mirror of
https://github.com/PiBrewing/craftbeerpi4.git
synced 2024-12-30 17:31:44 +01:00
123 lines
2.6 KiB
Python
123 lines
2.6 KiB
Python
import string
|
|
|
|
import numpy as np
|
|
import pytest
|
|
|
|
import pandas as pd
|
|
from pandas.core.arrays.string_ import StringArray, StringDtype
|
|
from pandas.tests.extension import base
|
|
|
|
|
|
@pytest.fixture
|
|
def dtype():
|
|
return StringDtype()
|
|
|
|
|
|
@pytest.fixture
|
|
def data():
|
|
strings = np.random.choice(list(string.ascii_letters), size=100)
|
|
while strings[0] == strings[1]:
|
|
strings = np.random.choice(list(string.ascii_letters), size=100)
|
|
|
|
return StringArray._from_sequence(strings)
|
|
|
|
|
|
@pytest.fixture
|
|
def data_missing():
|
|
"""Length 2 array with [NA, Valid]"""
|
|
return StringArray._from_sequence([pd.NA, "A"])
|
|
|
|
|
|
@pytest.fixture
|
|
def data_for_sorting():
|
|
return StringArray._from_sequence(["B", "C", "A"])
|
|
|
|
|
|
@pytest.fixture
|
|
def data_missing_for_sorting():
|
|
return StringArray._from_sequence(["B", pd.NA, "A"])
|
|
|
|
|
|
@pytest.fixture
|
|
def na_value():
|
|
return pd.NA
|
|
|
|
|
|
@pytest.fixture
|
|
def data_for_grouping():
|
|
return StringArray._from_sequence(["B", "B", pd.NA, pd.NA, "A", "A", "B", "C"])
|
|
|
|
|
|
class TestDtype(base.BaseDtypeTests):
|
|
pass
|
|
|
|
|
|
class TestInterface(base.BaseInterfaceTests):
|
|
pass
|
|
|
|
|
|
class TestConstructors(base.BaseConstructorsTests):
|
|
pass
|
|
|
|
|
|
class TestReshaping(base.BaseReshapingTests):
|
|
pass
|
|
|
|
|
|
class TestGetitem(base.BaseGetitemTests):
|
|
pass
|
|
|
|
|
|
class TestSetitem(base.BaseSetitemTests):
|
|
pass
|
|
|
|
|
|
class TestMissing(base.BaseMissingTests):
|
|
pass
|
|
|
|
|
|
class TestNoReduce(base.BaseNoReduceTests):
|
|
@pytest.mark.parametrize("skipna", [True, False])
|
|
def test_reduce_series_numeric(self, data, all_numeric_reductions, skipna):
|
|
op_name = all_numeric_reductions
|
|
|
|
if op_name in ["min", "max"]:
|
|
return None
|
|
|
|
s = pd.Series(data)
|
|
with pytest.raises(TypeError):
|
|
getattr(s, op_name)(skipna=skipna)
|
|
|
|
|
|
class TestMethods(base.BaseMethodsTests):
|
|
@pytest.mark.skip(reason="returns nullable")
|
|
def test_value_counts(self, all_data, dropna):
|
|
return super().test_value_counts(all_data, dropna)
|
|
|
|
|
|
class TestCasting(base.BaseCastingTests):
|
|
pass
|
|
|
|
|
|
class TestComparisonOps(base.BaseComparisonOpsTests):
|
|
def _compare_other(self, s, data, op_name, other):
|
|
result = getattr(s, op_name)(other)
|
|
expected = getattr(s.astype(object), op_name)(other).astype("boolean")
|
|
self.assert_series_equal(result, expected)
|
|
|
|
def test_compare_scalar(self, data, all_compare_operators):
|
|
op_name = all_compare_operators
|
|
s = pd.Series(data)
|
|
self._compare_other(s, data, op_name, "abc")
|
|
|
|
|
|
class TestParsing(base.BaseParsingTests):
|
|
pass
|
|
|
|
|
|
class TestPrinting(base.BasePrintingTests):
|
|
pass
|
|
|
|
|
|
class TestGroupBy(base.BaseGroupbyTests):
|
|
pass
|