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- import re
- import numpy as np
- import pytest
- import pandas as pd
- class TestSetitemValidation:
- def _check_setitem_invalid(self, arr, invalid):
- msg = f"Invalid value '{str(invalid)}' for dtype {arr.dtype}"
- msg = re.escape(msg)
- with pytest.raises(TypeError, match=msg):
- arr[0] = invalid
- with pytest.raises(TypeError, match=msg):
- arr[:] = invalid
- with pytest.raises(TypeError, match=msg):
- arr[[0]] = invalid
- # FIXME: don't leave commented-out
- # with pytest.raises(TypeError):
- # arr[[0]] = [invalid]
- # with pytest.raises(TypeError):
- # arr[[0]] = np.array([invalid], dtype=object)
- # Series non-coercion, behavior subject to change
- ser = pd.Series(arr)
- with pytest.raises(TypeError, match=msg):
- ser[0] = invalid
- # TODO: so, so many other variants of this...
- _invalid_scalars = [
- 1 + 2j,
- "True",
- "1",
- "1.0",
- pd.NaT,
- np.datetime64("NaT"),
- np.timedelta64("NaT"),
- ]
- @pytest.mark.parametrize(
- "invalid", _invalid_scalars + [1, 1.0, np.int64(1), np.float64(1)]
- )
- def test_setitem_validation_scalar_bool(self, invalid):
- arr = pd.array([True, False, None], dtype="boolean")
- self._check_setitem_invalid(arr, invalid)
- @pytest.mark.parametrize("invalid", _invalid_scalars + [True, 1.5, np.float64(1.5)])
- def test_setitem_validation_scalar_int(self, invalid, any_int_ea_dtype):
- arr = pd.array([1, 2, None], dtype=any_int_ea_dtype)
- self._check_setitem_invalid(arr, invalid)
- @pytest.mark.parametrize("invalid", _invalid_scalars + [True])
- def test_setitem_validation_scalar_float(self, invalid, float_ea_dtype):
- arr = pd.array([1, 2, None], dtype=float_ea_dtype)
- self._check_setitem_invalid(arr, invalid)
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