import numpy as np
import pytest

import pandas as pd
import pandas.util.testing as tm

# ------------------------------------------------------------------
# Helper Functions


def id_func(x):
    if isinstance(x, tuple):
        assert len(x) == 2
        return x[0].__name__ + "-" + str(x[1])
    else:
        return x.__name__


# ------------------------------------------------------------------


@pytest.fixture(params=[1, np.array(1, dtype=np.int64)])
def one(request):
    # zero-dim integer array behaves like an integer
    return request.param


zeros = [
    box_cls([0] * 5, dtype=dtype)
    for box_cls in [pd.Index, np.array]
    for dtype in [np.int64, np.uint64, np.float64]
]
zeros.extend(
    [box_cls([-0.0] * 5, dtype=np.float64) for box_cls in [pd.Index, np.array]]
)
zeros.extend([np.array(0, dtype=dtype) for dtype in [np.int64, np.uint64, np.float64]])
zeros.extend([np.array(-0.0, dtype=np.float64)])
zeros.extend([0, 0.0, -0.0])


@pytest.fixture(params=zeros)
def zero(request):
    # For testing division by (or of) zero for Index with length 5, this
    # gives several scalar-zeros and length-5 vector-zeros
    return request.param


# ------------------------------------------------------------------
# Vector Fixtures


@pytest.fixture(
    params=[
        pd.Float64Index(np.arange(5, dtype="float64")),
        pd.Int64Index(np.arange(5, dtype="int64")),
        pd.UInt64Index(np.arange(5, dtype="uint64")),
        pd.RangeIndex(5),
    ],
    ids=lambda x: type(x).__name__,
)
def numeric_idx(request):
    """
    Several types of numeric-dtypes Index objects
    """
    return request.param


# ------------------------------------------------------------------
# Scalar Fixtures


@pytest.fixture(
    params=[
        pd.Timedelta("5m4s").to_pytimedelta(),
        pd.Timedelta("5m4s"),
        pd.Timedelta("5m4s").to_timedelta64(),
    ],
    ids=lambda x: type(x).__name__,
)
def scalar_td(request):
    """
    Several variants of Timedelta scalars representing 5 minutes and 4 seconds
    """
    return request.param


@pytest.fixture(
    params=[
        pd.offsets.Day(3),
        pd.offsets.Hour(72),
        pd.Timedelta(days=3).to_pytimedelta(),
        pd.Timedelta("72:00:00"),
        np.timedelta64(3, "D"),
        np.timedelta64(72, "h"),
    ],
    ids=lambda x: type(x).__name__,
)
def three_days(request):
    """
    Several timedelta-like and DateOffset objects that each represent
    a 3-day timedelta
    """
    return request.param


@pytest.fixture(
    params=[
        pd.offsets.Hour(2),
        pd.offsets.Minute(120),
        pd.Timedelta(hours=2).to_pytimedelta(),
        pd.Timedelta(seconds=2 * 3600),
        np.timedelta64(2, "h"),
        np.timedelta64(120, "m"),
    ],
    ids=lambda x: type(x).__name__,
)
def two_hours(request):
    """
    Several timedelta-like and DateOffset objects that each represent
    a 2-hour timedelta
    """
    return request.param


_common_mismatch = [
    pd.offsets.YearBegin(2),
    pd.offsets.MonthBegin(1),
    pd.offsets.Minute(),
]


@pytest.fixture(
    params=[
        pd.Timedelta(minutes=30).to_pytimedelta(),
        np.timedelta64(30, "s"),
        pd.Timedelta(seconds=30),
    ]
    + _common_mismatch
)
def not_hourly(request):
    """
    Several timedelta-like and DateOffset instances that are _not_
    compatible with Hourly frequencies.
    """
    return request.param


@pytest.fixture(
    params=[
        np.timedelta64(4, "h"),
        pd.Timedelta(hours=23).to_pytimedelta(),
        pd.Timedelta("23:00:00"),
    ]
    + _common_mismatch
)
def not_daily(request):
    """
    Several timedelta-like and DateOffset instances that are _not_
    compatible with Daily frequencies.
    """
    return request.param


@pytest.fixture(
    params=[
        np.timedelta64(365, "D"),
        pd.Timedelta(days=365).to_pytimedelta(),
        pd.Timedelta(days=365),
    ]
    + _common_mismatch
)
def mismatched_freq(request):
    """
    Several timedelta-like and DateOffset instances that are _not_
    compatible with Monthly or Annual frequencies.
    """
    return request.param


# ------------------------------------------------------------------


@pytest.fixture(params=[pd.Index, pd.Series, pd.DataFrame], ids=id_func)
def box(request):
    """
    Several array-like containers that should have effectively identical
    behavior with respect to arithmetic operations.
    """
    return request.param


@pytest.fixture(
    params=[pd.Index, pd.Series, pytest.param(pd.DataFrame, marks=pytest.mark.xfail)],
    ids=id_func,
)
def box_df_fail(request):
    """
    Fixture equivalent to `box` fixture but xfailing the DataFrame case.
    """
    return request.param


@pytest.fixture(
    params=[
        (pd.Index, False),
        (pd.Series, False),
        (pd.DataFrame, False),
        pytest.param((pd.DataFrame, True), marks=pytest.mark.xfail),
    ],
    ids=id_func,
)
def box_transpose_fail(request):
    """
    Fixture similar to `box` but testing both transpose cases for DataFrame,
    with the tranpose=True case xfailed.
    """
    # GH#23620
    return request.param


@pytest.fixture(params=[pd.Index, pd.Series, pd.DataFrame, tm.to_array], ids=id_func)
def box_with_array(request):
    """
    Fixture to test behavior for Index, Series, DataFrame, and pandas Array
    classes
    """
    return request.param


# alias so we can use the same fixture for multiple parameters in a test
box_with_array2 = box_with_array