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python/cudf/cudf_pandas_tests/test_cudf_pandas_no_fallback.py
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# SPDX-FileCopyrightText: Copyright (c) 2024, NVIDIA CORPORATION & AFFILIATES. | ||
# All rights reserved. | ||
# SPDX-License-Identifier: Apache-2.0 | ||
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import pytest | ||
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from cudf.pandas import LOADED | ||
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if not LOADED: | ||
raise ImportError("These tests must be run with cudf.pandas loaded") | ||
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import numpy as np | ||
import pandas as pd | ||
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@pytest.fixture(autouse=True) | ||
def fail_on_fallback(monkeypatch): | ||
monkeypatch.setenv("CUDF_PANDAS_FAIL_ON_FALLBACK", "True") | ||
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@pytest.fixture | ||
def dataframe(): | ||
df = pd.DataFrame( | ||
{ | ||
"a": [1, 1, 1, 2, 3], | ||
"b": [1, 2, 3, 4, 5], | ||
"c": [1.2, 1.3, 1.5, 1.7, 1.11], | ||
} | ||
) | ||
return df | ||
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@pytest.fixture | ||
def series(dataframe): | ||
return dataframe["a"] | ||
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@pytest.fixture | ||
def array(series): | ||
return series.values | ||
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@pytest.mark.parametrize( | ||
"op", | ||
[ | ||
"sum", | ||
"min", | ||
"max", | ||
"mean", | ||
"std", | ||
"var", | ||
"prod", | ||
"median", | ||
], | ||
) | ||
def test_no_fallback_in_reduction_ops(series, op): | ||
s = series | ||
getattr(s, op)() | ||
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def test_groupby(dataframe): | ||
df = dataframe | ||
df.groupby("a", sort=True).max() | ||
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def test_no_fallback_in_binops(dataframe): | ||
df = dataframe | ||
df + df | ||
df - df | ||
df * df | ||
df**df | ||
df[["a", "b"]] & df[["a", "b"]] | ||
df <= df | ||
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def test_no_fallback_in_groupby_rolling_sum(dataframe): | ||
df = dataframe | ||
df.groupby("a").rolling(2).sum() | ||
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def test_no_fallback_in_concat(dataframe): | ||
df = dataframe | ||
pd.concat([df, df]) | ||
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def test_no_fallback_in_get_shape(dataframe): | ||
df = dataframe | ||
df.shape | ||
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def test_no_fallback_in_array_ufunc_op(array): | ||
np.add(array, array) | ||
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def test_no_fallback_in_merge(dataframe): | ||
df = dataframe | ||
pd.merge(df * df, df + df, how="inner") | ||
pd.merge(df * df, df + df, how="outer") | ||
pd.merge(df * df, df + df, how="left") | ||
pd.merge(df * df, df + df, how="right") |