test_readers.py

from datetime import (
    datetime,
    time,
)
from functools import partial
import os
from pathlib import Path
from urllib.error import URLError
from zipfile import BadZipFile

import numpy as np
import pytest

import pandas.util._test_decorators as td

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

read_ext_params = [".xls", ".xlsx", ".xlsm", ".xlsb", ".ods"]
engine_params = [
    # Add any engines to test here
    # When defusedxml is installed it triggers deprecation warnings for
    # xlrd and openpyxl, so catch those here
    pytest.param(
        "xlrd",
        marks=[
            td.skip_if_no("xlrd"),
        ],
    ),
    pytest.param(
        "openpyxl",
        marks=[
            td.skip_if_no("openpyxl"),
            pytest.mark.filterwarnings("ignore:.*html argument"),
        ],
    ),
    pytest.param(
        None,
        marks=[
            td.skip_if_no("xlrd"),
        ],
    ),
    pytest.param("pyxlsb", marks=td.skip_if_no("pyxlsb")),
    pytest.param("odf", marks=td.skip_if_no("odf")),
]


def _is_valid_engine_ext_pair(engine, read_ext: str) -> bool:
    """
    Filter out invalid (engine, ext) pairs instead of skipping, as that
    produces 500+ pytest.skips.
    """
    engine = engine.values[0]
    if engine == "openpyxl" and read_ext == ".xls":
        return False
    if engine == "odf" and read_ext != ".ods":
        return False
    if read_ext == ".ods" and engine != "odf":
        return False
    if engine == "pyxlsb" and read_ext != ".xlsb":
        return False
    if read_ext == ".xlsb" and engine != "pyxlsb":
        return False
    if engine == "xlrd" and read_ext != ".xls":
        return False
    return True


def _transfer_marks(engine, read_ext):
    """
    engine gives us a pytest.param object with some marks, read_ext is just
    a string.  We need to generate a new pytest.param inheriting the marks.
    """
    values = engine.values + (read_ext,)
    new_param = pytest.param(values, marks=engine.marks)
    return new_param


@pytest.fixture(
    params=[
        _transfer_marks(eng, ext)
        for eng in engine_params
        for ext in read_ext_params
        if _is_valid_engine_ext_pair(eng, ext)
    ],
    ids=str,
)
def engine_and_read_ext(request):
    """
    Fixture for Excel reader engine and read_ext, only including valid pairs.
    """
    return request.param


@pytest.fixture
def engine(engine_and_read_ext):
    engine, read_ext = engine_and_read_ext
    return engine


@pytest.fixture
def read_ext(engine_and_read_ext):
    engine, read_ext = engine_and_read_ext
    return read_ext


class TestReaders:
    @pytest.fixture(autouse=True)
    def cd_and_set_engine(self, engine, datapath, monkeypatch):
        """
        Change directory and set engine for read_excel calls.
        """
        func = partial(pd.read_excel, engine=engine)
        monkeypatch.chdir(datapath("io", "data", "excel"))
        monkeypatch.setattr(pd, "read_excel", func)

    def test_engine_used(self, read_ext, engine, monkeypatch):
        # GH 38884
        def parser(self, *args, **kwargs):
            return self.engine

        monkeypatch.setattr(pd.ExcelFile, "parse", parser)

        expected_defaults = {
            "xlsx": "openpyxl",
            "xlsm": "openpyxl",
            "xlsb": "pyxlsb",
            "xls": "xlrd",
            "ods": "odf",
        }

        with open("test1" + read_ext, "rb") as f:
            result = pd.read_excel(f)

        if engine is not None:
            expected = engine
        else:
            expected = expected_defaults[read_ext[1:]]
        assert result == expected

    def test_usecols_int(self, read_ext):
        # usecols as int
        msg = "Passing an integer for `usecols`"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel(
                "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols=3
            )

        # usecols as int
        with pytest.raises(ValueError, match=msg):
            pd.read_excel(
                "test1" + read_ext,
                sheet_name="Sheet2",
                skiprows=[1],
                index_col=0,
                usecols=3,
            )

    def test_usecols_list(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        df_ref = df_ref.reindex(columns=["B", "C"])
        df1 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols=[0, 2, 3]
        )
        df2 = pd.read_excel(
            "test1" + read_ext,
            sheet_name="Sheet2",
            skiprows=[1],
            index_col=0,
            usecols=[0, 2, 3],
        )

        # TODO add index to xls file)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

    def test_usecols_str(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        df1 = df_ref.reindex(columns=["A", "B", "C"])
        df2 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols="A:D"
        )
        df3 = pd.read_excel(
            "test1" + read_ext,
            sheet_name="Sheet2",
            skiprows=[1],
            index_col=0,
            usecols="A:D",
        )

        # TODO add index to xls, read xls ignores index name ?
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

        df1 = df_ref.reindex(columns=["B", "C"])
        df2 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols="A,C,D"
        )
        df3 = pd.read_excel(
            "test1" + read_ext,
            sheet_name="Sheet2",
            skiprows=[1],
            index_col=0,
            usecols="A,C,D",
        )
        # TODO add index to xls file
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

        df1 = df_ref.reindex(columns=["B", "C"])
        df2 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols="A,C:D"
        )
        df3 = pd.read_excel(
            "test1" + read_ext,
            sheet_name="Sheet2",
            skiprows=[1],
            index_col=0,
            usecols="A,C:D",
        )
        tm.assert_frame_equal(df2, df1, check_names=False)
        tm.assert_frame_equal(df3, df1, check_names=False)

    @pytest.mark.parametrize(
        "usecols", [[0, 1, 3], [0, 3, 1], [1, 0, 3], [1, 3, 0], [3, 0, 1], [3, 1, 0]]
    )
    def test_usecols_diff_positional_int_columns_order(
        self, request, read_ext, usecols, df_ref
    ):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        expected = df_ref[["A", "C"]]
        result = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols=usecols
        )
        tm.assert_frame_equal(result, expected, check_names=False)

    @pytest.mark.parametrize("usecols", [["B", "D"], ["D", "B"]])
    def test_usecols_diff_positional_str_columns_order(self, read_ext, usecols, df_ref):
        expected = df_ref[["B", "D"]]
        expected.index = range(len(expected))

        result = pd.read_excel("test1" + read_ext, sheet_name="Sheet1", usecols=usecols)
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_read_excel_without_slicing(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        expected = df_ref
        result = pd.read_excel("test1" + read_ext, sheet_name="Sheet1", index_col=0)
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_usecols_excel_range_str(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        expected = df_ref[["C", "D"]]
        result = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, usecols="A,D:E"
        )
        tm.assert_frame_equal(result, expected, check_names=False)

    def test_usecols_excel_range_str_invalid(self, read_ext):
        msg = "Invalid column name: E1"

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, sheet_name="Sheet1", usecols="D:E1")

    def test_index_col_label_error(self, read_ext):
        msg = "list indices must be integers.*, not str"

        with pytest.raises(TypeError, match=msg):
            pd.read_excel(
                "test1" + read_ext,
                sheet_name="Sheet1",
                index_col=["A"],
                usecols=["A", "C"],
            )

    def test_index_col_empty(self, read_ext):
        # see gh-9208
        result = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet3", index_col=["A", "B", "C"]
        )
        expected = DataFrame(
            columns=["D", "E", "F"],
            index=MultiIndex(levels=[[]] * 3, codes=[[]] * 3, names=["A", "B", "C"]),
        )
        tm.assert_frame_equal(result, expected)

    @pytest.mark.parametrize("index_col", [None, 2])
    def test_index_col_with_unnamed(self, read_ext, index_col):
        # see gh-18792
        result = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet4", index_col=index_col
        )
        expected = DataFrame(
            [["i1", "a", "x"], ["i2", "b", "y"]], columns=["Unnamed: 0", "col1", "col2"]
        )
        if index_col:
            expected = expected.set_index(expected.columns[index_col])

        tm.assert_frame_equal(result, expected)

    def test_usecols_pass_non_existent_column(self, read_ext):
        msg = (
            "Usecols do not match columns, "
            "columns expected but not found: " + r"\['E'\]"
        )

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, usecols=["E"])

    def test_usecols_wrong_type(self, read_ext):
        msg = (
            "'usecols' must either be list-like of "
            "all strings, all unicode, all integers or a callable."
        )

        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, usecols=["E1", 0])

    def test_excel_stop_iterator(self, read_ext):

        parsed = pd.read_excel("test2" + read_ext, sheet_name="Sheet1")
        expected = DataFrame([["aaaa", "bbbbb"]], columns=["Test", "Test1"])
        tm.assert_frame_equal(parsed, expected)

    def test_excel_cell_error_na(self, request, read_ext):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        parsed = pd.read_excel("test3" + read_ext, sheet_name="Sheet1")
        expected = DataFrame([[np.nan]], columns=["Test"])
        tm.assert_frame_equal(parsed, expected)

    def test_excel_table(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        df1 = pd.read_excel("test1" + read_ext, sheet_name="Sheet1", index_col=0)
        df2 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet2", skiprows=[1], index_col=0
        )
        # TODO add index to file
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        df3 = pd.read_excel(
            "test1" + read_ext, sheet_name="Sheet1", index_col=0, skipfooter=1
        )
        tm.assert_frame_equal(df3, df1.iloc[:-1])

    def test_reader_special_dtypes(self, request, read_ext):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        expected = DataFrame.from_dict(
            {
                "IntCol": [1, 2, -3, 4, 0],
                "FloatCol": [1.25, 2.25, 1.83, 1.92, 0.0000000005],
                "BoolCol": [True, False, True, True, False],
                "StrCol": [1, 2, 3, 4, 5],
                # GH5394 - this is why convert_float isn't vectorized
                "Str2Col": ["a", 3, "c", "d", "e"],
                "DateCol": [
                    datetime(2013, 10, 30),
                    datetime(2013, 10, 31),
                    datetime(1905, 1, 1),
                    datetime(2013, 12, 14),
                    datetime(2015, 3, 14),
                ],
            },
        )
        basename = "test_types"

        # should read in correctly and infer types
        actual = pd.read_excel(basename + read_ext, sheet_name="Sheet1")
        tm.assert_frame_equal(actual, expected)

        # if not coercing number, then int comes in as float
        float_expected = expected.copy()
        float_expected["IntCol"] = float_expected["IntCol"].astype(float)
        float_expected.loc[float_expected.index[1], "Str2Col"] = 3.0
        with tm.assert_produces_warning(
            FutureWarning,
            match="convert_float is deprecated",
            raise_on_extra_warnings=False,
        ):
            # raise_on_extra_warnings because xlrd raises a PendingDeprecationWarning
            # on database job Linux_py37_IO (ci/deps/actions-37-db.yaml)
            # See GH#41176
            actual = pd.read_excel(
                basename + read_ext, sheet_name="Sheet1", convert_float=False
            )
        tm.assert_frame_equal(actual, float_expected)

        # check setting Index (assuming xls and xlsx are the same here)
        for icol, name in enumerate(expected.columns):
            actual = pd.read_excel(
                basename + read_ext, sheet_name="Sheet1", index_col=icol
            )
            exp = expected.set_index(name)
            tm.assert_frame_equal(actual, exp)

        # convert_float and converters should be different but both accepted
        expected["StrCol"] = expected["StrCol"].apply(str)
        actual = pd.read_excel(
            basename + read_ext, sheet_name="Sheet1", converters={"StrCol": str}
        )
        tm.assert_frame_equal(actual, expected)

        no_convert_float = float_expected.copy()
        no_convert_float["StrCol"] = no_convert_float["StrCol"].apply(str)
        with tm.assert_produces_warning(
            FutureWarning,
            match="convert_float is deprecated",
            raise_on_extra_warnings=False,
        ):
            # raise_on_extra_warnings because xlrd raises a PendingDeprecationWarning
            # on database job Linux_py37_IO (ci/deps/actions-37-db.yaml)
            # See GH#41176
            actual = pd.read_excel(
                basename + read_ext,
                sheet_name="Sheet1",
                convert_float=False,
                converters={"StrCol": str},
            )
        tm.assert_frame_equal(actual, no_convert_float)

    # GH8212 - support for converters and missing values
    def test_reader_converters(self, read_ext):

        basename = "test_converters"

        expected = DataFrame.from_dict(
            {
                "IntCol": [1, 2, -3, -1000, 0],
                "FloatCol": [12.5, np.nan, 18.3, 19.2, 0.000000005],
                "BoolCol": ["Found", "Found", "Found", "Not found", "Found"],
                "StrCol": ["1", np.nan, "3", "4", "5"],
            }
        )

        converters = {
            "IntCol": lambda x: int(x) if x != "" else -1000,
            "FloatCol": lambda x: 10 * x if x else np.nan,
            2: lambda x: "Found" if x != "" else "Not found",
            3: lambda x: str(x) if x else "",
        }

        # should read in correctly and set types of single cells (not array
        # dtypes)
        actual = pd.read_excel(
            basename + read_ext, sheet_name="Sheet1", converters=converters
        )
        tm.assert_frame_equal(actual, expected)

    def test_reader_dtype(self, read_ext):
        # GH 8212
        basename = "testdtype"
        actual = pd.read_excel(basename + read_ext)

        expected = DataFrame(
            {
                "a": [1, 2, 3, 4],
                "b": [2.5, 3.5, 4.5, 5.5],
                "c": [1, 2, 3, 4],
                "d": [1.0, 2.0, np.nan, 4.0],
            }
        ).reindex(columns=["a", "b", "c", "d"])

        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(
            basename + read_ext, dtype={"a": "float64", "b": "float32", "c": str}
        )

        expected["a"] = expected["a"].astype("float64")
        expected["b"] = expected["b"].astype("float32")
        expected["c"] = ["001", "002", "003", "004"]
        tm.assert_frame_equal(actual, expected)

        msg = "Unable to convert column d to type int64"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel(basename + read_ext, dtype={"d": "int64"})

    @pytest.mark.parametrize(
        "dtype,expected",
        [
            (
                None,
                DataFrame(
                    {
                        "a": [1, 2, 3, 4],
                        "b": [2.5, 3.5, 4.5, 5.5],
                        "c": [1, 2, 3, 4],
                        "d": [1.0, 2.0, np.nan, 4.0],
                    }
                ),
            ),
            (
                {"a": "float64", "b": "float32", "c": str, "d": str},
                DataFrame(
                    {
                        "a": Series([1, 2, 3, 4], dtype="float64"),
                        "b": Series([2.5, 3.5, 4.5, 5.5], dtype="float32"),
                        "c": ["001", "002", "003", "004"],
                        "d": ["1", "2", np.nan, "4"],
                    }
                ),
            ),
        ],
    )
    def test_reader_dtype_str(self, read_ext, dtype, expected):
        # see gh-20377
        basename = "testdtype"

        actual = pd.read_excel(basename + read_ext, dtype=dtype)
        tm.assert_frame_equal(actual, expected)

    @pytest.mark.parametrize("dtypes, exp_value", [({}, "1"), ({"a.1": "int64"}, 1)])
    def test_dtype_mangle_dup_cols(self, read_ext, dtypes, exp_value):
        # GH#35211
        basename = "df_mangle_dup_col_dtypes"
        dtype_dict = {"a": str, **dtypes}
        dtype_dict_copy = dtype_dict.copy()
        # GH#42462
        result = pd.read_excel(basename + read_ext, dtype=dtype_dict)
        expected = DataFrame({"a": ["1"], "a.1": [exp_value]})
        assert dtype_dict == dtype_dict_copy, "dtype dict changed"
        tm.assert_frame_equal(result, expected)

    def test_reader_spaces(self, read_ext):
        # see gh-32207
        basename = "test_spaces"

        actual = pd.read_excel(basename + read_ext)
        expected = DataFrame(
            {
                "testcol": [
                    "this is great",
                    "4    spaces",
                    "1 trailing ",
                    " 1 leading",
                    "2  spaces  multiple  times",
                ]
            }
        )
        tm.assert_frame_equal(actual, expected)

    # gh-36122, gh-35802
    @pytest.mark.parametrize(
        "basename,expected",
        [
            ("gh-35802", DataFrame({"COLUMN": ["Test (1)"]})),
            ("gh-36122", DataFrame(columns=["got 2nd sa"])),
        ],
    )
    def test_read_excel_ods_nested_xml(self, engine, read_ext, basename, expected):
        # see gh-35802
        if engine != "odf":
            pytest.skip(f"Skipped for engine: {engine}")

        actual = pd.read_excel(basename + read_ext)
        tm.assert_frame_equal(actual, expected)

    def test_reading_all_sheets(self, read_ext):
        # Test reading all sheet names by setting sheet_name to None,
        # Ensure a dict is returned.
        # See PR #9450
        basename = "test_multisheet"
        dfs = pd.read_excel(basename + read_ext, sheet_name=None)
        # ensure this is not alphabetical to test order preservation
        expected_keys = ["Charlie", "Alpha", "Beta"]
        tm.assert_contains_all(expected_keys, dfs.keys())
        # Issue 9930
        # Ensure sheet order is preserved
        assert expected_keys == list(dfs.keys())

    def test_reading_multiple_specific_sheets(self, read_ext):
        # Test reading specific sheet names by specifying a mixed list
        # of integers and strings, and confirm that duplicated sheet
        # references (positions/names) are removed properly.
        # Ensure a dict is returned
        # See PR #9450
        basename = "test_multisheet"
        # Explicitly request duplicates. Only the set should be returned.
        expected_keys = [2, "Charlie", "Charlie"]
        dfs = pd.read_excel(basename + read_ext, sheet_name=expected_keys)
        expected_keys = list(set(expected_keys))
        tm.assert_contains_all(expected_keys, dfs.keys())
        assert len(expected_keys) == len(dfs.keys())

    def test_reading_all_sheets_with_blank(self, read_ext):
        # Test reading all sheet names by setting sheet_name to None,
        # In the case where some sheets are blank.
        # Issue #11711
        basename = "blank_with_header"
        dfs = pd.read_excel(basename + read_ext, sheet_name=None)
        expected_keys = ["Sheet1", "Sheet2", "Sheet3"]
        tm.assert_contains_all(expected_keys, dfs.keys())

    # GH6403
    def test_read_excel_blank(self, read_ext):
        actual = pd.read_excel("blank" + read_ext, sheet_name="Sheet1")
        tm.assert_frame_equal(actual, DataFrame())

    def test_read_excel_blank_with_header(self, read_ext):
        expected = DataFrame(columns=["col_1", "col_2"])
        actual = pd.read_excel("blank_with_header" + read_ext, sheet_name="Sheet1")
        tm.assert_frame_equal(actual, expected)

    @pytest.mark.filterwarnings("ignore:Cell A4 is marked:UserWarning:openpyxl")
    def test_date_conversion_overflow(self, request, engine, read_ext):
        # GH 10001 : pandas.ExcelFile ignore parse_dates=False
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        expected = DataFrame(
            [
                [pd.Timestamp("2016-03-12"), "Marc Johnson"],
                [pd.Timestamp("2016-03-16"), "Jack Black"],
                [1e20, "Timothy Brown"],
            ],
            columns=["DateColWithBigInt", "StringCol"],
        )

        if engine == "openpyxl":
            request.node.add_marker(
                pytest.mark.xfail(reason="Maybe not supported by openpyxl")
            )

        if engine is None and read_ext in (".xlsx", ".xlsm"):
            # GH 35029
            request.node.add_marker(
                pytest.mark.xfail(reason="Defaults to openpyxl, maybe not supported")
            )

        result = pd.read_excel("testdateoverflow" + read_ext)
        tm.assert_frame_equal(result, expected)

    def test_sheet_name(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )
        filename = "test1"
        sheet_name = "Sheet1"

        df1 = pd.read_excel(
            filename + read_ext, sheet_name=sheet_name, index_col=0
        )  # doc
        df2 = pd.read_excel(filename + read_ext, index_col=0, sheet_name=sheet_name)

        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

    def test_excel_read_buffer(self, read_ext):

        pth = "test1" + read_ext
        expected = pd.read_excel(pth, sheet_name="Sheet1", index_col=0)
        with open(pth, "rb") as f:
            actual = pd.read_excel(f, sheet_name="Sheet1", index_col=0)
            tm.assert_frame_equal(expected, actual)

    def test_bad_engine_raises(self):
        bad_engine = "foo"
        with pytest.raises(ValueError, match="Unknown engine: foo"):
            pd.read_excel("", engine=bad_engine)

    @pytest.mark.parametrize(
        "sheet_name",
        [3, [0, 3], [3, 0], "Sheet4", ["Sheet1", "Sheet4"], ["Sheet4", "Sheet1"]],
    )
    def test_bad_sheetname_raises(self, read_ext, sheet_name):
        # GH 39250
        msg = "Worksheet index 3 is invalid|Worksheet named 'Sheet4' not found"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel("blank" + read_ext, sheet_name=sheet_name)

    def test_missing_file_raises(self, read_ext):
        bad_file = f"foo{read_ext}"
        # CI tests with other languages, translates to "No such file or directory"
        match = r"(No such file or directory|没有那个文件或目录|File o directory non esistente)"
        with pytest.raises(FileNotFoundError, match=match):
            pd.read_excel(bad_file)

    def test_corrupt_bytes_raises(self, engine):
        bad_stream = b"foo"
        if engine is None:
            error = ValueError
            msg = (
                "Excel file format cannot be determined, you must "
                "specify an engine manually."
            )
        elif engine == "xlrd":
            from xlrd import XLRDError

            error = XLRDError
            msg = (
                "Unsupported format, or corrupt file: Expected BOF "
                "record; found b'foo'"
            )
        else:
            error = BadZipFile
            msg = "File is not a zip file"
        with pytest.raises(error, match=msg):
            pd.read_excel(bad_stream)

    @pytest.mark.network
    @tm.network(
        url=(
            "https://raw.githubusercontent.com/pandas-dev/pandas/main/"
            "pandas/tests/io/data/excel/test1.xlsx"
        ),
        check_before_test=True,
    )
    def test_read_from_http_url(self, read_ext):
        url = (
            "https://raw.githubusercontent.com/pandas-dev/pandas/main/"
            "pandas/tests/io/data/excel/test1" + read_ext
        )
        url_table = pd.read_excel(url)
        local_table = pd.read_excel("test1" + read_ext)
        tm.assert_frame_equal(url_table, local_table)

    @td.skip_if_not_us_locale
    @pytest.mark.single_cpu
    def test_read_from_s3_url(self, read_ext, s3_resource, s3so):
        # Bucket "pandas-test" created in tests/io/conftest.py
        with open("test1" + read_ext, "rb") as f:
            s3_resource.Bucket("pandas-test").put_object(Key="test1" + read_ext, Body=f)

        url = "s3://pandas-test/test1" + read_ext

        url_table = pd.read_excel(url, storage_options=s3so)
        local_table = pd.read_excel("test1" + read_ext)
        tm.assert_frame_equal(url_table, local_table)

    @pytest.mark.single_cpu
    def test_read_from_s3_object(self, read_ext, s3_resource, s3so):
        # GH 38788
        # Bucket "pandas-test" created in tests/io/conftest.py
        with open("test1" + read_ext, "rb") as f:
            s3_resource.Bucket("pandas-test").put_object(Key="test1" + read_ext, Body=f)

        import s3fs

        s3 = s3fs.S3FileSystem(**s3so)

        with s3.open("s3://pandas-test/test1" + read_ext) as f:
            url_table = pd.read_excel(f)

        local_table = pd.read_excel("test1" + read_ext)
        tm.assert_frame_equal(url_table, local_table)

    @pytest.mark.slow
    def test_read_from_file_url(self, read_ext, datapath):

        # FILE
        localtable = os.path.join(datapath("io", "data", "excel"), "test1" + read_ext)
        local_table = pd.read_excel(localtable)

        try:
            url_table = pd.read_excel("file://localhost/" + localtable)
        except URLError:
            # fails on some systems
            import platform

            platform_info = " ".join(platform.uname()).strip()
            pytest.skip(f"failing on {platform_info}")

        tm.assert_frame_equal(url_table, local_table)

    def test_read_from_pathlib_path(self, read_ext):

        # GH12655
        from pathlib import Path

        str_path = "test1" + read_ext
        expected = pd.read_excel(str_path, sheet_name="Sheet1", index_col=0)

        path_obj = Path("test1" + read_ext)
        actual = pd.read_excel(path_obj, sheet_name="Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    @td.skip_if_no("py.path")
    @td.check_file_leaks
    def test_read_from_py_localpath(self, read_ext):

        # GH12655
        from py.path import local as LocalPath

        str_path = os.path.join("test1" + read_ext)
        expected = pd.read_excel(str_path, sheet_name="Sheet1", index_col=0)

        path_obj = LocalPath().join("test1" + read_ext)
        actual = pd.read_excel(path_obj, sheet_name="Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    @td.check_file_leaks
    def test_close_from_py_localpath(self, read_ext):

        # GH31467
        str_path = os.path.join("test1" + read_ext)
        with open(str_path, "rb") as f:
            x = pd.read_excel(f, sheet_name="Sheet1", index_col=0)
            del x
            # should not throw an exception because the passed file was closed
            f.read()

    def test_reader_seconds(self, request, engine, read_ext):
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        # Test reading times with and without milliseconds. GH5945.
        expected = DataFrame.from_dict(
            {
                "Time": [
                    time(1, 2, 3),
                    time(2, 45, 56, 100000),
                    time(4, 29, 49, 200000),
                    time(6, 13, 42, 300000),
                    time(7, 57, 35, 400000),
                    time(9, 41, 28, 500000),
                    time(11, 25, 21, 600000),
                    time(13, 9, 14, 700000),
                    time(14, 53, 7, 800000),
                    time(16, 37, 0, 900000),
                    time(18, 20, 54),
                ]
            }
        )

        actual = pd.read_excel("times_1900" + read_ext, sheet_name="Sheet1")
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel("times_1904" + read_ext, sheet_name="Sheet1")
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_multiindex(self, request, read_ext):
        # see gh-4679
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        mi = MultiIndex.from_product([["foo", "bar"], ["a", "b"]])
        mi_file = "testmultiindex" + read_ext

        # "mi_column" sheet
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=mi,
        )

        actual = pd.read_excel(
            mi_file, sheet_name="mi_column", header=[0, 1], index_col=0
        )
        tm.assert_frame_equal(actual, expected)

        # "mi_index" sheet
        expected.index = mi
        expected.columns = ["a", "b", "c", "d"]

        actual = pd.read_excel(mi_file, sheet_name="mi_index", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected, check_names=False)

        # "both" sheet
        expected.columns = mi

        actual = pd.read_excel(
            mi_file, sheet_name="both", index_col=[0, 1], header=[0, 1]
        )
        tm.assert_frame_equal(actual, expected, check_names=False)

        # "mi_index_name" sheet
        expected.columns = ["a", "b", "c", "d"]
        expected.index = mi.set_names(["ilvl1", "ilvl2"])

        actual = pd.read_excel(mi_file, sheet_name="mi_index_name", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # "mi_column_name" sheet
        expected.index = list(range(4))
        expected.columns = mi.set_names(["c1", "c2"])
        actual = pd.read_excel(
            mi_file, sheet_name="mi_column_name", header=[0, 1], index_col=0
        )
        tm.assert_frame_equal(actual, expected)

        # see gh-11317
        # "name_with_int" sheet
        expected.columns = mi.set_levels([1, 2], level=1).set_names(["c1", "c2"])

        actual = pd.read_excel(
            mi_file, sheet_name="name_with_int", index_col=0, header=[0, 1]
        )
        tm.assert_frame_equal(actual, expected)

        # "both_name" sheet
        expected.columns = mi.set_names(["c1", "c2"])
        expected.index = mi.set_names(["ilvl1", "ilvl2"])

        actual = pd.read_excel(
            mi_file, sheet_name="both_name", index_col=[0, 1], header=[0, 1]
        )
        tm.assert_frame_equal(actual, expected)

        # "both_skiprows" sheet
        actual = pd.read_excel(
            mi_file,
            sheet_name="both_name_skiprows",
            index_col=[0, 1],
            header=[0, 1],
            skiprows=2,
        )
        tm.assert_frame_equal(actual, expected)

    @pytest.mark.parametrize(
        "sheet_name,idx_lvl2",
        [
            ("both_name_blank_after_mi_name", [np.nan, "b", "a", "b"]),
            ("both_name_multiple_blanks", [np.nan] * 4),
        ],
    )
    def test_read_excel_multiindex_blank_after_name(
        self, request, read_ext, sheet_name, idx_lvl2
    ):
        # GH34673
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb (GH4679"
                )
            )

        mi_file = "testmultiindex" + read_ext
        mi = MultiIndex.from_product([["foo", "bar"], ["a", "b"]], names=["c1", "c2"])
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=mi,
            index=MultiIndex.from_arrays(
                (["foo", "foo", "bar", "bar"], idx_lvl2),
                names=["ilvl1", "ilvl2"],
            ),
        )
        result = pd.read_excel(
            mi_file,
            sheet_name=sheet_name,
            index_col=[0, 1],
            header=[0, 1],
        )
        tm.assert_frame_equal(result, expected)

    def test_read_excel_multiindex_header_only(self, read_ext):
        # see gh-11733.
        #
        # Don't try to parse a header name if there isn't one.
        mi_file = "testmultiindex" + read_ext
        result = pd.read_excel(mi_file, sheet_name="index_col_none", header=[0, 1])

        exp_columns = MultiIndex.from_product([("A", "B"), ("key", "val")])
        expected = DataFrame([[1, 2, 3, 4]] * 2, columns=exp_columns)
        tm.assert_frame_equal(result, expected)

    def test_excel_old_index_format(self, read_ext):
        # see gh-4679
        filename = "test_index_name_pre17" + read_ext

        # We detect headers to determine if index names exist, so
        # that "index" name in the "names" version of the data will
        # now be interpreted as rows that include null data.
        data = np.array(
            [
                [None, None, None, None, None],
                ["R0C0", "R0C1", "R0C2", "R0C3", "R0C4"],
                ["R1C0", "R1C1", "R1C2", "R1C3", "R1C4"],
                ["R2C0", "R2C1", "R2C2", "R2C3", "R2C4"],
                ["R3C0", "R3C1", "R3C2", "R3C3", "R3C4"],
                ["R4C0", "R4C1", "R4C2", "R4C3", "R4C4"],
            ]
        )
        columns = ["C_l0_g0", "C_l0_g1", "C_l0_g2", "C_l0_g3", "C_l0_g4"]
        mi = MultiIndex(
            levels=[
                ["R0", "R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"],
                ["R1", "R_l1_g0", "R_l1_g1", "R_l1_g2", "R_l1_g3", "R_l1_g4"],
            ],
            codes=[[0, 1, 2, 3, 4, 5], [0, 1, 2, 3, 4, 5]],
            names=[None, None],
        )
        si = Index(
            ["R0", "R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"], name=None
        )

        expected = DataFrame(data, index=si, columns=columns)

        actual = pd.read_excel(filename, sheet_name="single_names", index_col=0)
        tm.assert_frame_equal(actual, expected)

        expected.index = mi

        actual = pd.read_excel(filename, sheet_name="multi_names", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected)

        # The analogous versions of the "names" version data
        # where there are explicitly no names for the indices.
        data = np.array(
            [
                ["R0C0", "R0C1", "R0C2", "R0C3", "R0C4"],
                ["R1C0", "R1C1", "R1C2", "R1C3", "R1C4"],
                ["R2C0", "R2C1", "R2C2", "R2C3", "R2C4"],
                ["R3C0", "R3C1", "R3C2", "R3C3", "R3C4"],
                ["R4C0", "R4C1", "R4C2", "R4C3", "R4C4"],
            ]
        )
        columns = ["C_l0_g0", "C_l0_g1", "C_l0_g2", "C_l0_g3", "C_l0_g4"]
        mi = MultiIndex(
            levels=[
                ["R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"],
                ["R_l1_g0", "R_l1_g1", "R_l1_g2", "R_l1_g3", "R_l1_g4"],
            ],
            codes=[[0, 1, 2, 3, 4], [0, 1, 2, 3, 4]],
            names=[None, None],
        )
        si = Index(["R_l0_g0", "R_l0_g1", "R_l0_g2", "R_l0_g3", "R_l0_g4"], name=None)

        expected = DataFrame(data, index=si, columns=columns)

        actual = pd.read_excel(filename, sheet_name="single_no_names", index_col=0)
        tm.assert_frame_equal(actual, expected)

        expected.index = mi

        actual = pd.read_excel(filename, sheet_name="multi_no_names", index_col=[0, 1])
        tm.assert_frame_equal(actual, expected, check_names=False)

    def test_read_excel_bool_header_arg(self, read_ext):
        # GH 6114
        msg = "Passing a bool to header is invalid"
        for arg in [True, False]:
            with pytest.raises(TypeError, match=msg):
                pd.read_excel("test1" + read_ext, header=arg)

    def test_read_excel_skiprows(self, request, read_ext):
        # GH 4903
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        actual = pd.read_excel(
            "testskiprows" + read_ext, sheet_name="skiprows_list", skiprows=[0, 2]
        )
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=["a", "b", "c", "d"],
        )
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(
            "testskiprows" + read_ext,
            sheet_name="skiprows_list",
            skiprows=np.array([0, 2]),
        )
        tm.assert_frame_equal(actual, expected)

        # GH36435
        actual = pd.read_excel(
            "testskiprows" + read_ext,
            sheet_name="skiprows_list",
            skiprows=lambda x: x in [0, 2],
        )
        tm.assert_frame_equal(actual, expected)

        actual = pd.read_excel(
            "testskiprows" + read_ext,
            sheet_name="skiprows_list",
            skiprows=3,
            names=["a", "b", "c", "d"],
        )
        expected = DataFrame(
            [
                # [1, 2.5, pd.Timestamp("2015-01-01"), True],
                [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=["a", "b", "c", "d"],
        )
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_skiprows_callable_not_in(self, request, read_ext):
        # GH 4903
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        actual = pd.read_excel(
            "testskiprows" + read_ext,
            sheet_name="skiprows_list",
            skiprows=lambda x: x not in [1, 3, 5],
        )
        expected = DataFrame(
            [
                [1, 2.5, pd.Timestamp("2015-01-01"), True],
                # [2, 3.5, pd.Timestamp("2015-01-02"), False],
                [3, 4.5, pd.Timestamp("2015-01-03"), False],
                # [4, 5.5, pd.Timestamp("2015-01-04"), True],
            ],
            columns=["a", "b", "c", "d"],
        )
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows(self, read_ext):
        # GH 16645
        num_rows_to_pull = 5
        actual = pd.read_excel("test1" + read_ext, nrows=num_rows_to_pull)
        expected = pd.read_excel("test1" + read_ext)
        expected = expected[:num_rows_to_pull]
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows_greater_than_nrows_in_file(self, read_ext):
        # GH 16645
        expected = pd.read_excel("test1" + read_ext)
        num_records_in_file = len(expected)
        num_rows_to_pull = num_records_in_file + 10
        actual = pd.read_excel("test1" + read_ext, nrows=num_rows_to_pull)
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_nrows_non_integer_parameter(self, read_ext):
        # GH 16645
        msg = "'nrows' must be an integer >=0"
        with pytest.raises(ValueError, match=msg):
            pd.read_excel("test1" + read_ext, nrows="5")

    @pytest.mark.parametrize(
        "filename,sheet_name,header,index_col,skiprows",
        [
            ("testmultiindex", "mi_column", [0, 1], 0, None),
            ("testmultiindex", "mi_index", None, [0, 1], None),
            ("testmultiindex", "both", [0, 1], [0, 1], None),
            ("testmultiindex", "mi_column_name", [0, 1], 0, None),
            ("testskiprows", "skiprows_list", None, None, [0, 2]),
            ("testskiprows", "skiprows_list", None, None, lambda x: x in (0, 2)),
        ],
    )
    def test_read_excel_nrows_params(
        self, read_ext, filename, sheet_name, header, index_col, skiprows
    ):
        """
        For various parameters, we should get the same result whether we
        limit the rows during load (nrows=3) or after (df.iloc[:3]).
        """
        # GH 46894
        expected = pd.read_excel(
            filename + read_ext,
            sheet_name=sheet_name,
            header=header,
            index_col=index_col,
            skiprows=skiprows,
        ).iloc[:3]
        actual = pd.read_excel(
            filename + read_ext,
            sheet_name=sheet_name,
            header=header,
            index_col=index_col,
            skiprows=skiprows,
            nrows=3,
        )
        tm.assert_frame_equal(actual, expected)

    def test_read_excel_squeeze(self, read_ext):
        # GH 12157
        f = "test_squeeze" + read_ext

        with tm.assert_produces_warning(
            FutureWarning,
            match="The squeeze argument has been deprecated "
            "and will be removed in a future version. "
            'Append .squeeze\\("columns"\\) to the call to squeeze.\n\n',
        ):
            actual = pd.read_excel(
                f, sheet_name="two_columns", index_col=0, squeeze=True
            )
            expected = Series([2, 3, 4], [4, 5, 6], name="b")
            expected.index.name = "a"
            tm.assert_series_equal(actual, expected)

            actual = pd.read_excel(f, sheet_name="two_columns", squeeze=True)
            expected = DataFrame({"a": [4, 5, 6], "b": [2, 3, 4]})
            tm.assert_frame_equal(actual, expected)

            actual = pd.read_excel(f, sheet_name="one_column", squeeze=True)
            expected = Series([1, 2, 3], name="a")
            tm.assert_series_equal(actual, expected)

    def test_deprecated_kwargs(self, read_ext):
        with tm.assert_produces_warning(FutureWarning, raise_on_extra_warnings=False):
            pd.read_excel("test1" + read_ext, "Sheet1", 0)

        pd.read_excel("test1" + read_ext)

    def test_no_header_with_list_index_col(self, read_ext):
        # GH 31783
        file_name = "testmultiindex" + read_ext
        data = [("B", "B"), ("key", "val"), (3, 4), (3, 4)]
        idx = MultiIndex.from_tuples(
            [("A", "A"), ("key", "val"), (1, 2), (1, 2)], names=(0, 1)
        )
        expected = DataFrame(data, index=idx, columns=(2, 3))
        result = pd.read_excel(
            file_name, sheet_name="index_col_none", index_col=[0, 1], header=None
        )
        tm.assert_frame_equal(expected, result)

    def test_one_col_noskip_blank_line(self, read_ext):
        # GH 39808
        file_name = "one_col_blank_line" + read_ext
        data = [0.5, np.nan, 1, 2]
        expected = DataFrame(data, columns=["numbers"])
        result = pd.read_excel(file_name)
        tm.assert_frame_equal(result, expected)

    def test_multiheader_two_blank_lines(self, read_ext):
        # GH 40442
        file_name = "testmultiindex" + read_ext
        columns = MultiIndex.from_tuples([("a", "A"), ("b", "B")])
        data = [[np.nan, np.nan], [np.nan, np.nan], [1, 3], [2, 4]]
        expected = DataFrame(data, columns=columns)
        result = pd.read_excel(
            file_name, sheet_name="mi_column_empty_rows", header=[0, 1]
        )
        tm.assert_frame_equal(result, expected)

    def test_trailing_blanks(self, read_ext):
        """
        Sheets can contain blank cells with no data. Some of our readers
        were including those cells, creating many empty rows and columns
        """
        file_name = "trailing_blanks" + read_ext
        result = pd.read_excel(file_name)
        assert result.shape == (3, 3)

    def test_ignore_chartsheets_by_str(self, request, engine, read_ext):
        # GH 41448
        if engine == "odf":
            pytest.skip("chartsheets do not exist in the ODF format")
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="pyxlsb can't distinguish chartsheets from worksheets"
                )
            )
        with pytest.raises(ValueError, match="Worksheet named 'Chart1' not found"):
            pd.read_excel("chartsheet" + read_ext, sheet_name="Chart1")

    def test_ignore_chartsheets_by_int(self, request, engine, read_ext):
        # GH 41448
        if engine == "odf":
            pytest.skip("chartsheets do not exist in the ODF format")
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="pyxlsb can't distinguish chartsheets from worksheets"
                )
            )
        with pytest.raises(
            ValueError, match="Worksheet index 1 is invalid, 1 worksheets found"
        ):
            pd.read_excel("chartsheet" + read_ext, sheet_name=1)

    def test_euro_decimal_format(self, read_ext):
        # copied from read_csv
        result = pd.read_excel("test_decimal" + read_ext, decimal=",", skiprows=1)
        expected = DataFrame(
            [
                [1, 1521.1541, 187101.9543, "ABC", "poi", 4.738797819],
                [2, 121.12, 14897.76, "DEF", "uyt", 0.377320872],
                [3, 878.158, 108013.434, "GHI", "rez", 2.735694704],
            ],
            columns=["Id", "Number1", "Number2", "Text1", "Text2", "Number3"],
        )
        tm.assert_frame_equal(result, expected)


class TestExcelFileRead:
    @pytest.fixture(autouse=True)
    def cd_and_set_engine(self, engine, datapath, monkeypatch):
        """
        Change directory and set engine for ExcelFile objects.
        """
        func = partial(pd.ExcelFile, engine=engine)
        monkeypatch.chdir(datapath("io", "data", "excel"))
        monkeypatch.setattr(pd, "ExcelFile", func)

    def test_engine_used(self, read_ext, engine):
        expected_defaults = {
            "xlsx": "openpyxl",
            "xlsm": "openpyxl",
            "xlsb": "pyxlsb",
            "xls": "xlrd",
            "ods": "odf",
        }

        with pd.ExcelFile("test1" + read_ext) as excel:
            result = excel.engine

        if engine is not None:
            expected = engine
        else:
            expected = expected_defaults[read_ext[1:]]
        assert result == expected

    def test_excel_passes_na(self, read_ext):
        with pd.ExcelFile("test4" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, sheet_name="Sheet1", keep_default_na=False, na_values=["apple"]
            )
        expected = DataFrame(
            [["NA"], [1], ["NA"], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        with pd.ExcelFile("test4" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, sheet_name="Sheet1", keep_default_na=True, na_values=["apple"]
            )
        expected = DataFrame(
            [[np.nan], [1], [np.nan], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        # 13967
        with pd.ExcelFile("test5" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, sheet_name="Sheet1", keep_default_na=False, na_values=["apple"]
            )
        expected = DataFrame(
            [["1.#QNAN"], [1], ["nan"], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

        with pd.ExcelFile("test5" + read_ext) as excel:
            parsed = pd.read_excel(
                excel, sheet_name="Sheet1", keep_default_na=True, na_values=["apple"]
            )
        expected = DataFrame(
            [[np.nan], [1], [np.nan], [np.nan], ["rabbit"]], columns=["Test"]
        )
        tm.assert_frame_equal(parsed, expected)

    @pytest.mark.parametrize("na_filter", [None, True, False])
    def test_excel_passes_na_filter(self, read_ext, na_filter):
        # gh-25453
        kwargs = {}

        if na_filter is not None:
            kwargs["na_filter"] = na_filter

        with pd.ExcelFile("test5" + read_ext) as excel:
            parsed = pd.read_excel(
                excel,
                sheet_name="Sheet1",
                keep_default_na=True,
                na_values=["apple"],
                **kwargs,
            )

        if na_filter is False:
            expected = [["1.#QNAN"], [1], ["nan"], ["apple"], ["rabbit"]]
        else:
            expected = [[np.nan], [1], [np.nan], [np.nan], ["rabbit"]]

        expected = DataFrame(expected, columns=["Test"])
        tm.assert_frame_equal(parsed, expected)

    def test_excel_table_sheet_by_index(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        with pd.ExcelFile("test1" + read_ext) as excel:
            df1 = pd.read_excel(excel, sheet_name=0, index_col=0)
            df2 = pd.read_excel(excel, sheet_name=1, skiprows=[1], index_col=0)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        with pd.ExcelFile("test1" + read_ext) as excel:
            df1 = excel.parse(0, index_col=0)
            df2 = excel.parse(1, skiprows=[1], index_col=0)
        tm.assert_frame_equal(df1, df_ref, check_names=False)
        tm.assert_frame_equal(df2, df_ref, check_names=False)

        with pd.ExcelFile("test1" + read_ext) as excel:
            df3 = pd.read_excel(excel, sheet_name=0, index_col=0, skipfooter=1)
        tm.assert_frame_equal(df3, df1.iloc[:-1])

        with pd.ExcelFile("test1" + read_ext) as excel:
            df3 = excel.parse(0, index_col=0, skipfooter=1)

        tm.assert_frame_equal(df3, df1.iloc[:-1])

    def test_sheet_name(self, request, read_ext, df_ref):
        if read_ext == ".xlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        filename = "test1"
        sheet_name = "Sheet1"

        with pd.ExcelFile(filename + read_ext) as excel:
            df1_parse = excel.parse(sheet_name=sheet_name, index_col=0)  # doc

        with pd.ExcelFile(filename + read_ext) as excel:
            df2_parse = excel.parse(index_col=0, sheet_name=sheet_name)

        tm.assert_frame_equal(df1_parse, df_ref, check_names=False)
        tm.assert_frame_equal(df2_parse, df_ref, check_names=False)

    @pytest.mark.parametrize(
        "sheet_name",
        [3, [0, 3], [3, 0], "Sheet4", ["Sheet1", "Sheet4"], ["Sheet4", "Sheet1"]],
    )
    def test_bad_sheetname_raises(self, read_ext, sheet_name):
        # GH 39250
        msg = "Worksheet index 3 is invalid|Worksheet named 'Sheet4' not found"
        with pytest.raises(ValueError, match=msg):
            with pd.ExcelFile("blank" + read_ext) as excel:
                excel.parse(sheet_name=sheet_name)

    def test_excel_read_buffer(self, engine, read_ext):
        pth = "test1" + read_ext
        expected = pd.read_excel(pth, sheet_name="Sheet1", index_col=0, engine=engine)

        with open(pth, "rb") as f:
            with pd.ExcelFile(f) as xls:
                actual = pd.read_excel(xls, sheet_name="Sheet1", index_col=0)

        tm.assert_frame_equal(expected, actual)

    def test_reader_closes_file(self, engine, read_ext):
        with open("test1" + read_ext, "rb") as f:
            with pd.ExcelFile(f) as xlsx:
                # parses okay
                pd.read_excel(xlsx, sheet_name="Sheet1", index_col=0, engine=engine)

        assert f.closed

    def test_conflicting_excel_engines(self, read_ext):
        # GH 26566
        msg = "Engine should not be specified when passing an ExcelFile"

        with pd.ExcelFile("test1" + read_ext) as xl:
            with pytest.raises(ValueError, match=msg):
                pd.read_excel(xl, engine="foo")

    def test_excel_read_binary(self, engine, read_ext):
        # GH 15914
        expected = pd.read_excel("test1" + read_ext, engine=engine)

        with open("test1" + read_ext, "rb") as f:
            data = f.read()

        actual = pd.read_excel(data, engine=engine)
        tm.assert_frame_equal(expected, actual)

    def test_excel_read_binary_via_read_excel(self, read_ext, engine):
        # GH 38424
        with open("test1" + read_ext, "rb") as f:
            result = pd.read_excel(f)
        expected = pd.read_excel("test1" + read_ext, engine=engine)
        tm.assert_frame_equal(result, expected)

    def test_read_excel_header_index_out_of_range(self, engine):
        # GH#43143
        with open("df_header_oob.xlsx", "rb") as f:
            with pytest.raises(ValueError, match="exceeds maximum"):
                pd.read_excel(f, header=[0, 1])

    @pytest.mark.parametrize("filename", ["df_empty.xlsx", "df_equals.xlsx"])
    def test_header_with_index_col(self, filename):
        # GH 33476
        idx = Index(["Z"], name="I2")
        cols = MultiIndex.from_tuples([("A", "B"), ("A", "B.1")], names=["I11", "I12"])
        expected = DataFrame([[1, 3]], index=idx, columns=cols, dtype="int64")
        result = pd.read_excel(
            filename, sheet_name="Sheet1", index_col=0, header=[0, 1]
        )
        tm.assert_frame_equal(expected, result)

    def test_read_datetime_multiindex(self, request, engine, read_ext):
        # GH 34748
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="Sheets containing datetimes not supported by pyxlsb"
                )
            )

        f = "test_datetime_mi" + read_ext
        with pd.ExcelFile(f) as excel:
            actual = pd.read_excel(excel, header=[0, 1], index_col=0, engine=engine)
        expected_column_index = MultiIndex.from_tuples(
            [(pd.to_datetime("02/29/2020"), pd.to_datetime("03/01/2020"))],
            names=[
                pd.to_datetime("02/29/2020").to_pydatetime(),
                pd.to_datetime("03/01/2020").to_pydatetime(),
            ],
        )
        expected = DataFrame([], columns=expected_column_index)

        tm.assert_frame_equal(expected, actual)

    def test_engine_invalid_option(self, read_ext):
        # read_ext includes the '.' hence the weird formatting
        with pytest.raises(ValueError, match="Value must be one of *"):
            with pd.option_context(f"io.excel{read_ext}.reader", "abc"):
                pass

    def test_ignore_chartsheets(self, request, engine, read_ext):
        # GH 41448
        if engine == "odf":
            pytest.skip("chartsheets do not exist in the ODF format")
        if engine == "pyxlsb":
            request.node.add_marker(
                pytest.mark.xfail(
                    reason="pyxlsb can't distinguish chartsheets from worksheets"
                )
            )
        with pd.ExcelFile("chartsheet" + read_ext) as excel:
            assert excel.sheet_names == ["Sheet1"]

    def test_corrupt_files_closed(self, engine, read_ext):
        # GH41778
        errors = (BadZipFile,)
        if engine is None:
            pytest.skip(f"Invalid test for engine={engine}")
        elif engine == "xlrd":
            import xlrd

            errors = (BadZipFile, xlrd.biffh.XLRDError)

        with tm.ensure_clean(f"corrupt{read_ext}") as file:
            Path(file).write_text("corrupt")
            with tm.assert_produces_warning(False):
                try:
                    pd.ExcelFile(file, engine=engine)
                except errors:
                    pass