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TST: Use numeric dtype fixtures for testing #21500

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@jschendel

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@jschendel

Some new numeric dtype fixtures were implemented in #21432:

pandas/pandas/conftest.py

Lines 183 to 243 in 9e982e1

@pytest.fixture(params=["float32", "float64"])
def float_dtype(request):
"""
Parameterized fixture for float dtypes.
* float32
* float64
"""
return request.param
UNSIGNED_INT_DTYPES = ["uint8", "uint16", "uint32", "uint64"]
SIGNED_INT_DTYPES = ["int8", "int16", "int32", "int64"]
ALL_INT_DTYPES = UNSIGNED_INT_DTYPES + SIGNED_INT_DTYPES
@pytest.fixture(params=SIGNED_INT_DTYPES)
def sint_dtype(request):
"""
Parameterized fixture for signed integer dtypes.
* int8
* int16
* int32
* int64
"""
return request.param
@pytest.fixture(params=UNSIGNED_INT_DTYPES)
def uint_dtype(request):
"""
Parameterized fixture for unsigned integer dtypes.
* uint8
* uint16
* uint32
* uint64
"""
return request.param
@pytest.fixture(params=ALL_INT_DTYPES)
def any_int_dtype(request):
"""
Parameterized fixture for any integer dtypes.
* int8
* uint8
* int16
* uint16
* int32
* uint32
* int64
* uint64
"""
return request.param

It would be nice to use these fixtures where appropriate in the existing tests, e.g.

@pytest.mark.parametrize('dtype', [np.int64, np.int32, np.int16, np.int8])
def test_dti_constructor_small_int(self, dtype):

Additional comments:

  • These changes can be split across multiple PR's so no need to do all changes at once
    • Not how many instances of this will need to be replaced, so this will need to be investigated
  • This might involve expanding the dtype coverage for some tests
    • The example test shown above could also be tested over uint dtypes
  • Can probably drop float16 dtypes from tests since it's barely supported
  • Might be necessary to create additional fixtures
    • Perhaps a fixture for the combination of float + signed integer + unsigned integer dtypes

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    CleanDtype ConversionsUnexpected or buggy dtype conversionsTestingpandas testing functions or related to the test suite

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