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# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
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from distutils.version import LooseVersion
import unittest

import numpy as np
import pandas as pd

from pyspark import pandas as ps
from pyspark.testing.pandasutils import ComparisonTestBase
from pyspark.testing.sqlutils import SQLTestUtils


class FrameAnyAllMixin:
    @property
    def pdf(self):
        return pd.DataFrame(
            {"a": [1, 2, 3, 4, 5, 6, 7, 8, 9], "b": [4, 5, 6, 3, 2, 1, 0, 0, 0]},
            index=np.random.rand(9),
        )

    @property
    def df_pair(self):
        pdf = self.pdf
        psdf = ps.from_pandas(pdf)
        return pdf, psdf

    @unittest.skipIf(
        LooseVersion(pd.__version__) >= LooseVersion("2.0.0"),
        "TODO(SPARK-43812): Enable DataFrameTests.test_all for pandas 2.0.0.",
    )
    def test_all(self):
        pdf = pd.DataFrame(
            {
                "col1": [False, False, False],
                "col2": [True, False, False],
                "col3": [0, 0, 1],
                "col4": [0, 1, 2],
                "col5": [False, False, None],
                "col6": [True, False, None],
            },
            index=np.random.rand(3),
        )
        pdf.name = "x"
        psdf = ps.from_pandas(pdf)

        self.assert_eq(psdf.all(), pdf.all())
        self.assert_eq(psdf.all(bool_only=True), pdf.all(bool_only=True))
        self.assert_eq(psdf.all(bool_only=False), pdf.all(bool_only=False))
        self.assert_eq(psdf[["col5"]].all(bool_only=True), pdf[["col5"]].all(bool_only=True))
        self.assert_eq(psdf[["col5"]].all(bool_only=False), pdf[["col5"]].all(bool_only=False))

        columns = pd.MultiIndex.from_tuples(
            [
                ("a", "col1"),
                ("a", "col2"),
                ("a", "col3"),
                ("b", "col4"),
                ("b", "col5"),
                ("c", "col6"),
            ]
        )
        pdf.columns = columns
        psdf.columns = columns

        self.assert_eq(psdf.all(), pdf.all())
        self.assert_eq(psdf.all(bool_only=True), pdf.all(bool_only=True))
        self.assert_eq(psdf.all(bool_only=False), pdf.all(bool_only=False))

        columns.names = ["X", "Y"]
        pdf.columns = columns
        psdf.columns = columns

        self.assert_eq(psdf.all(), pdf.all())
        self.assert_eq(psdf.all(bool_only=True), pdf.all(bool_only=True))
        self.assert_eq(psdf.all(bool_only=False), pdf.all(bool_only=False))

        with self.assertRaisesRegex(
            NotImplementedError, 'axis should be either 0 or "index" currently.'
        ):
            psdf.all(axis=1)

        # Test skipna
        pdf = pd.DataFrame({"A": [True, True], "B": [1, np.nan], "C": [True, None]})
        pdf.name = "x"
        psdf = ps.from_pandas(pdf)
        self.assert_eq(psdf[["A", "B"]].all(skipna=False), pdf[["A", "B"]].all(skipna=False))
        self.assert_eq(psdf[["A", "C"]].all(skipna=False), pdf[["A", "C"]].all(skipna=False))
        self.assert_eq(psdf[["B", "C"]].all(skipna=False), pdf[["B", "C"]].all(skipna=False))
        self.assert_eq(psdf.all(skipna=False), pdf.all(skipna=False))
        self.assert_eq(psdf.all(skipna=True), pdf.all(skipna=True))
        self.assert_eq(psdf.all(), pdf.all())
        self.assert_eq(
            ps.DataFrame([np.nan]).all(skipna=False), pd.DataFrame([np.nan]).all(skipna=False)
        )
        self.assert_eq(ps.DataFrame([None]).all(skipna=True), pd.DataFrame([None]).all(skipna=True))

    def test_any(self):
        pdf = pd.DataFrame(
            {
                "col1": [False, False, False],
                "col2": [True, False, False],
                "col3": [0, 0, 1],
                "col4": [0, 1, 2],
                "col5": [False, False, None],
                "col6": [True, False, None],
            },
            index=np.random.rand(3),
        )
        pdf.name = "x"
        psdf = ps.from_pandas(pdf)

        self.assert_eq(psdf.any(), pdf.any())
        self.assert_eq(psdf.any(bool_only=True), pdf.any(bool_only=True))
        self.assert_eq(psdf.any(bool_only=False), pdf.any(bool_only=False))
        self.assert_eq(psdf[["col5"]].all(bool_only=True), pdf[["col5"]].all(bool_only=True))
        self.assert_eq(psdf[["col5"]].all(bool_only=False), pdf[["col5"]].all(bool_only=False))

        columns = pd.MultiIndex.from_tuples(
            [
                ("a", "col1"),
                ("a", "col2"),
                ("a", "col3"),
                ("b", "col4"),
                ("b", "col5"),
                ("c", "col6"),
            ]
        )
        pdf.columns = columns
        psdf.columns = columns

        self.assert_eq(psdf.any(), pdf.any())
        self.assert_eq(psdf.any(bool_only=True), pdf.any(bool_only=True))
        self.assert_eq(psdf.any(bool_only=False), pdf.any(bool_only=False))

        columns.names = ["X", "Y"]
        pdf.columns = columns
        psdf.columns = columns

        self.assert_eq(psdf.any(), pdf.any())
        self.assert_eq(psdf.any(bool_only=True), pdf.any(bool_only=True))
        self.assert_eq(psdf.any(bool_only=False), pdf.any(bool_only=False))

        with self.assertRaisesRegex(
            NotImplementedError, 'axis should be either 0 or "index" currently.'
        ):
            psdf.any(axis=1)


class FrameAnyAllTests(FrameAnyAllMixin, ComparisonTestBase, SQLTestUtils):
    pass


if __name__ == "__main__":
    from pyspark.pandas.tests.computation.test_any_all import *  # noqa: F401

    try:
        import xmlrunner

        testRunner = xmlrunner.XMLTestRunner(output="target/test-reports", verbosity=2)
    except ImportError:
        testRunner = None
    unittest.main(testRunner=testRunner, verbosity=2)