import numpy as np
import pytest

import pandas as pd
from pandas import (
    Categorical,
    DataFrame,
    Series,
)
import pandas._testing as tm


def _assert_series_equal_both(a, b, **kwargs):
    """
    Check that two Series equal.

    This check is performed commutatively.

    Parameters
    ----------
    a : Series
        The first Series to compare.
    b : Series
        The second Series to compare.
    kwargs : dict
        The arguments passed to `tm.assert_series_equal`.
    """
    tm.assert_series_equal(a, b, **kwargs)
    tm.assert_series_equal(b, a, **kwargs)


def _assert_not_series_equal(a, b, **kwargs):
    """
    Check that two Series are not equal.

    Parameters
    ----------
    a : Series
        The first Series to compare.
    b : Series
        The second Series to compare.
    kwargs : dict
        The arguments passed to `tm.assert_series_equal`.
    """
    try:
        tm.assert_series_equal(a, b, **kwargs)
        msg = "The two Series were equal when they shouldn't have been"

        pytest.fail(msg=msg)
    except AssertionError:
        pass


def _assert_not_series_equal_both(a, b, **kwargs):
    """
    Check that two Series are not equal.

    This check is performed commutatively.

    Parameters
    ----------
    a : Series
        The first Series to compare.
    b : Series
        The second Series to compare.
    kwargs : dict
        The arguments passed to `tm.assert_series_equal`.
    """
    _assert_not_series_equal(a, b, **kwargs)
    _assert_not_series_equal(b, a, **kwargs)


@pytest.mark.parametrize("data", [range(3), list("abc"), list("áàä")])
def test_series_equal(data):
    _assert_series_equal_both(Series(data), Series(data))


@pytest.mark.parametrize(
    "data1,data2",
    [
        (range(3), range(1, 4)),
        (list("abc"), list("xyz")),
        (list("áàä"), list("éèë")),
        (list("áàä"), list(b"aaa")),
        (range(3), range(4)),
    ],
)
def test_series_not_equal_value_mismatch(data1, data2):
    _assert_not_series_equal_both(Series(data1), Series(data2))


@pytest.mark.parametrize(
    "kwargs",
    [
        {"dtype": "float64"},  # dtype mismatch
        {"index": [1, 2, 4]},  # index mismatch
        {"name": "foo"},  # name mismatch
    ],
)
def test_series_not_equal_metadata_mismatch(kwargs):
    data = range(3)
    s1 = Series(data)

    s2 = Series(data, **kwargs)
    _assert_not_series_equal_both(s1, s2)


@pytest.mark.parametrize("data1,data2", [(0.12345, 0.12346), (0.1235, 0.1236)])
@pytest.mark.parametrize("decimals", [0, 1, 2, 3, 5, 10])
def test_less_precise(data1, data2, any_float_dtype, decimals):
    rtol = 10**-decimals
    s1 = Series([data1], dtype=any_float_dtype)
    s2 = Series([data2], dtype=any_float_dtype)

    if decimals in (5, 10) or (decimals >= 3 and abs(data1 - data2) >= 0.0005):
        msg = "Series values are different"
        with pytest.raises(AssertionError, match=msg):
            tm.assert_series_equal(s1, s2, rtol=rtol)
    else:
        _assert_series_equal_both(s1, s2, rtol=rtol)


@pytest.mark.parametrize(
    "s1,s2,msg",
    [
        # Index
        (
            Series(["l1", "l2"], index=[1, 2]),
            Series(["l1", "l2"], index=[1.0, 2.0]),
            "Series\\.index are different",
        ),
        # MultiIndex
        (
            DataFrame.from_records(
                {"a": [1, 2], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
            ).c,
            DataFrame.from_records(
                {"a": [1.0, 2.0], "b": [2.1, 1.5], "c": ["l1", "l2"]}, index=["a", "b"]
            ).c,
            "Series\\.index level \\[0\\] are different",
        ),
    ],
)
def test_series_equal_index_dtype(s1, s2, msg, check_index_type):
    kwargs = {"check_index_type": check_index_type}

    if check_index_type:
        with pytest.raises(AssertionError, match=msg):
            tm.assert_series_equal(s1, s2, **kwargs)
    else:
        tm.assert_series_equal(s1, s2, **kwargs)


@pytest.mark.parametrize("check_like", [True, False])
def test_series_equal_order_mismatch(check_like):
    s1 = Series([1, 2, 3], index=["a", "b", "c"])
    s2 = Series([3, 2, 1], index=["c", "b", "a"])

    if not check_like:  # Do not ignore index ordering.
        with pytest.raises(AssertionError, match="Series.index are different"):
            tm.assert_series_equal(s1, s2, check_like=check_like)
    else:
        _assert_series_equal_both(s1, s2, check_like=check_like)


@pytest.mark.parametrize("check_index", [True, False])
def test_series_equal_index_mismatch(check_index):
    s1 = Series([1, 2, 3], index=["a", "b", "c"])
    s2 = Series([1, 2, 3], index=["c", "b", "a"])

    if check_index:  # Do not ignore index.
        with pytest.raises(AssertionError, match="Series.index are different"):
            tm.assert_series_equal(s1, s2, check_index=check_index)
    else:
        _assert_series_equal_both(s1, s2, check_index=check_index)


def test_series_invalid_param_combination():
    left = Series(dtype=object)
    right = Series(dtype=object)
    with pytest.raises(
        ValueError, match="check_like must be False if check_index is False"
    ):
        tm.assert_series_equal(left, right, check_index=False, check_like=True)


def test_series_equal_length_mismatch(rtol):
    msg = """Series are different

Series length are different
\\[left\\]:  3, RangeIndex\\(start=0, stop=3, step=1\\)
\\[right\\]: 4, RangeIndex\\(start=0, stop=4, step=1\\)"""

    s1 = Series([1, 2, 3])
    s2 = Series([1, 2, 3, 4])

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s1, s2, rtol=rtol)


def test_series_equal_numeric_values_mismatch(rtol):
    msg = """Series are different

Series values are different \\(33\\.33333 %\\)
\\[index\\]: \\[0, 1, 2\\]
\\[left\\]:  \\[1, 2, 3\\]
\\[right\\]: \\[1, 2, 4\\]"""

    s1 = Series([1, 2, 3])
    s2 = Series([1, 2, 4])

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s1, s2, rtol=rtol)


def test_series_equal_categorical_values_mismatch(rtol, using_infer_string):
    dtype = "str" if using_infer_string else "object"
    msg = f"""Series are different

Series values are different \\(66\\.66667 %\\)
\\[index\\]: \\[0, 1, 2\\]
\\[left\\]:  \\['a', 'b', 'c'\\]
Categories \\(3, {dtype}\\): \\['a', 'b', 'c'\\]
\\[right\\]: \\['a', 'c', 'b'\\]
Categories \\(3, {dtype}\\): \\['a', 'b', 'c'\\]"""

    s1 = Series(Categorical(["a", "b", "c"]))
    s2 = Series(Categorical(["a", "c", "b"]))

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s1, s2, rtol=rtol)


def test_series_equal_datetime_values_mismatch(rtol):
    msg = """Series are different

Series values are different \\(100.0 %\\)
\\[index\\]: \\[0, 1, 2\\]
\\[left\\]:  \\[1514764800000000000, 1514851200000000000, 1514937600000000000\\]
\\[right\\]: \\[1549065600000000000, 1549152000000000000, 1549238400000000000\\]"""

    s1 = Series(pd.date_range("2018-01-01", periods=3, freq="D", unit="ns"))
    s2 = Series(pd.date_range("2019-02-02", periods=3, freq="D", unit="ns"))

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s1, s2, rtol=rtol)


def test_series_equal_categorical_mismatch(check_categorical, using_infer_string):
    if using_infer_string:
        dtype = "str"
    else:
        dtype = "object"
    msg = f"""Attributes of Series are different

Attribute "dtype" are different
\\[left\\]:  CategoricalDtype\\(categories=\\['a', 'b'\\], ordered=False, \
categories_dtype={dtype}\\)
\\[right\\]: CategoricalDtype\\(categories=\\['a', 'b', 'c'\\], \
ordered=False, categories_dtype={dtype}\\)"""

    s1 = Series(Categorical(["a", "b"]))
    s2 = Series(Categorical(["a", "b"], categories=list("abc")))

    if check_categorical:
        with pytest.raises(AssertionError, match=msg):
            tm.assert_series_equal(s1, s2, check_categorical=check_categorical)
    else:
        _assert_series_equal_both(s1, s2, check_categorical=check_categorical)


def test_assert_series_equal_extension_dtype_mismatch():
    # https://github.com/pandas-dev/pandas/issues/32747
    left = Series(pd.array([1, 2, 3], dtype="Int64"))
    right = left.astype(int)

    msg = """Attributes of Series are different

Attribute "dtype" are different
\\[left\\]:  Int64
\\[right\\]: int[32|64]"""

    tm.assert_series_equal(left, right, check_dtype=False)

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(left, right, check_dtype=True)


def test_assert_series_equal_interval_dtype_mismatch():
    # https://github.com/pandas-dev/pandas/issues/32747
    left = Series([pd.Interval(0, 1)], dtype="interval")
    right = left.astype(object)

    msg = """Attributes of Series are different

Attribute "dtype" are different
\\[left\\]:  interval\\[int64, right\\]
\\[right\\]: object"""

    tm.assert_series_equal(left, right, check_dtype=False)

    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(left, right, check_dtype=True)


def test_series_equal_series_type():
    class MySeries(Series):
        pass

    s1 = Series([1, 2])
    s2 = Series([1, 2])
    s3 = MySeries([1, 2])

    tm.assert_series_equal(s1, s2, check_series_type=False)
    tm.assert_series_equal(s1, s2, check_series_type=True)

    tm.assert_series_equal(s1, s3, check_series_type=False)
    tm.assert_series_equal(s3, s1, check_series_type=False)

    with pytest.raises(AssertionError, match="Series classes are different"):
        tm.assert_series_equal(s1, s3, check_series_type=True)

    with pytest.raises(AssertionError, match="Series classes are different"):
        tm.assert_series_equal(s3, s1, check_series_type=True)


def test_series_equal_exact_for_nonnumeric():
    # https://github.com/pandas-dev/pandas/issues/35446
    s1 = Series(["a", "b"])
    s2 = Series(["a", "b"])
    s3 = Series(["b", "a"])

    tm.assert_series_equal(s1, s2, check_exact=True)
    tm.assert_series_equal(s2, s1, check_exact=True)

    msg = """Series are different

Series values are different \\(100\\.0 %\\)
\\[index\\]: \\[0, 1\\]
\\[left\\]:  \\[a, b\\]
\\[right\\]: \\[b, a\\]"""
    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s1, s3, check_exact=True)

    msg = """Series are different

Series values are different \\(100\\.0 %\\)
\\[index\\]: \\[0, 1\\]
\\[left\\]:  \\[b, a\\]
\\[right\\]: \\[a, b\\]"""
    with pytest.raises(AssertionError, match=msg):
        tm.assert_series_equal(s3, s1, check_exact=True)


def test_assert_series_equal_ignore_extension_dtype_mismatch():
    # https://github.com/pandas-dev/pandas/issues/35715
    left = Series([1, 2, 3], dtype="Int64")
    right = Series([1, 2, 3], dtype="Int32")
    tm.assert_series_equal(left, right, check_dtype=False)


def test_assert_series_equal_ignore_extension_dtype_mismatch_cross_class():
    # https://github.com/pandas-dev/pandas/issues/35715
    left = Series([1, 2, 3], dtype="Int64")
    right = Series([1, 2, 3], dtype="int64")
    tm.assert_series_equal(left, right, check_dtype=False)


def test_allows_duplicate_labels():
    left = Series([1])
    right = Series([1]).set_flags(allows_duplicate_labels=False)
    tm.assert_series_equal(left, left)
    tm.assert_series_equal(right, right)
    tm.assert_series_equal(left, right, check_flags=False)
    tm.assert_series_equal(right, left, check_flags=False)

    with pytest.raises(AssertionError, match="<Flags"):
        tm.assert_series_equal(left, right)

    with pytest.raises(AssertionError, match="<Flags"):
        tm.assert_series_equal(left, right)


def test_assert_series_equal_identical_na(nulls_fixture):
    ser = Series([nulls_fixture])

    tm.assert_series_equal(ser, ser.copy())

    # while we're here do Index too
    idx = pd.Index(ser)
    tm.assert_index_equal(idx, idx.copy(deep=True))


def test_identical_nested_series_is_equal():
    # GH#22400
    x = Series(
        [
            0,
            0.0131142231938,
            1.77774652865e-05,
            np.array([0.4722720840328748, 0.4216929783681722]),
        ]
    )
    y = Series(
        [
            0,
            0.0131142231938,
            1.77774652865e-05,
            np.array([0.4722720840328748, 0.4216929783681722]),
        ]
    )
    # These two arrays should be equal, nesting could cause issue

    tm.assert_series_equal(x, x)
    tm.assert_series_equal(x, x, check_exact=True)
    tm.assert_series_equal(x, y)
    tm.assert_series_equal(x, y, check_exact=True)


@pytest.mark.parametrize("dtype", ["datetime64", "timedelta64"])
def test_check_dtype_false_different_reso(dtype):
    # GH 52449
    ser_s = Series([1000213, 2131232, 21312331]).astype(f"{dtype}[s]")
    ser_ms = ser_s.astype(f"{dtype}[ms]")
    with pytest.raises(AssertionError, match="Attributes of Series are different"):
        tm.assert_series_equal(ser_s, ser_ms)
    tm.assert_series_equal(ser_ms, ser_s, check_dtype=False)

    ser_ms -= Series([1, 1, 1]).astype(f"{dtype}[ms]")

    with pytest.raises(AssertionError, match="Series are different"):
        tm.assert_series_equal(ser_s, ser_ms)

    with pytest.raises(AssertionError, match="Series are different"):
        tm.assert_series_equal(ser_s, ser_ms, check_dtype=False)


@pytest.mark.parametrize("dtype", ["Int64", "int64"])
def test_large_unequal_ints(dtype):
    # https://github.com/pandas-dev/pandas/issues/55882
    left = Series([1577840521123000], dtype=dtype)
    right = Series([1577840521123543], dtype=dtype)
    with pytest.raises(AssertionError, match="Series are different"):
        tm.assert_series_equal(left, right)


@pytest.mark.parametrize("dtype", [None, object])
@pytest.mark.parametrize("check_exact", [True, False])
@pytest.mark.parametrize("val", [3, 3.5])
def test_ea_and_numpy_no_dtype_check(val, check_exact, dtype):
    # GH#56651
    left = Series([1, 2, val], dtype=dtype)
    right = Series(pd.array([1, 2, val]))
    tm.assert_series_equal(left, right, check_dtype=False, check_exact=check_exact)


def test_assert_series_equal_int_tol():
    # GH#56646
    left = Series([81, 18, 121, 38, 74, 72, 81, 81, 146, 81, 81, 170, 74, 74])
    right = Series([72, 9, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72, 72])
    tm.assert_series_equal(left, right, rtol=1.5)

    tm.assert_frame_equal(left.to_frame(), right.to_frame(), rtol=1.5)
    tm.assert_extension_array_equal(
        left.astype("Int64").values, right.astype("Int64").values, rtol=1.5
    )


@pytest.mark.parametrize(
    "left_idx, right_idx",
    [
        (
            pd.Index([0, 0.2, 0.4, 0.6, 0.8, 1]),
            pd.Index(np.linspace(0, 1, 6)),
        ),
        (
            pd.MultiIndex.from_arrays([[0, 0, 0, 0, 1, 1], [0, 0.2, 0.4, 0.6, 0.8, 1]]),
            pd.MultiIndex.from_arrays([[0, 0, 0, 0, 1, 1], np.linspace(0, 1, 6)]),
        ),
        (
            pd.MultiIndex.from_arrays(
                [["a", "a", "a", "b", "b", "b"], [1, 2, 3, 4, 5, 10000000000001]]
            ),
            pd.MultiIndex.from_arrays(
                [["a", "a", "a", "b", "b", "b"], [1, 2, 3, 4, 5, 10000000000002]]
            ),
        ),
        pytest.param(
            pd.Index([1, 2, 3, 4, 5, 10000000000001]),
            pd.Index([1, 2, 3, 4, 5, 10000000000002]),
            marks=pytest.mark.xfail(reason="check_exact_index defaults to True"),
        ),
        pytest.param(
            pd.MultiIndex.from_arrays(
                [[0, 0, 0, 0, 1, 1], [1, 2, 3, 4, 5, 10000000000001]]
            ),
            pd.MultiIndex.from_arrays(
                [[0, 0, 0, 0, 1, 1], [1, 2, 3, 4, 5, 10000000000002]]
            ),
            marks=pytest.mark.xfail(reason="check_exact_index defaults to True"),
        ),
    ],
)
def test_assert_series_equal_check_exact_index_default(left_idx, right_idx):
    # GH#57067
    ser1 = Series(np.zeros(6, dtype=int), left_idx)
    ser2 = Series(np.zeros(6, dtype=int), right_idx)
    tm.assert_series_equal(ser1, ser2)
    tm.assert_frame_equal(ser1.to_frame(), ser2.to_frame())
