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import numpy as np
import pytest
import pandas as pd
from pandas.core.arrays.integer import (
Int8Dtype,
Int16Dtype,
Int32Dtype,
Int64Dtype,
UInt8Dtype,
UInt16Dtype,
UInt32Dtype,
UInt64Dtype,
)
@pytest.fixture(
params=[
Int8Dtype,
Int16Dtype,
Int32Dtype,
Int64Dtype,
UInt8Dtype,
UInt16Dtype,
UInt32Dtype,
UInt64Dtype,
]
)
def dtype(request):
"""Parametrized fixture returning integer 'dtype'"""
return request.param()
@pytest.fixture
def data(dtype):
"""
Fixture returning 'data' array with valid and missing values according to
parametrized integer 'dtype'.
Used to test dtype conversion with and without missing values.
"""
return pd.array(
list(range(8)) + [np.nan] + list(range(10, 98)) + [np.nan] + [99, 100],
dtype=dtype,
)
@pytest.fixture
def data_missing(dtype):
"""
Fixture returning array with exactly one NaN and one valid integer,
according to parametrized integer 'dtype'.
Used to test dtype conversion with and without missing values.
"""
return pd.array([np.nan, 1], dtype=dtype)
@pytest.fixture(params=["data", "data_missing"])
def all_data(request, data, data_missing):
"""Parametrized fixture returning 'data' or 'data_missing' integer arrays.
Used to test dtype conversion with and without missing values.
"""
if request.param == "data":
return data
elif request.param == "data_missing":
return data_missing
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