_num_regression.py
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@@ -169,7 +169,7 @@ def test_different_data_types(num_regres
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def test_n_dimensions(num_regression, no_regen):
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- data1 = np.ones(shape=(10, 10), dtype=np.int)
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+ data1 = np.ones(shape=(10, 10), dtype=int)
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with pytest.raises(
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AssertionError,
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match="Only 1D arrays are supported on num_data_regression fixture.",
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@@ -186,7 +186,7 @@ def test_arrays_with_different_sizes(num
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def test_integer_values_smoke_test(num_regression, no_regen):
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- data1 = np.ones(11, dtype=np.int)
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+ data1 = np.ones(11, dtype=int)
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num_regression.check({"data1": data1})
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@@ -228,7 +228,7 @@ def test_fill_different_shape_with_nan_f
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def test_bool_array(num_regression, no_regen):
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- data1 = np.array([True, True, True], dtype=np.bool)
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+ data1 = np.array([True, True, True], dtype=bool)
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with pytest.raises(AssertionError) as excinfo:
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num_regression.check({"data1": data1})
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obtained_error_msg = str(excinfo.value)
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@@ -253,8 +253,8 @@ def test_bool_array(num_regression, no_r
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def test_arrays_of_same_size(num_regression):
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same_size_int_arrays = {
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- "hello": np.zeros((1,), dtype=np.int),
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- "world": np.zeros((1,), dtype=np.int),
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+ "hello": np.zeros((1,), dtype=int),
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+ "world": np.zeros((1,), dtype=int),
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}
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num_regression.check(same_size_int_arrays)
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