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| import numpy as np
| import pytest
|
| import pandas as pd
| from pandas.core.arrays.integer import (
| Int8Dtype,
| Int16Dtype,
| Int32Dtype,
| Int64Dtype,
| UInt8Dtype,
| UInt16Dtype,
| UInt32Dtype,
| UInt64Dtype,
| )
|
|
| def test_dtypes(dtype):
| # smoke tests on auto dtype construction
|
| if dtype.is_signed_integer:
| assert np.dtype(dtype.type).kind == "i"
| else:
| assert np.dtype(dtype.type).kind == "u"
| assert dtype.name is not None
|
|
| @pytest.mark.parametrize(
| "dtype, expected",
| [
| (Int8Dtype(), "Int8Dtype()"),
| (Int16Dtype(), "Int16Dtype()"),
| (Int32Dtype(), "Int32Dtype()"),
| (Int64Dtype(), "Int64Dtype()"),
| (UInt8Dtype(), "UInt8Dtype()"),
| (UInt16Dtype(), "UInt16Dtype()"),
| (UInt32Dtype(), "UInt32Dtype()"),
| (UInt64Dtype(), "UInt64Dtype()"),
| ],
| )
| def test_repr_dtype(dtype, expected):
| assert repr(dtype) == expected
|
|
| def test_repr_array():
| result = repr(pd.array([1, None, 3]))
| expected = "<IntegerArray>\n[1, <NA>, 3]\nLength: 3, dtype: Int64"
| assert result == expected
|
|
| def test_repr_array_long():
| data = pd.array([1, 2, None] * 1000)
| expected = (
| "<IntegerArray>\n"
| "[ 1, 2, <NA>, 1, 2, <NA>, 1, 2, <NA>, 1,\n"
| " ...\n"
| " <NA>, 1, 2, <NA>, 1, 2, <NA>, 1, 2, <NA>]\n"
| "Length: 3000, dtype: Int64"
| )
| result = repr(data)
| assert result == expected
|
|
| def test_frame_repr(data_missing):
| df = pd.DataFrame({"A": data_missing})
| result = repr(df)
| expected = " A\n0 <NA>\n1 1"
| assert result == expected
|
|
