projektAI/venv/Lib/site-packages/pandas/tests/extension/conftest.py

184 lines
3.7 KiB
Python
Raw Normal View History

2021-06-06 22:13:05 +02:00
import operator
import pytest
from pandas import Series
@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 be equal
"""
raise NotImplementedError
@pytest.fixture
def data_for_twos():
"""Length-100 array in which all the elements are two."""
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
@pytest.fixture(
params=[
lambda x: 1,
lambda x: [1] * len(x),
lambda x: Series([1] * len(x)),
lambda x: x,
],
ids=["scalar", "list", "series", "object"],
)
def groupby_apply_op(request):
"""
Functions to test groupby.apply().
"""
return request.param
@pytest.fixture(params=[True, False])
def as_frame(request):
"""
Boolean fixture to support Series and Series.to_frame() comparison testing.
"""
return request.param
@pytest.fixture(params=[True, False])
def as_series(request):
"""
Boolean fixture to support arr and Series(arr) comparison testing.
"""
return request.param
@pytest.fixture(params=[True, False])
def use_numpy(request):
"""
Boolean fixture to support comparison testing of ExtensionDtype array
and numpy array.
"""
return request.param
@pytest.fixture(params=["ffill", "bfill"])
def fillna_method(request):
"""
Parametrized fixture giving method parameters 'ffill' and 'bfill' for
Series.fillna(method=<method>) testing.
"""
return request.param
@pytest.fixture(params=[True, False])
def as_array(request):
"""
Boolean fixture to support ExtensionDtype _from_sequence method testing.
"""
return request.param