"""
Tests that apply to all groupby operation methods.

The only tests that should appear here are those that use the `groupby_func` fixture.
Even if it does use that fixture, prefer a more specific test file if it available
such as:

 - test_categorical
 - test_groupby_dropna
 - test_groupby_subclass
 - test_raises
"""

import pytest

from pandas.errors import Pandas4Warning

import pandas as pd
from pandas import DataFrame
import pandas._testing as tm
from pandas.tests.groupby import get_groupby_method_args


def test_multiindex_group_all_columns_when_empty(groupby_func):
    # GH 32464
    df = DataFrame({"a": [], "b": [], "c": []}).set_index(["a", "b", "c"])
    gb = df.groupby(["a", "b", "c"], group_keys=True)
    method = getattr(gb, groupby_func)
    args = get_groupby_method_args(groupby_func, df)
    if groupby_func == "corrwith":
        warn = Pandas4Warning
        warn_msg = "DataFrameGroupBy.corrwith is deprecated"
    else:
        warn = None
        warn_msg = ""
    with tm.assert_produces_warning(warn, match=warn_msg):
        result = method(*args).index
    expected = df.index
    tm.assert_index_equal(result, expected)


def test_duplicate_columns(request, groupby_func, as_index):
    # GH#50806
    if groupby_func == "corrwith":
        msg = "GH#50845 - corrwith fails when there are duplicate columns"
        request.applymarker(pytest.mark.xfail(reason=msg))
    df = DataFrame([[1, 3, 6], [1, 4, 7], [2, 5, 8]], columns=list("abb"))
    args = get_groupby_method_args(groupby_func, df)
    gb = df.groupby("a", as_index=as_index)
    result = getattr(gb, groupby_func)(*args)

    expected_df = df.set_axis(["a", "b", "c"], axis=1)
    expected_args = get_groupby_method_args(groupby_func, expected_df)
    expected_gb = expected_df.groupby("a", as_index=as_index)
    expected = getattr(expected_gb, groupby_func)(*expected_args)
    if groupby_func not in ("size", "ngroup", "cumcount"):
        expected = expected.rename(columns={"c": "b"})
    tm.assert_equal(result, expected)


@pytest.mark.parametrize(
    "idx",
    [
        pd.Index(["a", "a"], name="foo"),
        pd.MultiIndex.from_tuples((("a", "a"), ("a", "a")), names=["foo", "bar"]),
    ],
)
def test_dup_labels_output_shape(groupby_func, idx):
    if groupby_func in {"size", "ngroup", "cumcount"}:
        pytest.skip(f"Not applicable for {groupby_func}")

    df = DataFrame([[1, 1]], columns=idx)
    grp_by = df.groupby([0])

    args = get_groupby_method_args(groupby_func, df)
    if groupby_func == "corrwith":
        warn = Pandas4Warning
        warn_msg = "DataFrameGroupBy.corrwith is deprecated"
    else:
        warn = None
        warn_msg = ""
    with tm.assert_produces_warning(warn, match=warn_msg):
        result = getattr(grp_by, groupby_func)(*args)

    assert result.shape == (1, 2)
    tm.assert_index_equal(result.columns, idx)


def test_not_c_contiguous_mask(groupby_func):
    # https://github.com/pandas-dev/pandas/issues/61031
    if groupby_func == "corrwith":
        # corrwith is deprecated
        return
    df = DataFrame({"a": [1, 1, 2], "b": [3, 4, 5]}, dtype="Int64")
    reversed = DataFrame(
        {"a": [2, 1, 1], "b": [5, 4, 3]}, dtype="Int64", index=[2, 1, 0]
    )[::-1]
    assert not reversed["b"].array._mask.flags["C_CONTIGUOUS"]
    args = get_groupby_method_args(groupby_func, df)

    gb_reversed = reversed.groupby("a")
    result = getattr(gb_reversed, groupby_func)(*args)
    gb = df.groupby("a")
    expected = getattr(gb, groupby_func)(*args)
    tm.assert_equal(result, expected)