import operator
import pytest
@pytest.fixture
def dtype():
"""A fixture providing the ExtensionDtype to validate."""
raise NotImplementedError
@pytest.fixture
def data():
"""Length-100 array for this type.
* data[0] and data[1] should both be non missing
* data[0] and data[1] should not gbe equal
"""
raise NotImplementedError
@pytest.fixture
def data_missing():
"""Length-2 array with [NA, Valid]"""
raise NotImplementedError
@pytest.fixture(params=['data', 'data_missing'])
def all_data(request, data, data_missing):
"""Parametrized fixture giving 'data' and 'data_missing'"""
if request.param == 'data':
return data
elif request.param == 'data_missing':
return data_missing
@pytest.fixture
def data_repeated(data):
"""
Generate many datasets.
Parameters
----------
data : fixture implementing `data`
Returns
-------
Callable[[int], Generator]:
A callable that takes a `count` argument and
returns a generator yielding `count` datasets.
"""
def gen(count):
for _ in range(count):
yield data
return gen
@pytest.fixture
def data_for_sorting():
"""Length-3 array with a known sort order.
This should be three items [B, C, A] with
A < B < C
"""
raise NotImplementedError
@pytest.fixture
def data_missing_for_sorting():
"""Length-3 array with a known sort order.
This should be three items [B, NA, A] with
A < B and NA missing.
"""
raise NotImplementedError
@pytest.fixture
def na_cmp():
"""Binary operator for comparing NA values.
Should return a function of two arguments that returns
True if both arguments are (scalar) NA for your type.
By default, uses ``operator.is_``
"""
return operator.is_
@pytest.fixture
def na_value():
"""The scalar missing value for this type. Default 'None'"""
return None
@pytest.fixture
def data_for_grouping():
"""Data for factorization, grouping, and unique tests.
Expected to be like [B, B, NA, NA, A, A, B, C]
Where A < B < C and NA is missing
"""
raise NotImplementedError
@pytest.fixture(params=[True, False])
def box_in_series(request):
"""Whether to box the data in a Series"""
return request.param