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import pytest
import pandas as pd
import pandas._testing as tm
class BaseAccumulateTests:
"""
Accumulation specific tests. Generally these only
make sense for numeric/boolean operations.
"""
def _supports_accumulation(self, ser: pd.Series, op_name: str) -> bool:
# Do we expect this accumulation to be supported for this dtype?
# We default to assuming "no"; subclass authors should override here.
return False
def check_accumulate(self, ser: pd.Series, op_name: str, skipna: bool):
alt = ser.astype("float64")
result = getattr(ser, op_name)(skipna=skipna)
if result.dtype == pd.Float32Dtype() and op_name == "cumprod" and skipna:
# TODO: avoid special-casing here
pytest.skip(
f"Float32 precision lead to large differences with op {op_name} "
f"and skipna={skipna}"
)
expected = getattr(alt, op_name)(skipna=skipna)
tm.assert_series_equal(result, expected, check_dtype=False)
@pytest.mark.parametrize("skipna", [True, False])
def test_accumulate_series(self, data, all_numeric_accumulations, skipna):
op_name = all_numeric_accumulations
ser = pd.Series(data)
if self._supports_accumulation(ser, op_name):
self.check_accumulate(ser, op_name, skipna)
else:
with pytest.raises(NotImplementedError):
getattr(ser, op_name)(skipna=skipna)