259 lines
7.1 KiB
Python
259 lines
7.1 KiB
Python
"""
|
|
This file contains a minimal set of tests for compliance with the extension
|
|
array interface test suite, and should contain no other tests.
|
|
The test suite for the full functionality of the array is located in
|
|
`pandas/tests/arrays/`.
|
|
|
|
The tests in this file are inherited from the BaseExtensionTests, and only
|
|
minimal tweaks should be applied to get the tests passing (by overwriting a
|
|
parent method).
|
|
|
|
Additional tests should either be added to one of the BaseExtensionTests
|
|
classes (if they are relevant for the extension interface for all dtypes), or
|
|
be added to the array-specific tests in `pandas/tests/arrays/`.
|
|
|
|
"""
|
|
import numpy as np
|
|
import pytest
|
|
|
|
from pandas.core.dtypes.common import is_extension_array_dtype
|
|
|
|
import pandas as pd
|
|
import pandas._testing as tm
|
|
from pandas.core.arrays import integer_array
|
|
from pandas.core.arrays.integer import (
|
|
Int8Dtype,
|
|
Int16Dtype,
|
|
Int32Dtype,
|
|
Int64Dtype,
|
|
UInt8Dtype,
|
|
UInt16Dtype,
|
|
UInt32Dtype,
|
|
UInt64Dtype,
|
|
)
|
|
from pandas.tests.extension import base
|
|
|
|
|
|
def make_data():
|
|
return list(range(1, 9)) + [pd.NA] + list(range(10, 98)) + [pd.NA] + [99, 100]
|
|
|
|
|
|
@pytest.fixture(
|
|
params=[
|
|
Int8Dtype,
|
|
Int16Dtype,
|
|
Int32Dtype,
|
|
Int64Dtype,
|
|
UInt8Dtype,
|
|
UInt16Dtype,
|
|
UInt32Dtype,
|
|
UInt64Dtype,
|
|
]
|
|
)
|
|
def dtype(request):
|
|
return request.param()
|
|
|
|
|
|
@pytest.fixture
|
|
def data(dtype):
|
|
return integer_array(make_data(), dtype=dtype)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_for_twos(dtype):
|
|
return integer_array(np.ones(100) * 2, dtype=dtype)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_missing(dtype):
|
|
return integer_array([pd.NA, 1], dtype=dtype)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_for_sorting(dtype):
|
|
return integer_array([1, 2, 0], dtype=dtype)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_missing_for_sorting(dtype):
|
|
return integer_array([1, pd.NA, 0], dtype=dtype)
|
|
|
|
|
|
@pytest.fixture
|
|
def na_cmp():
|
|
# we are pd.NA
|
|
return lambda x, y: x is pd.NA and y is pd.NA
|
|
|
|
|
|
@pytest.fixture
|
|
def na_value():
|
|
return pd.NA
|
|
|
|
|
|
@pytest.fixture
|
|
def data_for_grouping(dtype):
|
|
b = 1
|
|
a = 0
|
|
c = 2
|
|
na = pd.NA
|
|
return integer_array([b, b, na, na, a, a, b, c], dtype=dtype)
|
|
|
|
|
|
class TestDtype(base.BaseDtypeTests):
|
|
@pytest.mark.skip(reason="using multiple dtypes")
|
|
def test_is_dtype_unboxes_dtype(self):
|
|
# we have multiple dtypes, so skip
|
|
pass
|
|
|
|
|
|
class TestArithmeticOps(base.BaseArithmeticOpsTests):
|
|
def check_opname(self, s, op_name, other, exc=None):
|
|
# overwriting to indicate ops don't raise an error
|
|
super().check_opname(s, op_name, other, exc=None)
|
|
|
|
def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
|
|
if exc is None:
|
|
if s.dtype.is_unsigned_integer and (op_name == "__rsub__"):
|
|
# TODO see https://github.com/pandas-dev/pandas/issues/22023
|
|
pytest.skip("unsigned subtraction gives negative values")
|
|
|
|
if (
|
|
hasattr(other, "dtype")
|
|
and not is_extension_array_dtype(other.dtype)
|
|
and pd.api.types.is_integer_dtype(other.dtype)
|
|
):
|
|
# other is np.int64 and would therefore always result in
|
|
# upcasting, so keeping other as same numpy_dtype
|
|
other = other.astype(s.dtype.numpy_dtype)
|
|
|
|
result = op(s, other)
|
|
expected = s.combine(other, op)
|
|
|
|
if op_name in ("__rtruediv__", "__truediv__", "__div__"):
|
|
expected = expected.fillna(np.nan).astype("Float64")
|
|
elif op_name.startswith("__r"):
|
|
# TODO reverse operators result in object dtype
|
|
# see https://github.com/pandas-dev/pandas/issues/22024
|
|
expected = expected.astype(s.dtype)
|
|
result = result.astype(s.dtype)
|
|
else:
|
|
# combine method result in 'biggest' (int64) dtype
|
|
expected = expected.astype(s.dtype)
|
|
pass
|
|
|
|
if (op_name == "__rpow__") and isinstance(other, pd.Series):
|
|
# TODO pow on Int arrays gives different result with NA
|
|
# see https://github.com/pandas-dev/pandas/issues/22022
|
|
result = result.fillna(1)
|
|
|
|
self.assert_series_equal(result, expected)
|
|
else:
|
|
with pytest.raises(exc):
|
|
op(s, other)
|
|
|
|
def _check_divmod_op(self, s, op, other, exc=None):
|
|
super()._check_divmod_op(s, op, other, None)
|
|
|
|
@pytest.mark.skip(reason="intNA does not error on ops")
|
|
def test_error(self, data, all_arithmetic_operators):
|
|
# other specific errors tested in the integer array specific tests
|
|
pass
|
|
|
|
|
|
class TestComparisonOps(base.BaseComparisonOpsTests):
|
|
def _check_op(self, s, op, other, op_name, exc=NotImplementedError):
|
|
if exc is None:
|
|
result = op(s, other)
|
|
# Override to do the astype to boolean
|
|
expected = s.combine(other, op).astype("boolean")
|
|
self.assert_series_equal(result, expected)
|
|
else:
|
|
with pytest.raises(exc):
|
|
op(s, other)
|
|
|
|
def check_opname(self, s, op_name, other, exc=None):
|
|
super().check_opname(s, op_name, other, exc=None)
|
|
|
|
def _compare_other(self, s, data, op_name, other):
|
|
self.check_opname(s, op_name, other)
|
|
|
|
|
|
class TestInterface(base.BaseInterfaceTests):
|
|
pass
|
|
|
|
|
|
class TestConstructors(base.BaseConstructorsTests):
|
|
pass
|
|
|
|
|
|
class TestReshaping(base.BaseReshapingTests):
|
|
pass
|
|
|
|
# for test_concat_mixed_dtypes test
|
|
# concat of an Integer and Int coerces to object dtype
|
|
# TODO(jreback) once integrated this would
|
|
|
|
|
|
class TestGetitem(base.BaseGetitemTests):
|
|
pass
|
|
|
|
|
|
class TestSetitem(base.BaseSetitemTests):
|
|
pass
|
|
|
|
|
|
class TestMissing(base.BaseMissingTests):
|
|
pass
|
|
|
|
|
|
class TestMethods(base.BaseMethodsTests):
|
|
@pytest.mark.skip(reason="uses nullable integer")
|
|
def test_value_counts(self, all_data, dropna):
|
|
all_data = all_data[:10]
|
|
if dropna:
|
|
other = np.array(all_data[~all_data.isna()])
|
|
else:
|
|
other = all_data
|
|
|
|
result = pd.Series(all_data).value_counts(dropna=dropna).sort_index()
|
|
expected = pd.Series(other).value_counts(dropna=dropna).sort_index()
|
|
expected.index = expected.index.astype(all_data.dtype)
|
|
|
|
self.assert_series_equal(result, expected)
|
|
|
|
@pytest.mark.skip(reason="uses nullable integer")
|
|
def test_value_counts_with_normalize(self, data):
|
|
pass
|
|
|
|
|
|
class TestCasting(base.BaseCastingTests):
|
|
pass
|
|
|
|
|
|
class TestGroupby(base.BaseGroupbyTests):
|
|
pass
|
|
|
|
|
|
class TestNumericReduce(base.BaseNumericReduceTests):
|
|
def check_reduce(self, s, op_name, skipna):
|
|
# overwrite to ensure pd.NA is tested instead of np.nan
|
|
# https://github.com/pandas-dev/pandas/issues/30958
|
|
result = getattr(s, op_name)(skipna=skipna)
|
|
if not skipna and s.isna().any():
|
|
expected = pd.NA
|
|
else:
|
|
expected = getattr(s.dropna().astype("int64"), op_name)(skipna=skipna)
|
|
tm.assert_almost_equal(result, expected)
|
|
|
|
|
|
class TestBooleanReduce(base.BaseBooleanReduceTests):
|
|
pass
|
|
|
|
|
|
class TestPrinting(base.BasePrintingTests):
|
|
pass
|
|
|
|
|
|
class TestParsing(base.BaseParsingTests):
|
|
pass
|