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import pytest
import pandas as pd
from pandas import (
Index,
RangeIndex,
)
import pandas._testing as tm
from pandas.core.computation import expressions as expr
@pytest.fixture(autouse=True, params=[0, 1000000], ids=["numexpr", "python"])
def switch_numexpr_min_elements(request):
_MIN_ELEMENTS = expr._MIN_ELEMENTS
expr._MIN_ELEMENTS = request.param
yield request.param
expr._MIN_ELEMENTS = _MIN_ELEMENTS
# ------------------------------------------------------------------
# doctest with +SKIP for one fixture fails during setup with
# 'DoctestItem' object has no attribute 'callspec'
# due to switch_numexpr_min_elements fixture
@pytest.fixture(params=[1, np.array(1, dtype=np.int64)])
def one(request):
"""
Several variants of integer value 1. The zero-dim integer array
behaves like an integer.
This fixture can be used to check that datetimelike indexes handle
addition and subtraction of integers and zero-dimensional arrays
of integers.
Examples
--------
dti = pd.date_range('2016-01-01', periods=2, freq='H')
dti
DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 01:00:00'],
dtype='datetime64[ns]', freq='H')
dti + one
DatetimeIndex(['2016-01-01 01:00:00', '2016-01-01 02:00:00'],
dtype='datetime64[ns]', freq='H')
"""
return request.param
zeros = [
box_cls([0] * 5, dtype=dtype)
for box_cls in [Index, np.array, pd.array]
for dtype in [np.int64, np.uint64, np.float64]
]
zeros.extend([box_cls([-0.0] * 5, dtype=np.float64) for box_cls in [Index, np.array]])
zeros.extend([np.array(0, dtype=dtype) for dtype in [np.int64, np.uint64, np.float64]])
zeros.extend([np.array(-0.0, dtype=np.float64)])
zeros.extend([0, 0.0, -0.0])
# doctest with +SKIP for zero fixture fails during setup with
# 'DoctestItem' object has no attribute 'callspec'
# due to switch_numexpr_min_elements fixture
@pytest.fixture(params=zeros)
def zero(request):
"""
Several types of scalar zeros and length 5 vectors of zeros.
This fixture can be used to check that numeric-dtype indexes handle
division by any zero numeric-dtype.
Uses vector of length 5 for broadcasting with `numeric_idx` fixture,
which creates numeric-dtype vectors also of length 5.
Examples
--------
arr = RangeIndex(5)
arr / zeros
Index([nan, inf, inf, inf, inf], dtype='float64')
"""
return request.param
# ------------------------------------------------------------------
# Vector Fixtures
@pytest.fixture(
params=[
# TODO: add more dtypes here
Index(np.arange(5, dtype="float64")),
Index(np.arange(5, dtype="int64")),
Index(np.arange(5, dtype="uint64")),
RangeIndex(5),
],
ids=lambda x: type(x).__name__,
)
def numeric_idx(request):
"""
Several types of numeric-dtypes Index objects
"""
return request.param
# ------------------------------------------------------------------
# Scalar Fixtures
@pytest.fixture(
params=[
pd.Timedelta("10m7s").to_pytimedelta(),
pd.Timedelta("10m7s"),
pd.Timedelta("10m7s").to_timedelta64(),
],
ids=lambda x: type(x).__name__,
)
def scalar_td(request):
"""
Several variants of Timedelta scalars representing 10 minutes and 7 seconds.
"""
return request.param
@pytest.fixture(
params=[
pd.offsets.Day(3),
pd.offsets.Hour(72),
pd.Timedelta(days=3).to_pytimedelta(),
pd.Timedelta("72:00:00"),
np.timedelta64(3, "D"),
np.timedelta64(72, "h"),
],
ids=lambda x: type(x).__name__,
)
def three_days(request):
"""
Several timedelta-like and DateOffset objects that each represent
a 3-day timedelta
"""
return request.param
@pytest.fixture(
params=[
pd.offsets.Hour(2),
pd.offsets.Minute(120),
pd.Timedelta(hours=2).to_pytimedelta(),
pd.Timedelta(seconds=2 * 3600),
np.timedelta64(2, "h"),
np.timedelta64(120, "m"),
],
ids=lambda x: type(x).__name__,
)
def two_hours(request):
"""
Several timedelta-like and DateOffset objects that each represent
a 2-hour timedelta
"""
return request.param
_common_mismatch = [
pd.offsets.YearBegin(2),
pd.offsets.MonthBegin(1),
pd.offsets.Minute(),
]
@pytest.fixture(
params=[
pd.Timedelta(minutes=30).to_pytimedelta(),
np.timedelta64(30, "s"),
pd.Timedelta(seconds=30),
]
+ _common_mismatch
)
def not_hourly(request):
"""
Several timedelta-like and DateOffset instances that are _not_
compatible with Hourly frequencies.
"""
return request.param
@pytest.fixture(
params=[
np.timedelta64(4, "h"),
pd.Timedelta(hours=23).to_pytimedelta(),
pd.Timedelta("23:00:00"),
]
+ _common_mismatch
)
def not_daily(request):
"""
Several timedelta-like and DateOffset instances that are _not_
compatible with Daily frequencies.
"""
return request.param
@pytest.fixture(
params=[
np.timedelta64(365, "D"),
pd.Timedelta(days=365).to_pytimedelta(),
pd.Timedelta(days=365),
]
+ _common_mismatch
)
def mismatched_freq(request):
"""
Several timedelta-like and DateOffset instances that are _not_
compatible with Monthly or Annual frequencies.
"""
return request.param
# ------------------------------------------------------------------
@pytest.fixture(
params=[Index, pd.Series, tm.to_array, np.array, list], ids=lambda x: x.__name__
)
def box_1d_array(request):
"""
Fixture to test behavior for Index, Series, tm.to_array, numpy Array and list
classes
"""
return request.param
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