from datetime import date, datetime, timedelta
from functools import partial
from io import BytesIO
import os

import numpy as np
import pytest

import pandas.util._test_decorators as td

import pandas as pd
from pandas import DataFrame, Index, MultiIndex, get_option, set_option
import pandas._testing as tm

from pandas.io.excel import (
    ExcelFile,
    ExcelWriter,
    _OpenpyxlWriter,
    _XlsxWriter,
    _XlwtWriter,
    register_writer,
)


@pytest.fixture
def path(ext):
    """
    Fixture to open file for use in each test case.
    """
    with tm.ensure_clean(ext) as file_path:
        yield file_path


@pytest.fixture
def set_engine(engine, ext):
    """
    Fixture to set engine for use in each test case.

    Rather than requiring `engine=...` to be provided explicitly as an
    argument in each test, this fixture sets a global option to dictate
    which engine should be used to write Excel files. After executing
    the test it rolls back said change to the global option.
    """
    option_name = "io.excel.{ext}.writer".format(ext=ext.strip("."))
    prev_engine = get_option(option_name)
    set_option(option_name, engine)
    yield
    set_option(option_name, prev_engine)  # Roll back option change


@td.skip_if_no("xlrd")
@pytest.mark.parametrize("ext", [".xls", ".xlsx", ".xlsm"])
class TestRoundTrip:
    @td.skip_if_no("xlwt")
    @td.skip_if_no("openpyxl")
    @pytest.mark.parametrize(
        "header,expected",
        [(None, DataFrame([np.nan] * 4)), (0, DataFrame({"Unnamed: 0": [np.nan] * 3}))],
    )
    def test_read_one_empty_col_no_header(self, ext, header, expected):
        # xref gh-12292
        filename = "no_header"
        df = pd.DataFrame([["", 1, 100], ["", 2, 200], ["", 3, 300], ["", 4, 400]])

        with tm.ensure_clean(ext) as path:
            df.to_excel(path, filename, index=False, header=False)
            result = pd.read_excel(path, filename, usecols=[0], header=header)

        tm.assert_frame_equal(result, expected)

    @td.skip_if_no("xlwt")
    @td.skip_if_no("openpyxl")
    @pytest.mark.parametrize(
        "header,expected",
        [(None, DataFrame([0] + [np.nan] * 4)), (0, DataFrame([np.nan] * 4))],
    )
    def test_read_one_empty_col_with_header(self, ext, header, expected):
        filename = "with_header"
        df = pd.DataFrame([["", 1, 100], ["", 2, 200], ["", 3, 300], ["", 4, 400]])

        with tm.ensure_clean(ext) as path:
            df.to_excel(path, "with_header", index=False, header=True)
            result = pd.read_excel(path, filename, usecols=[0], header=header)

        tm.assert_frame_equal(result, expected)

    @td.skip_if_no("openpyxl")
    @td.skip_if_no("xlwt")
    def test_set_column_names_in_parameter(self, ext):
        # GH 12870 : pass down column names associated with
        # keyword argument names
        refdf = pd.DataFrame([[1, "foo"], [2, "bar"], [3, "baz"]], columns=["a", "b"])

        with tm.ensure_clean(ext) as pth:
            with ExcelWriter(pth) as writer:
                refdf.to_excel(writer, "Data_no_head", header=False, index=False)
                refdf.to_excel(writer, "Data_with_head", index=False)

            refdf.columns = ["A", "B"]

            with ExcelFile(pth) as reader:
                xlsdf_no_head = pd.read_excel(
                    reader, "Data_no_head", header=None, names=["A", "B"]
                )
                xlsdf_with_head = pd.read_excel(
                    reader, "Data_with_head", index_col=None, names=["A", "B"]
                )

            tm.assert_frame_equal(xlsdf_no_head, refdf)
            tm.assert_frame_equal(xlsdf_with_head, refdf)

    @td.skip_if_no("xlwt")
    @td.skip_if_no("openpyxl")
    def test_creating_and_reading_multiple_sheets(self, ext):
        # see gh-9450
        #
        # Test reading multiple sheets, from a runtime
        # created Excel file with multiple sheets.
        def tdf(col_sheet_name):
            d, i = [11, 22, 33], [1, 2, 3]
            return DataFrame(d, i, columns=[col_sheet_name])

        sheets = ["AAA", "BBB", "CCC"]

        dfs = [tdf(s) for s in sheets]
        dfs = dict(zip(sheets, dfs))

        with tm.ensure_clean(ext) as pth:
            with ExcelWriter(pth) as ew:
                for sheetname, df in dfs.items():
                    df.to_excel(ew, sheetname)

            dfs_returned = pd.read_excel(pth, sheet_name=sheets, index_col=0)

            for s in sheets:
                tm.assert_frame_equal(dfs[s], dfs_returned[s])

    @td.skip_if_no("xlsxwriter")
    def test_read_excel_multiindex_empty_level(self, ext):
        # see gh-12453
        with tm.ensure_clean(ext) as path:
            df = DataFrame(
                {
                    ("One", "x"): {0: 1},
                    ("Two", "X"): {0: 3},
                    ("Two", "Y"): {0: 7},
                    ("Zero", ""): {0: 0},
                }
            )

            expected = DataFrame(
                {
                    ("One", "x"): {0: 1},
                    ("Two", "X"): {0: 3},
                    ("Two", "Y"): {0: 7},
                    ("Zero", "Unnamed: 4_level_1"): {0: 0},
                }
            )

            df.to_excel(path)
            actual = pd.read_excel(path, header=[0, 1], index_col=0)
            tm.assert_frame_equal(actual, expected)

            df = pd.DataFrame(
                {
                    ("Beg", ""): {0: 0},
                    ("Middle", "x"): {0: 1},
                    ("Tail", "X"): {0: 3},
                    ("Tail", "Y"): {0: 7},
                }
            )

            expected = pd.DataFrame(
                {
                    ("Beg", "Unnamed: 1_level_1"): {0: 0},
                    ("Middle", "x"): {0: 1},
                    ("Tail", "X"): {0: 3},
                    ("Tail", "Y"): {0: 7},
                }
            )

            df.to_excel(path)
            actual = pd.read_excel(path, header=[0, 1], index_col=0)
            tm.assert_frame_equal(actual, expected)

    @td.skip_if_no("xlsxwriter")
    @pytest.mark.parametrize("c_idx_names", [True, False])
    @pytest.mark.parametrize("r_idx_names", [True, False])
    @pytest.mark.parametrize("c_idx_levels", [1, 3])
    @pytest.mark.parametrize("r_idx_levels", [1, 3])
    def test_excel_multindex_roundtrip(
        self, ext, c_idx_names, r_idx_names, c_idx_levels, r_idx_levels
    ):
        # see gh-4679
        with tm.ensure_clean(ext) as pth:
            if c_idx_levels == 1 and c_idx_names:
                pytest.skip(
                    "Column index name cannot be serialized unless it's a MultiIndex"
                )

            # Empty name case current read in as
            # unnamed levels, not Nones.
            check_names = r_idx_names or r_idx_levels <= 1

            df = tm.makeCustomDataframe(
                5, 5, c_idx_names, r_idx_names, c_idx_levels, r_idx_levels
            )
            df.to_excel(pth)

            act = pd.read_excel(
                pth,
                index_col=list(range(r_idx_levels)),
                header=list(range(c_idx_levels)),
            )
            tm.assert_frame_equal(df, act, check_names=check_names)

            df.iloc[0, :] = np.nan
            df.to_excel(pth)

            act = pd.read_excel(
                pth,
                index_col=list(range(r_idx_levels)),
                header=list(range(c_idx_levels)),
            )
            tm.assert_frame_equal(df, act, check_names=check_names)

            df.iloc[-1, :] = np.nan
            df.to_excel(pth)
            act = pd.read_excel(
                pth,
                index_col=list(range(r_idx_levels)),
                header=list(range(c_idx_levels)),
            )
            tm.assert_frame_equal(df, act, check_names=check_names)

    @td.skip_if_no("xlwt")
    @td.skip_if_no("openpyxl")
    def test_read_excel_parse_dates(self, ext):
        # see gh-11544, gh-12051
        df = DataFrame(
            {"col": [1, 2, 3], "date_strings": pd.date_range("2012-01-01", periods=3)}
        )
        df2 = df.copy()
        df2["date_strings"] = df2["date_strings"].dt.strftime("%m/%d/%Y")

        with tm.ensure_clean(ext) as pth:
            df2.to_excel(pth)

            res = pd.read_excel(pth, index_col=0)
            tm.assert_frame_equal(df2, res)

            res = pd.read_excel(pth, parse_dates=["date_strings"], index_col=0)
            tm.assert_frame_equal(df, res)

            date_parser = lambda x: datetime.strptime(x, "%m/%d/%Y")
            res = pd.read_excel(
                pth, parse_dates=["date_strings"], date_parser=date_parser, index_col=0
            )
            tm.assert_frame_equal(df, res)


@td.skip_if_no("xlrd")
@pytest.mark.parametrize(
    "engine,ext",
    [
        pytest.param("openpyxl", ".xlsx", marks=td.skip_if_no("openpyxl")),
        pytest.param("openpyxl", ".xlsm", marks=td.skip_if_no("openpyxl")),
        pytest.param("xlwt", ".xls", marks=td.skip_if_no("xlwt")),
        pytest.param("xlsxwriter", ".xlsx", marks=td.skip_if_no("xlsxwriter")),
    ],
)
@pytest.mark.usefixtures("set_engine")
class TestExcelWriter:
    def test_excel_sheet_size(self, path):

        # GH 26080
        breaking_row_count = 2 ** 20 + 1
        breaking_col_count = 2 ** 14 + 1
        # purposely using two arrays to prevent memory issues while testing
        row_arr = np.zeros(shape=(breaking_row_count, 1))
        col_arr = np.zeros(shape=(1, breaking_col_count))
        row_df = pd.DataFrame(row_arr)
        col_df = pd.DataFrame(col_arr)

        msg = "sheet is too large"
        with pytest.raises(ValueError, match=msg):
            row_df.to_excel(path)

        with pytest.raises(ValueError, match=msg):
            col_df.to_excel(path)

    def test_excel_sheet_by_name_raise(self, path):
        import xlrd

        gt = DataFrame(np.random.randn(10, 2))
        gt.to_excel(path)

        xl = ExcelFile(path)
        df = pd.read_excel(xl, 0, index_col=0)

        tm.assert_frame_equal(gt, df)

        with pytest.raises(xlrd.XLRDError):
            pd.read_excel(xl, "0")

    def test_excel_writer_context_manager(self, frame, path):
        with ExcelWriter(path) as writer:
            frame.to_excel(writer, "Data1")
            frame2 = frame.copy()
            frame2.columns = frame.columns[::-1]
            frame2.to_excel(writer, "Data2")

        with ExcelFile(path) as reader:
            found_df = pd.read_excel(reader, "Data1", index_col=0)
            found_df2 = pd.read_excel(reader, "Data2", index_col=0)

            tm.assert_frame_equal(found_df, frame)
            tm.assert_frame_equal(found_df2, frame2)

    def test_roundtrip(self, frame, path):
        frame = frame.copy()
        frame["A"][:5] = np.nan

        frame.to_excel(path, "test1")
        frame.to_excel(path, "test1", columns=["A", "B"])
        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", index=False)

        # test roundtrip
        frame.to_excel(path, "test1")
        recons = pd.read_excel(path, "test1", index_col=0)
        tm.assert_frame_equal(frame, recons)

        frame.to_excel(path, "test1", index=False)
        recons = pd.read_excel(path, "test1", index_col=None)
        recons.index = frame.index
        tm.assert_frame_equal(frame, recons)

        frame.to_excel(path, "test1", na_rep="NA")
        recons = pd.read_excel(path, "test1", index_col=0, na_values=["NA"])
        tm.assert_frame_equal(frame, recons)

        # GH 3611
        frame.to_excel(path, "test1", na_rep="88")
        recons = pd.read_excel(path, "test1", index_col=0, na_values=["88"])
        tm.assert_frame_equal(frame, recons)

        frame.to_excel(path, "test1", na_rep="88")
        recons = pd.read_excel(path, "test1", index_col=0, na_values=[88, 88.0])
        tm.assert_frame_equal(frame, recons)

        # GH 6573
        frame.to_excel(path, "Sheet1")
        recons = pd.read_excel(path, index_col=0)
        tm.assert_frame_equal(frame, recons)

        frame.to_excel(path, "0")
        recons = pd.read_excel(path, index_col=0)
        tm.assert_frame_equal(frame, recons)

        # GH 8825 Pandas Series should provide to_excel method
        s = frame["A"]
        s.to_excel(path)
        recons = pd.read_excel(path, index_col=0)
        tm.assert_frame_equal(s.to_frame(), recons)

    def test_mixed(self, frame, path):
        mixed_frame = frame.copy()
        mixed_frame["foo"] = "bar"

        mixed_frame.to_excel(path, "test1")
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(mixed_frame, recons)

    def test_ts_frame(self, tsframe, path):
        df = tsframe

        df.to_excel(path, "test1")
        reader = ExcelFile(path)

        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(df, recons)

    def test_basics_with_nan(self, frame, path):
        frame = frame.copy()
        frame["A"][:5] = np.nan
        frame.to_excel(path, "test1")
        frame.to_excel(path, "test1", columns=["A", "B"])
        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", index=False)

    @pytest.mark.parametrize("np_type", [np.int8, np.int16, np.int32, np.int64])
    def test_int_types(self, np_type, path):
        # Test np.int values read come back as int
        # (rather than float which is Excel's format).
        df = DataFrame(np.random.randint(-10, 10, size=(10, 2)), dtype=np_type)
        df.to_excel(path, "test1")

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0)

        int_frame = df.astype(np.int64)
        tm.assert_frame_equal(int_frame, recons)

        recons2 = pd.read_excel(path, "test1", index_col=0)
        tm.assert_frame_equal(int_frame, recons2)

        # Test with convert_float=False comes back as float.
        float_frame = df.astype(float)
        recons = pd.read_excel(path, "test1", convert_float=False, index_col=0)
        tm.assert_frame_equal(
            recons, float_frame, check_index_type=False, check_column_type=False
        )

    @pytest.mark.parametrize("np_type", [np.float16, np.float32, np.float64])
    def test_float_types(self, np_type, path):
        # Test np.float values read come back as float.
        df = DataFrame(np.random.random_sample(10), dtype=np_type)
        df.to_excel(path, "test1")

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0).astype(np_type)

        tm.assert_frame_equal(df, recons, check_dtype=False)

    @pytest.mark.parametrize("np_type", [np.bool8, np.bool_])
    def test_bool_types(self, np_type, path):
        # Test np.bool values read come back as float.
        df = DataFrame([1, 0, True, False], dtype=np_type)
        df.to_excel(path, "test1")

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0).astype(np_type)

        tm.assert_frame_equal(df, recons)

    def test_inf_roundtrip(self, path):
        df = DataFrame([(1, np.inf), (2, 3), (5, -np.inf)])
        df.to_excel(path, "test1")

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0)

        tm.assert_frame_equal(df, recons)

    def test_sheets(self, frame, tsframe, path):
        frame = frame.copy()
        frame["A"][:5] = np.nan

        frame.to_excel(path, "test1")
        frame.to_excel(path, "test1", columns=["A", "B"])
        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", index=False)

        # Test writing to separate sheets
        writer = ExcelWriter(path)
        frame.to_excel(writer, "test1")
        tsframe.to_excel(writer, "test2")
        writer.save()
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(frame, recons)
        recons = pd.read_excel(reader, "test2", index_col=0)
        tm.assert_frame_equal(tsframe, recons)
        assert 2 == len(reader.sheet_names)
        assert "test1" == reader.sheet_names[0]
        assert "test2" == reader.sheet_names[1]

    def test_colaliases(self, frame, path):
        frame = frame.copy()
        frame["A"][:5] = np.nan

        frame.to_excel(path, "test1")
        frame.to_excel(path, "test1", columns=["A", "B"])
        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", index=False)

        # column aliases
        col_aliases = Index(["AA", "X", "Y", "Z"])
        frame.to_excel(path, "test1", header=col_aliases)
        reader = ExcelFile(path)
        rs = pd.read_excel(reader, "test1", index_col=0)
        xp = frame.copy()
        xp.columns = col_aliases
        tm.assert_frame_equal(xp, rs)

    def test_roundtrip_indexlabels(self, merge_cells, frame, path):
        frame = frame.copy()
        frame["A"][:5] = np.nan

        frame.to_excel(path, "test1")
        frame.to_excel(path, "test1", columns=["A", "B"])
        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", index=False)

        # test index_label
        df = DataFrame(np.random.randn(10, 2)) >= 0
        df.to_excel(path, "test1", index_label=["test"], merge_cells=merge_cells)
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0).astype(np.int64)
        df.index.names = ["test"]
        assert df.index.names == recons.index.names

        df = DataFrame(np.random.randn(10, 2)) >= 0
        df.to_excel(
            path,
            "test1",
            index_label=["test", "dummy", "dummy2"],
            merge_cells=merge_cells,
        )
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0).astype(np.int64)
        df.index.names = ["test"]
        assert df.index.names == recons.index.names

        df = DataFrame(np.random.randn(10, 2)) >= 0
        df.to_excel(path, "test1", index_label="test", merge_cells=merge_cells)
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0).astype(np.int64)
        df.index.names = ["test"]
        tm.assert_frame_equal(df, recons.astype(bool))

        frame.to_excel(
            path,
            "test1",
            columns=["A", "B", "C", "D"],
            index=False,
            merge_cells=merge_cells,
        )
        # take 'A' and 'B' as indexes (same row as cols 'C', 'D')
        df = frame.copy()
        df = df.set_index(["A", "B"])

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=[0, 1])
        tm.assert_frame_equal(df, recons, check_less_precise=True)

    def test_excel_roundtrip_indexname(self, merge_cells, path):
        df = DataFrame(np.random.randn(10, 4))
        df.index.name = "foo"

        df.to_excel(path, merge_cells=merge_cells)

        xf = ExcelFile(path)
        result = pd.read_excel(xf, xf.sheet_names[0], index_col=0)

        tm.assert_frame_equal(result, df)
        assert result.index.name == "foo"

    def test_excel_roundtrip_datetime(self, merge_cells, tsframe, path):
        # datetime.date, not sure what to test here exactly
        tsf = tsframe.copy()

        tsf.index = [x.date() for x in tsframe.index]
        tsf.to_excel(path, "test1", merge_cells=merge_cells)

        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=0)

        tm.assert_frame_equal(tsframe, recons)

    def test_excel_date_datetime_format(self, engine, ext, path):
        # see gh-4133
        #
        # Excel output format strings
        df = DataFrame(
            [
                [date(2014, 1, 31), date(1999, 9, 24)],
                [datetime(1998, 5, 26, 23, 33, 4), datetime(2014, 2, 28, 13, 5, 13)],
            ],
            index=["DATE", "DATETIME"],
            columns=["X", "Y"],
        )
        df_expected = DataFrame(
            [
                [datetime(2014, 1, 31), datetime(1999, 9, 24)],
                [datetime(1998, 5, 26, 23, 33, 4), datetime(2014, 2, 28, 13, 5, 13)],
            ],
            index=["DATE", "DATETIME"],
            columns=["X", "Y"],
        )

        with tm.ensure_clean(ext) as filename2:
            writer1 = ExcelWriter(path)
            writer2 = ExcelWriter(
                filename2,
                date_format="DD.MM.YYYY",
                datetime_format="DD.MM.YYYY HH-MM-SS",
            )

            df.to_excel(writer1, "test1")
            df.to_excel(writer2, "test1")

            writer1.close()
            writer2.close()

            reader1 = ExcelFile(path)
            reader2 = ExcelFile(filename2)

            rs1 = pd.read_excel(reader1, "test1", index_col=0)
            rs2 = pd.read_excel(reader2, "test1", index_col=0)

            tm.assert_frame_equal(rs1, rs2)

            # Since the reader returns a datetime object for dates,
            # we need to use df_expected to check the result.
            tm.assert_frame_equal(rs2, df_expected)

    def test_to_excel_interval_no_labels(self, path):
        # see gh-19242
        #
        # Test writing Interval without labels.
        df = DataFrame(np.random.randint(-10, 10, size=(20, 1)), dtype=np.int64)
        expected = df.copy()

        df["new"] = pd.cut(df[0], 10)
        expected["new"] = pd.cut(expected[0], 10).astype(str)

        df.to_excel(path, "test1")
        reader = ExcelFile(path)

        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(expected, recons)

    def test_to_excel_interval_labels(self, path):
        # see gh-19242
        #
        # Test writing Interval with labels.
        df = DataFrame(np.random.randint(-10, 10, size=(20, 1)), dtype=np.int64)
        expected = df.copy()
        intervals = pd.cut(
            df[0], 10, labels=["A", "B", "C", "D", "E", "F", "G", "H", "I", "J"]
        )
        df["new"] = intervals
        expected["new"] = pd.Series(list(intervals))

        df.to_excel(path, "test1")
        reader = ExcelFile(path)

        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(expected, recons)

    def test_to_excel_timedelta(self, path):
        # see gh-19242, gh-9155
        #
        # Test writing timedelta to xls.
        df = DataFrame(
            np.random.randint(-10, 10, size=(20, 1)), columns=["A"], dtype=np.int64
        )
        expected = df.copy()

        df["new"] = df["A"].apply(lambda x: timedelta(seconds=x))
        expected["new"] = expected["A"].apply(
            lambda x: timedelta(seconds=x).total_seconds() / float(86400)
        )

        df.to_excel(path, "test1")
        reader = ExcelFile(path)

        recons = pd.read_excel(reader, "test1", index_col=0)
        tm.assert_frame_equal(expected, recons)

    def test_to_excel_periodindex(self, tsframe, path):
        xp = tsframe.resample("M", kind="period").mean()

        xp.to_excel(path, "sht1")

        reader = ExcelFile(path)
        rs = pd.read_excel(reader, "sht1", index_col=0)
        tm.assert_frame_equal(xp, rs.to_period("M"))

    def test_to_excel_multiindex(self, merge_cells, frame, path):
        arrays = np.arange(len(frame.index) * 2).reshape(2, -1)
        new_index = MultiIndex.from_arrays(arrays, names=["first", "second"])
        frame.index = new_index

        frame.to_excel(path, "test1", header=False)
        frame.to_excel(path, "test1", columns=["A", "B"])

        # round trip
        frame.to_excel(path, "test1", merge_cells=merge_cells)
        reader = ExcelFile(path)
        df = pd.read_excel(reader, "test1", index_col=[0, 1])
        tm.assert_frame_equal(frame, df)

    # GH13511
    def test_to_excel_multiindex_nan_label(self, merge_cells, path):
        df = pd.DataFrame(
            {"A": [None, 2, 3], "B": [10, 20, 30], "C": np.random.sample(3)}
        )
        df = df.set_index(["A", "B"])

        df.to_excel(path, merge_cells=merge_cells)
        df1 = pd.read_excel(path, index_col=[0, 1])
        tm.assert_frame_equal(df, df1)

    # Test for Issue 11328. If column indices are integers, make
    # sure they are handled correctly for either setting of
    # merge_cells
    def test_to_excel_multiindex_cols(self, merge_cells, frame, path):
        arrays = np.arange(len(frame.index) * 2).reshape(2, -1)
        new_index = MultiIndex.from_arrays(arrays, names=["first", "second"])
        frame.index = new_index

        new_cols_index = MultiIndex.from_tuples([(40, 1), (40, 2), (50, 1), (50, 2)])
        frame.columns = new_cols_index
        header = [0, 1]
        if not merge_cells:
            header = 0

        # round trip
        frame.to_excel(path, "test1", merge_cells=merge_cells)
        reader = ExcelFile(path)
        df = pd.read_excel(reader, "test1", header=header, index_col=[0, 1])
        if not merge_cells:
            fm = frame.columns.format(sparsify=False, adjoin=False, names=False)
            frame.columns = [".".join(map(str, q)) for q in zip(*fm)]
        tm.assert_frame_equal(frame, df)

    def test_to_excel_multiindex_dates(self, merge_cells, tsframe, path):
        # try multiindex with dates
        new_index = [tsframe.index, np.arange(len(tsframe.index))]
        tsframe.index = MultiIndex.from_arrays(new_index)

        tsframe.index.names = ["time", "foo"]
        tsframe.to_excel(path, "test1", merge_cells=merge_cells)
        reader = ExcelFile(path)
        recons = pd.read_excel(reader, "test1", index_col=[0, 1])

        tm.assert_frame_equal(tsframe, recons)
        assert recons.index.names == ("time", "foo")

    def test_to_excel_multiindex_no_write_index(self, path):
        # Test writing and re-reading a MI without the index. GH 5616.

        # Initial non-MI frame.
        frame1 = DataFrame({"a": [10, 20], "b": [30, 40], "c": [50, 60]})

        # Add a MI.
        frame2 = frame1.copy()
        multi_index = MultiIndex.from_tuples([(70, 80), (90, 100)])
        frame2.index = multi_index

        # Write out to Excel without the index.
        frame2.to_excel(path, "test1", index=False)

        # Read it back in.
        reader = ExcelFile(path)
        frame3 = pd.read_excel(reader, "test1")

        # Test that it is the same as the initial frame.
        tm.assert_frame_equal(frame1, frame3)

    def test_to_excel_float_format(self, path):
        df = DataFrame(
            [[0.123456, 0.234567, 0.567567], [12.32112, 123123.2, 321321.2]],
            index=["A", "B"],
            columns=["X", "Y", "Z"],
        )
        df.to_excel(path, "test1", float_format="%.2f")

        reader = ExcelFile(path)
        result = pd.read_excel(reader, "test1", index_col=0)

        expected = DataFrame(
            [[0.12, 0.23, 0.57], [12.32, 123123.20, 321321.20]],
            index=["A", "B"],
            columns=["X", "Y", "Z"],
        )
        tm.assert_frame_equal(result, expected)

    def test_to_excel_output_encoding(self, ext):
        # Avoid mixed inferred_type.
        df = DataFrame(
            [["\u0192", "\u0193", "\u0194"], ["\u0195", "\u0196", "\u0197"]],
            index=["A\u0192", "B"],
            columns=["X\u0193", "Y", "Z"],
        )

        with tm.ensure_clean("__tmp_to_excel_float_format__." + ext) as filename:
            df.to_excel(filename, sheet_name="TestSheet", encoding="utf8")
            result = pd.read_excel(filename, "TestSheet", encoding="utf8", index_col=0)
            tm.assert_frame_equal(result, df)

    def test_to_excel_unicode_filename(self, ext, path):
        with tm.ensure_clean("\u0192u." + ext) as filename:
            try:
                f = open(filename, "wb")
            except UnicodeEncodeError:
                pytest.skip("No unicode file names on this system")
            else:
                f.close()

            df = DataFrame(
                [[0.123456, 0.234567, 0.567567], [12.32112, 123123.2, 321321.2]],
                index=["A", "B"],
                columns=["X", "Y", "Z"],
            )
            df.to_excel(filename, "test1", float_format="%.2f")

            reader = ExcelFile(filename)
            result = pd.read_excel(reader, "test1", index_col=0)

            expected = DataFrame(
                [[0.12, 0.23, 0.57], [12.32, 123123.20, 321321.20]],
                index=["A", "B"],
                columns=["X", "Y", "Z"],
            )
            tm.assert_frame_equal(result, expected)

    # FIXME: dont leave commented-out
    # def test_to_excel_header_styling_xls(self, engine, ext):

    #     import StringIO
    #     s = StringIO(
    #     """Date,ticker,type,value
    #     2001-01-01,x,close,12.2
    #     2001-01-01,x,open ,12.1
    #     2001-01-01,y,close,12.2
    #     2001-01-01,y,open ,12.1
    #     2001-02-01,x,close,12.2
    #     2001-02-01,x,open ,12.1
    #     2001-02-01,y,close,12.2
    #     2001-02-01,y,open ,12.1
    #     2001-03-01,x,close,12.2
    #     2001-03-01,x,open ,12.1
    #     2001-03-01,y,close,12.2
    #     2001-03-01,y,open ,12.1""")
    #     df = read_csv(s, parse_dates=["Date"])
    #     pdf = df.pivot_table(values="value", rows=["ticker"],
    #                                          cols=["Date", "type"])

    #     try:
    #         import xlwt
    #         import xlrd
    #     except ImportError:
    #         pytest.skip

    #     filename = '__tmp_to_excel_header_styling_xls__.xls'
    #     pdf.to_excel(filename, 'test1')

    #     wbk = xlrd.open_workbook(filename,
    #                              formatting_info=True)
    #     assert ["test1"] == wbk.sheet_names()
    #     ws = wbk.sheet_by_name('test1')
    #     assert [(0, 1, 5, 7), (0, 1, 3, 5), (0, 1, 1, 3)] == ws.merged_cells
    #     for i in range(0, 2):
    #         for j in range(0, 7):
    #             xfx = ws.cell_xf_index(0, 0)
    #             cell_xf = wbk.xf_list[xfx]
    #             font = wbk.font_list
    #             assert 1 == font[cell_xf.font_index].bold
    #             assert 1 == cell_xf.border.top_line_style
    #             assert 1 == cell_xf.border.right_line_style
    #             assert 1 == cell_xf.border.bottom_line_style
    #             assert 1 == cell_xf.border.left_line_style
    #             assert 2 == cell_xf.alignment.hor_align
    #     os.remove(filename)
    # def test_to_excel_header_styling_xlsx(self, engine, ext):
    #     import StringIO
    #     s = StringIO(
    #     """Date,ticker,type,value
    #     2001-01-01,x,close,12.2
    #     2001-01-01,x,open ,12.1
    #     2001-01-01,y,close,12.2
    #     2001-01-01,y,open ,12.1
    #     2001-02-01,x,close,12.2
    #     2001-02-01,x,open ,12.1
    #     2001-02-01,y,close,12.2
    #     2001-02-01,y,open ,12.1
    #     2001-03-01,x,close,12.2
    #     2001-03-01,x,open ,12.1
    #     2001-03-01,y,close,12.2
    #     2001-03-01,y,open ,12.1""")
    #     df = read_csv(s, parse_dates=["Date"])
    #     pdf = df.pivot_table(values="value", rows=["ticker"],
    #                                          cols=["Date", "type"])
    #     try:
    #         import openpyxl
    #         from openpyxl.cell import get_column_letter
    #     except ImportError:
    #         pytest.skip
    #     if openpyxl.__version__ < '1.6.1':
    #         pytest.skip
    #     # test xlsx_styling
    #     filename = '__tmp_to_excel_header_styling_xlsx__.xlsx'
    #     pdf.to_excel(filename, 'test1')
    #     wbk = openpyxl.load_workbook(filename)
    #     assert ["test1"] == wbk.get_sheet_names()
    #     ws = wbk.get_sheet_by_name('test1')
    #     xlsaddrs = ["%s2" % chr(i) for i in range(ord('A'), ord('H'))]
    #     xlsaddrs += ["A%s" % i for i in range(1, 6)]
    #     xlsaddrs += ["B1", "D1", "F1"]
    #     for xlsaddr in xlsaddrs:
    #         cell = ws.cell(xlsaddr)
    #         assert cell.style.font.bold
    #         assert (openpyxl.style.Border.BORDER_THIN ==
    #                 cell.style.borders.top.border_style)
    #         assert (openpyxl.style.Border.BORDER_THIN ==
    #                 cell.style.borders.right.border_style)
    #         assert (openpyxl.style.Border.BORDER_THIN ==
    #                 cell.style.borders.bottom.border_style)
    #         assert (openpyxl.style.Border.BORDER_THIN ==
    #                 cell.style.borders.left.border_style)
    #         assert (openpyxl.style.Alignment.HORIZONTAL_CENTER ==
    #                 cell.style.alignment.horizontal)
    #     mergedcells_addrs = ["C1", "E1", "G1"]
    #     for maddr in mergedcells_addrs:
    #         assert ws.cell(maddr).merged
    #     os.remove(filename)

    @pytest.mark.parametrize("use_headers", [True, False])
    @pytest.mark.parametrize("r_idx_nlevels", [1, 2, 3])
    @pytest.mark.parametrize("c_idx_nlevels", [1, 2, 3])
    def test_excel_010_hemstring(
        self, merge_cells, c_idx_nlevels, r_idx_nlevels, use_headers, path
    ):
        def roundtrip(data, header=True, parser_hdr=0, index=True):
            data.to_excel(path, header=header, merge_cells=merge_cells, index=index)

            xf = ExcelFile(path)
            return pd.read_excel(xf, xf.sheet_names[0], header=parser_hdr)

        # Basic test.
        parser_header = 0 if use_headers else None
        res = roundtrip(DataFrame([0]), use_headers, parser_header)

        assert res.shape == (1, 2)
        assert res.iloc[0, 0] is not np.nan

        # More complex tests with multi-index.
        nrows = 5
        ncols = 3

        # ensure limited functionality in 0.10
        # override of gh-2370 until sorted out in 0.11

        df = tm.makeCustomDataframe(
            nrows, ncols, r_idx_nlevels=r_idx_nlevels, c_idx_nlevels=c_idx_nlevels
        )

        # This if will be removed once multi-column Excel writing
        # is implemented. For now fixing gh-9794.
        if c_idx_nlevels > 1:
            with pytest.raises(NotImplementedError):
                roundtrip(df, use_headers, index=False)
        else:
            res = roundtrip(df, use_headers)

            if use_headers:
                assert res.shape == (nrows, ncols + r_idx_nlevels)
            else:
                # First row taken as columns.
                assert res.shape == (nrows - 1, ncols + r_idx_nlevels)

            # No NaNs.
            for r in range(len(res.index)):
                for c in range(len(res.columns)):
                    assert res.iloc[r, c] is not np.nan

    def test_duplicated_columns(self, path):
        # see gh-5235
        df = DataFrame([[1, 2, 3], [1, 2, 3], [1, 2, 3]], columns=["A", "B", "B"])
        df.to_excel(path, "test1")
        expected = DataFrame(
            [[1, 2, 3], [1, 2, 3], [1, 2, 3]], columns=["A", "B", "B.1"]
        )

        # By default, we mangle.
        result = pd.read_excel(path, "test1", index_col=0)
        tm.assert_frame_equal(result, expected)

        # Explicitly, we pass in the parameter.
        result = pd.read_excel(path, "test1", index_col=0, mangle_dupe_cols=True)
        tm.assert_frame_equal(result, expected)

        # see gh-11007, gh-10970
        df = DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]], columns=["A", "B", "A", "B"])
        df.to_excel(path, "test1")

        result = pd.read_excel(path, "test1", index_col=0)
        expected = DataFrame(
            [[1, 2, 3, 4], [5, 6, 7, 8]], columns=["A", "B", "A.1", "B.1"]
        )
        tm.assert_frame_equal(result, expected)

        # see gh-10982
        df.to_excel(path, "test1", index=False, header=False)
        result = pd.read_excel(path, "test1", header=None)

        expected = DataFrame([[1, 2, 3, 4], [5, 6, 7, 8]])
        tm.assert_frame_equal(result, expected)

        msg = "Setting mangle_dupe_cols=False is not supported yet"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel(path, "test1", header=None, mangle_dupe_cols=False)

    def test_swapped_columns(self, path):
        # Test for issue #5427.
        write_frame = DataFrame({"A": [1, 1, 1], "B": [2, 2, 2]})
        write_frame.to_excel(path, "test1", columns=["B", "A"])

        read_frame = pd.read_excel(path, "test1", header=0)

        tm.assert_series_equal(write_frame["A"], read_frame["A"])
        tm.assert_series_equal(write_frame["B"], read_frame["B"])

    def test_invalid_columns(self, path):
        # see gh-10982
        write_frame = DataFrame({"A": [1, 1, 1], "B": [2, 2, 2]})

        with pytest.raises(KeyError, match="Not all names specified"):
            write_frame.to_excel(path, "test1", columns=["B", "C"])

        with pytest.raises(
            KeyError, match="'passes columns are not ALL present dataframe'"
        ):
            write_frame.to_excel(path, "test1", columns=["C", "D"])

    def test_comment_arg(self, path):
        # see gh-18735
        #
        # Test the comment argument functionality to pd.read_excel.

        # Create file to read in.
        df = DataFrame({"A": ["one", "#one", "one"], "B": ["two", "two", "#two"]})
        df.to_excel(path, "test_c")

        # Read file without comment arg.
        result1 = pd.read_excel(path, "test_c", index_col=0)

        result1.iloc[1, 0] = None
        result1.iloc[1, 1] = None
        result1.iloc[2, 1] = None

        result2 = pd.read_excel(path, "test_c", comment="#", index_col=0)
        tm.assert_frame_equal(result1, result2)

    def test_comment_default(self, path):
        # Re issue #18735
        # Test the comment argument default to pd.read_excel

        # Create file to read in
        df = DataFrame({"A": ["one", "#one", "one"], "B": ["two", "two", "#two"]})
        df.to_excel(path, "test_c")

        # Read file with default and explicit comment=None
        result1 = pd.read_excel(path, "test_c")
        result2 = pd.read_excel(path, "test_c", comment=None)
        tm.assert_frame_equal(result1, result2)

    def test_comment_used(self, path):
        # see gh-18735
        #
        # Test the comment argument is working as expected when used.

        # Create file to read in.
        df = DataFrame({"A": ["one", "#one", "one"], "B": ["two", "two", "#two"]})
        df.to_excel(path, "test_c")

        # Test read_frame_comment against manually produced expected output.
        expected = DataFrame({"A": ["one", None, "one"], "B": ["two", None, None]})
        result = pd.read_excel(path, "test_c", comment="#", index_col=0)
        tm.assert_frame_equal(result, expected)

    def test_comment_empty_line(self, path):
        # Re issue #18735
        # Test that pd.read_excel ignores commented lines at the end of file

        df = DataFrame({"a": ["1", "#2"], "b": ["2", "3"]})
        df.to_excel(path, index=False)

        # Test that all-comment lines at EoF are ignored
        expected = DataFrame({"a": [1], "b": [2]})
        result = pd.read_excel(path, comment="#")
        tm.assert_frame_equal(result, expected)

    def test_datetimes(self, path):

        # Test writing and reading datetimes. For issue #9139. (xref #9185)
        datetimes = [
            datetime(2013, 1, 13, 1, 2, 3),
            datetime(2013, 1, 13, 2, 45, 56),
            datetime(2013, 1, 13, 4, 29, 49),
            datetime(2013, 1, 13, 6, 13, 42),
            datetime(2013, 1, 13, 7, 57, 35),
            datetime(2013, 1, 13, 9, 41, 28),
            datetime(2013, 1, 13, 11, 25, 21),
            datetime(2013, 1, 13, 13, 9, 14),
            datetime(2013, 1, 13, 14, 53, 7),
            datetime(2013, 1, 13, 16, 37, 0),
            datetime(2013, 1, 13, 18, 20, 52),
        ]

        write_frame = DataFrame({"A": datetimes})
        write_frame.to_excel(path, "Sheet1")
        read_frame = pd.read_excel(path, "Sheet1", header=0)

        tm.assert_series_equal(write_frame["A"], read_frame["A"])

    def test_bytes_io(self, engine):
        # see gh-7074
        bio = BytesIO()
        df = DataFrame(np.random.randn(10, 2))

        # Pass engine explicitly, as there is no file path to infer from.
        writer = ExcelWriter(bio, engine=engine)
        df.to_excel(writer)
        writer.save()

        bio.seek(0)
        reread_df = pd.read_excel(bio, index_col=0)
        tm.assert_frame_equal(df, reread_df)

    def test_write_lists_dict(self, path):
        # see gh-8188.
        df = DataFrame(
            {
                "mixed": ["a", ["b", "c"], {"d": "e", "f": 2}],
                "numeric": [1, 2, 3.0],
                "str": ["apple", "banana", "cherry"],
            }
        )
        df.to_excel(path, "Sheet1")
        read = pd.read_excel(path, "Sheet1", header=0, index_col=0)

        expected = df.copy()
        expected.mixed = expected.mixed.apply(str)
        expected.numeric = expected.numeric.astype("int64")

        tm.assert_frame_equal(read, expected)

    def test_true_and_false_value_options(self, path):
        # see gh-13347
        df = pd.DataFrame([["foo", "bar"]], columns=["col1", "col2"])
        expected = df.replace({"foo": True, "bar": False})

        df.to_excel(path)
        read_frame = pd.read_excel(
            path, true_values=["foo"], false_values=["bar"], index_col=0
        )
        tm.assert_frame_equal(read_frame, expected)

    def test_freeze_panes(self, path):
        # see gh-15160
        expected = DataFrame([[1, 2], [3, 4]], columns=["col1", "col2"])
        expected.to_excel(path, "Sheet1", freeze_panes=(1, 1))

        result = pd.read_excel(path, index_col=0)
        tm.assert_frame_equal(result, expected)

    def test_path_path_lib(self, engine, ext):
        df = tm.makeDataFrame()
        writer = partial(df.to_excel, engine=engine)

        reader = partial(pd.read_excel, index_col=0)
        result = tm.round_trip_pathlib(writer, reader, path="foo.{ext}".format(ext=ext))
        tm.assert_frame_equal(result, df)

    def test_path_local_path(self, engine, ext):
        df = tm.makeDataFrame()
        writer = partial(df.to_excel, engine=engine)

        reader = partial(pd.read_excel, index_col=0)
        result = tm.round_trip_pathlib(writer, reader, path="foo.{ext}".format(ext=ext))
        tm.assert_frame_equal(result, df)

    def test_merged_cell_custom_objects(self, merge_cells, path):
        # see GH-27006
        mi = MultiIndex.from_tuples(
            [
                (pd.Period("2018"), pd.Period("2018Q1")),
                (pd.Period("2018"), pd.Period("2018Q2")),
            ]
        )
        expected = DataFrame(np.ones((2, 2)), columns=mi)
        expected.to_excel(path)
        result = pd.read_excel(path, header=[0, 1], index_col=0, convert_float=False)
        # need to convert PeriodIndexes to standard Indexes for assert equal
        expected.columns.set_levels(
            [[str(i) for i in mi.levels[0]], [str(i) for i in mi.levels[1]]],
            level=[0, 1],
            inplace=True,
        )
        expected.index = expected.index.astype(np.float64)
        tm.assert_frame_equal(expected, result)

    @pytest.mark.parametrize("dtype", [None, object])
    def test_raise_when_saving_timezones(self, dtype, tz_aware_fixture, path):
        # GH 27008, GH 7056
        tz = tz_aware_fixture
        data = pd.Timestamp("2019", tz=tz)
        df = DataFrame([data], dtype=dtype)
        with pytest.raises(ValueError, match="Excel does not support"):
            df.to_excel(path)

        data = data.to_pydatetime()
        df = DataFrame([data], dtype=dtype)
        with pytest.raises(ValueError, match="Excel does not support"):
            df.to_excel(path)


class TestExcelWriterEngineTests:
    @pytest.mark.parametrize(
        "klass,ext",
        [
            pytest.param(_XlsxWriter, ".xlsx", marks=td.skip_if_no("xlsxwriter")),
            pytest.param(_OpenpyxlWriter, ".xlsx", marks=td.skip_if_no("openpyxl")),
            pytest.param(_XlwtWriter, ".xls", marks=td.skip_if_no("xlwt")),
        ],
    )
    def test_ExcelWriter_dispatch(self, klass, ext):
        with tm.ensure_clean(ext) as path:
            writer = ExcelWriter(path)
            if ext == ".xlsx" and td.safe_import("xlsxwriter"):
                # xlsxwriter has preference over openpyxl if both installed
                assert isinstance(writer, _XlsxWriter)
            else:
                assert isinstance(writer, klass)

    def test_ExcelWriter_dispatch_raises(self):
        with pytest.raises(ValueError, match="No engine"):
            ExcelWriter("nothing")

    def test_register_writer(self):
        # some awkward mocking to test out dispatch and such actually works
        called_save = []
        called_write_cells = []

        class DummyClass(ExcelWriter):
            called_save = False
            called_write_cells = False
            supported_extensions = ["xlsx", "xls"]
            engine = "dummy"

            def save(self):
                called_save.append(True)

            def write_cells(self, *args, **kwargs):
                called_write_cells.append(True)

        def check_called(func):
            func()
            assert len(called_save) >= 1
            assert len(called_write_cells) >= 1
            del called_save[:]
            del called_write_cells[:]

        with pd.option_context("io.excel.xlsx.writer", "dummy"):
            register_writer(DummyClass)
            writer = ExcelWriter("something.xlsx")
            assert isinstance(writer, DummyClass)
            df = tm.makeCustomDataframe(1, 1)
            check_called(lambda: df.to_excel("something.xlsx"))
            check_called(lambda: df.to_excel("something.xls", engine="dummy"))


@td.skip_if_no("xlrd")
@td.skip_if_no("openpyxl")
class TestFSPath:
    def test_excelfile_fspath(self):
        with tm.ensure_clean("foo.xlsx") as path:
            df = DataFrame({"A": [1, 2]})
            df.to_excel(path)
            xl = ExcelFile(path)
            result = os.fspath(xl)
            assert result == path

    def test_excelwriter_fspath(self):
        with tm.ensure_clean("foo.xlsx") as path:
            writer = ExcelWriter(path)
            assert os.fspath(writer) == str(path)
