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import pytest
from deepdiff import DeepDiff
from deepdiff.helper import np
from tests import parameterize_cases
"""
These are numpy specific test cases.
There are more numpy tests for delta additions in the test_delta.py
"""
NUMPY_CASES = {
'numpy_bools': {
't1': np.array([True, False, True, False], dtype=bool),
't2': np.array([False, True, True, False], dtype=bool),
'deepdiff_kwargs': {},
'expected_result': {'values_changed': {'root[0]': {'new_value': False, 'old_value': True},
'root[1]': {'new_value': True, 'old_value': False}}},
},
'numpy_bools_ignore_order': {
't1': np.array([True, False, True, False], dtype=bool),
't2': np.array([False, True, True, False], dtype=bool),
'deepdiff_kwargs': {'ignore_order': True},
'expected_result': {},
},
'numpy_multi_dimensional1': {
't1': np.array([[[1, 2, 3], [4, 5, 6]]], np.int32),
't2': np.array([[[1, 2, 5], [3, 5, 6]]], np.int32),
'deepdiff_kwargs': {},
'expected_result': {'values_changed':
{'root[0][0][2]': {'new_value': 5, 'old_value': 3},
'root[0][1][0]': {'new_value': 3, 'old_value': 4}}},
},
'numpy_array2_type_change': {
't1': np.array([1, 2, 3], np.int8),
't2': np.array([1, 2, 5], np.int32),
'deepdiff_kwargs': {'verbose_level': 0},
'expected_result': {'type_changes': {'root': {'old_type': np.int8, 'new_type': np.int32}}},
},
'numpy_array3_ignore_number_type_changes': {
't1': np.array([1, 2, 3], np.int8),
't2': np.array([1, 2, 5], np.int32),
'deepdiff_kwargs': {'ignore_numeric_type_changes': True},
'expected_result': {'values_changed': {'root[2]': {'new_value': 5, 'old_value': 3}}},
},
'numpy_array4_ignore_number_type_changes_and_ignore_order': {
't1': np.array([1, 2, 3], np.int8),
't2': np.array([3, 1, 2], np.int32),
'deepdiff_kwargs': {'ignore_numeric_type_changes': True, 'ignore_order': True},
'expected_result': {},
},
'numpy_array5_ignore_number_type_changes_and_ignore_order': {
't1': np.array([1, 2, 4, 3], np.int8),
't2': np.array([3, 1, 2, 5], np.int32),
'deepdiff_kwargs': {'ignore_numeric_type_changes': True, 'ignore_order': True},
'expected_result': {'values_changed': {'root[2]': {'new_value': 5, 'old_value': 4}}},
},
'numpy_array6_ignore_order_and_report_repetition': {
't1': np.array([1, 2, 3, 3], np.int8),
't2': np.array([3, 1, 2, 5], np.int8),
'deepdiff_kwargs': {'report_repetition': True, 'ignore_order': True},
'expected_result': {'iterable_item_added': {'root[3]': 5},
'repetition_change': {'root[2]': {'old_repeat': 2, 'new_repeat': 1,
'old_indexes': [2, 3], 'new_indexes': [0], 'value': 3}}},
},
'numpy_array7_ignore_order_multi_dimensional_array': {
't1': np.array([[1, 2, 3, 4], [4, 2, 2, 1]], np.int8),
't2': np.array([[4, 1, 1, 1], [1, 3, 2, 4]], np.int8),
'deepdiff_kwargs': {'report_repetition': True, 'ignore_order': True},
'expected_result': {
'iterable_item_removed': {
'root[1][1]': 2,
'root[1][2]': 2
},
'repetition_change': {
'root[1][3]': {
'old_repeat': 1,
'new_repeat': 3,
'old_indexes': [3],
'new_indexes': [1, 2, 3],
'value': 1
}
}
},
},
'numpy_array8_ignore_order_multi_dimensional_array_converted_to_list': {
't1': np.array([[1, 2, 3, 4], [4, 2, 2, 1]], np.int8).tolist(),
't2': np.array([[4, 1, 1, 1], [1, 3, 2, 4]], np.int8).tolist(),
'deepdiff_kwargs': {
'report_repetition': True,
'ignore_order': True
},
'expected_result': {
'iterable_item_removed': {
'root[1][1]': 2,
'root[1][2]': 2
},
'repetition_change': {
'root[1][3]': {
'old_repeat': 1,
'new_repeat': 3,
'old_indexes': [3],
'new_indexes': [1, 2, 3],
'value': 1
}
}
},
},
'numpy_array9_ignore_nan_inequality_float32': {
't1': np.array([1, 2, 3, np.nan], np.float32),
't2': np.array([1, 2, 4, np.nan], np.float32),
'deepdiff_kwargs': {
'ignore_nan_inequality': True,
},
'expected_result': {'values_changed': {'root[2]': {'new_value': 4.0, 'old_value': 3.0}}}
},
'numpy_almost_equal': {
't1': np.array([1.0, 2.3333333333333]),
't2': np.array([1.0, 2.33333334]),
'deepdiff_kwargs': {'significant_digits': 3},
'expected_result': {},
},
'numpy_almost_equal2': {
't1': np.array(['a', 'b'], dtype=object),
't2': np.array(['a', 'b'], dtype=object),
'deepdiff_kwargs': {'significant_digits': 6},
'expected_result': {},
},
'numpy_different_shape': {
't1': np.array([[1, 1], [2, 3]]),
't2': np.array([1]),
'deepdiff_kwargs': {},
'expected_result': {
'type_changes': {
'root[0]': {
'old_type': list,
'new_type': int,
'old_value': [1, 1],
'new_value': 1
}
},
'iterable_item_removed': {
'root[1]': [2, 3]
}
},
},
}
NUMPY_CASES_PARAMS = parameterize_cases('test_name, t1, t2, deepdiff_kwargs, expected_result', NUMPY_CASES)
class TestNumpy:
@pytest.mark.parametrize(**NUMPY_CASES_PARAMS)
def test_numpy(self, test_name, t1, t2, deepdiff_kwargs, expected_result):
diff = DeepDiff(t1, t2, **deepdiff_kwargs)
assert expected_result == diff, f"test_numpy {test_name} failed."
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