"""
Tests the 'read_fwf' function in parsers.py. This
test suite is independent of the others because the
engine is set to 'python-fwf' internally.
"""

from datetime import datetime
from io import (
    BytesIO,
    StringIO,
)
from pathlib import Path

import numpy as np
import pytest

from pandas.errors import EmptyDataError

import pandas as pd
from pandas import (
    DataFrame,
    DatetimeIndex,
)
import pandas._testing as tm
from pandas.core.arrays import (
    ArrowStringArray,
    StringArray,
)

from pandas.io.common import urlopen
from pandas.io.parsers import (
    read_csv,
    read_fwf,
)


def test_basic():
    data = """\
A         B            C            D
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    result = read_fwf(StringIO(data))
    expected = DataFrame(
        [
            [201158, 360.242940, 149.910199, 11950.7],
            [201159, 444.953632, 166.985655, 11788.4],
            [201160, 364.136849, 183.628767, 11806.2],
            [201161, 413.836124, 184.375703, 11916.8],
            [201162, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D"],
    )
    tm.assert_frame_equal(result, expected)


def test_colspecs():
    data = """\
A   B     C            D            E
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    colspecs = [(0, 4), (4, 8), (8, 20), (21, 33), (34, 43)]
    result = read_fwf(StringIO(data), colspecs=colspecs)

    expected = DataFrame(
        [
            [2011, 58, 360.242940, 149.910199, 11950.7],
            [2011, 59, 444.953632, 166.985655, 11788.4],
            [2011, 60, 364.136849, 183.628767, 11806.2],
            [2011, 61, 413.836124, 184.375703, 11916.8],
            [2011, 62, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D", "E"],
    )
    tm.assert_frame_equal(result, expected)


def test_widths():
    data = """\
A    B    C            D            E
2011 58   360.242940   149.910199   11950.7
2011 59   444.953632   166.985655   11788.4
2011 60   364.136849   183.628767   11806.2
2011 61   413.836124   184.375703   11916.8
2011 62   502.953953   173.237159   12468.3
"""
    result = read_fwf(StringIO(data), widths=[5, 5, 13, 13, 7])

    expected = DataFrame(
        [
            [2011, 58, 360.242940, 149.910199, 11950.7],
            [2011, 59, 444.953632, 166.985655, 11788.4],
            [2011, 60, 364.136849, 183.628767, 11806.2],
            [2011, 61, 413.836124, 184.375703, 11916.8],
            [2011, 62, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D", "E"],
    )
    tm.assert_frame_equal(result, expected)


def test_non_space_filler():
    # From Thomas Kluyver:
    #
    # Apparently, some non-space filler characters can be seen, this is
    # supported by specifying the 'delimiter' character:
    #
    # http://publib.boulder.ibm.com/infocenter/dmndhelp/v6r1mx/index.jsp?topic=/com.ibm.wbit.612.help.config.doc/topics/rfixwidth.html
    data = """\
A~~~~B~~~~C~~~~~~~~~~~~D~~~~~~~~~~~~E
201158~~~~360.242940~~~149.910199~~~11950.7
201159~~~~444.953632~~~166.985655~~~11788.4
201160~~~~364.136849~~~183.628767~~~11806.2
201161~~~~413.836124~~~184.375703~~~11916.8
201162~~~~502.953953~~~173.237159~~~12468.3
"""
    colspecs = [(0, 4), (4, 8), (8, 20), (21, 33), (34, 43)]
    result = read_fwf(StringIO(data), colspecs=colspecs, delimiter="~")

    expected = DataFrame(
        [
            [2011, 58, 360.242940, 149.910199, 11950.7],
            [2011, 59, 444.953632, 166.985655, 11788.4],
            [2011, 60, 364.136849, 183.628767, 11806.2],
            [2011, 61, 413.836124, 184.375703, 11916.8],
            [2011, 62, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D", "E"],
    )
    tm.assert_frame_equal(result, expected)


def test_over_specified():
    data = """\
A   B     C            D            E
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    colspecs = [(0, 4), (4, 8), (8, 20), (21, 33), (34, 43)]

    with pytest.raises(ValueError, match="must specify only one of"):
        read_fwf(StringIO(data), colspecs=colspecs, widths=[6, 10, 10, 7])


def test_under_specified():
    data = """\
A   B     C            D            E
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    with pytest.raises(ValueError, match="Must specify either"):
        read_fwf(StringIO(data), colspecs=None, widths=None)


def test_read_csv_compat():
    csv_data = """\
A,B,C,D,E
2011,58,360.242940,149.910199,11950.7
2011,59,444.953632,166.985655,11788.4
2011,60,364.136849,183.628767,11806.2
2011,61,413.836124,184.375703,11916.8
2011,62,502.953953,173.237159,12468.3
"""
    expected = read_csv(StringIO(csv_data), engine="python")

    fwf_data = """\
A   B     C            D            E
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    colspecs = [(0, 4), (4, 8), (8, 20), (21, 33), (34, 43)]
    result = read_fwf(StringIO(fwf_data), colspecs=colspecs)
    tm.assert_frame_equal(result, expected)


def test_bytes_io_input():
    data = BytesIO("שלום\nשלום".encode())  # noqa: RUF001
    result = read_fwf(data, widths=[2, 2], encoding="utf8")
    expected = DataFrame([["של", "ום"]], columns=["של", "ום"])
    tm.assert_frame_equal(result, expected)


def test_fwf_colspecs_is_list_or_tuple():
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""

    msg = "column specifications must be a list or tuple.+"

    with pytest.raises(TypeError, match=msg):
        read_fwf(StringIO(data), colspecs={"a": 1}, delimiter=",")


def test_fwf_colspecs_is_list_or_tuple_of_two_element_tuples():
    data = """index,A,B,C,D
foo,2,3,4,5
bar,7,8,9,10
baz,12,13,14,15
qux,12,13,14,15
foo2,12,13,14,15
bar2,12,13,14,15
"""

    msg = "Each column specification must be.+"

    with pytest.raises(TypeError, match=msg):
        read_fwf(StringIO(data), colspecs=[("a", 1)])


@pytest.mark.parametrize(
    "colspecs,exp_data",
    [
        ([(0, 3), (3, None)], [[123, 456], [456, 789]]),
        ([(None, 3), (3, 6)], [[123, 456], [456, 789]]),
        ([(0, None), (3, None)], [[123456, 456], [456789, 789]]),
        ([(None, None), (3, 6)], [[123456, 456], [456789, 789]]),
    ],
)
def test_fwf_colspecs_none(colspecs, exp_data):
    # see gh-7079
    data = """\
123456
456789
"""
    expected = DataFrame(exp_data)

    result = read_fwf(StringIO(data), colspecs=colspecs, header=None)
    tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize(
    "infer_nrows,exp_data",
    [
        # infer_nrows --> colspec == [(2, 3), (5, 6)]
        (1, [[1, 2], [3, 8]]),
        # infer_nrows > number of rows
        (10, [[1, 2], [123, 98]]),
    ],
)
def test_fwf_colspecs_infer_nrows(infer_nrows, exp_data):
    # see gh-15138
    data = """\
  1  2
123 98
"""
    expected = DataFrame(exp_data)

    result = read_fwf(StringIO(data), infer_nrows=infer_nrows, header=None)
    tm.assert_frame_equal(result, expected)


def test_fwf_regression():
    # see gh-3594
    #
    # Turns out "T060" is parsable as a datetime slice!
    tz_list = [1, 10, 20, 30, 60, 80, 100]
    widths = [16] + [8] * len(tz_list)
    names = ["SST"] + [f"T{z:03d}" for z in tz_list[1:]]

    data = """  2009164202000   9.5403  9.4105  8.6571  7.8372  6.0612  5.8843  5.5192
2009164203000   9.5435  9.2010  8.6167  7.8176  6.0804  5.8728  5.4869
2009164204000   9.5873  9.1326  8.4694  7.5889  6.0422  5.8526  5.4657
2009164205000   9.5810  9.0896  8.4009  7.4652  6.0322  5.8189  5.4379
2009164210000   9.6034  9.0897  8.3822  7.4905  6.0908  5.7904  5.4039
"""

    with tm.assert_produces_warning(FutureWarning, match="use 'date_format' instead"):
        result = read_fwf(
            StringIO(data),
            index_col=0,
            header=None,
            names=names,
            widths=widths,
            parse_dates=True,
            date_parser=lambda s: datetime.strptime(s, "%Y%j%H%M%S"),
        )
    expected = DataFrame(
        [
            [9.5403, 9.4105, 8.6571, 7.8372, 6.0612, 5.8843, 5.5192],
            [9.5435, 9.2010, 8.6167, 7.8176, 6.0804, 5.8728, 5.4869],
            [9.5873, 9.1326, 8.4694, 7.5889, 6.0422, 5.8526, 5.4657],
            [9.5810, 9.0896, 8.4009, 7.4652, 6.0322, 5.8189, 5.4379],
            [9.6034, 9.0897, 8.3822, 7.4905, 6.0908, 5.7904, 5.4039],
        ],
        index=DatetimeIndex(
            [
                "2009-06-13 20:20:00",
                "2009-06-13 20:30:00",
                "2009-06-13 20:40:00",
                "2009-06-13 20:50:00",
                "2009-06-13 21:00:00",
            ]
        ),
        columns=["SST", "T010", "T020", "T030", "T060", "T080", "T100"],
    )
    tm.assert_frame_equal(result, expected)
    result = read_fwf(
        StringIO(data),
        index_col=0,
        header=None,
        names=names,
        widths=widths,
        parse_dates=True,
        date_format="%Y%j%H%M%S",
    )
    tm.assert_frame_equal(result, expected)


def test_fwf_for_uint8():
    data = """1421302965.213420    PRI=3 PGN=0xef00      DST=0x17 SRC=0x28    04 154 00 00 00 00 00 127
1421302964.226776    PRI=6 PGN=0xf002               SRC=0x47    243 00 00 255 247 00 00 71"""  # noqa: E501
    df = read_fwf(
        StringIO(data),
        colspecs=[(0, 17), (25, 26), (33, 37), (49, 51), (58, 62), (63, 1000)],
        names=["time", "pri", "pgn", "dst", "src", "data"],
        converters={
            "pgn": lambda x: int(x, 16),
            "src": lambda x: int(x, 16),
            "dst": lambda x: int(x, 16),
            "data": lambda x: len(x.split(" ")),
        },
    )

    expected = DataFrame(
        [
            [1421302965.213420, 3, 61184, 23, 40, 8],
            [1421302964.226776, 6, 61442, None, 71, 8],
        ],
        columns=["time", "pri", "pgn", "dst", "src", "data"],
    )
    expected["dst"] = expected["dst"].astype(object)
    tm.assert_frame_equal(df, expected)


@pytest.mark.parametrize("comment", ["#", "~", "!"])
def test_fwf_comment(comment):
    data = """\
  1   2.   4  #hello world
  5  NaN  10.0
"""
    data = data.replace("#", comment)

    colspecs = [(0, 3), (4, 9), (9, 25)]
    expected = DataFrame([[1, 2.0, 4], [5, np.nan, 10.0]])

    result = read_fwf(StringIO(data), colspecs=colspecs, header=None, comment=comment)
    tm.assert_almost_equal(result, expected)


def test_fwf_skip_blank_lines():
    data = """

A         B            C            D

201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4


201162    502.953953   173.237159   12468.3

"""
    result = read_fwf(StringIO(data), skip_blank_lines=True)
    expected = DataFrame(
        [
            [201158, 360.242940, 149.910199, 11950.7],
            [201159, 444.953632, 166.985655, 11788.4],
            [201162, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D"],
    )
    tm.assert_frame_equal(result, expected)

    data = """\
A         B            C            D
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4


201162    502.953953   173.237159   12468.3
"""
    result = read_fwf(StringIO(data), skip_blank_lines=False)
    expected = DataFrame(
        [
            [201158, 360.242940, 149.910199, 11950.7],
            [201159, 444.953632, 166.985655, 11788.4],
            [np.nan, np.nan, np.nan, np.nan],
            [np.nan, np.nan, np.nan, np.nan],
            [201162, 502.953953, 173.237159, 12468.3],
        ],
        columns=["A", "B", "C", "D"],
    )
    tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("thousands", [",", "#", "~"])
def test_fwf_thousands(thousands):
    data = """\
 1 2,334.0    5
10   13     10.
"""
    data = data.replace(",", thousands)

    colspecs = [(0, 3), (3, 11), (12, 16)]
    expected = DataFrame([[1, 2334.0, 5], [10, 13, 10.0]])

    result = read_fwf(
        StringIO(data), header=None, colspecs=colspecs, thousands=thousands
    )
    tm.assert_almost_equal(result, expected)


@pytest.mark.parametrize("header", [True, False])
def test_bool_header_arg(header):
    # see gh-6114
    data = """\
MyColumn
   a
   b
   a
   b"""

    msg = "Passing a bool to header is invalid"
    with pytest.raises(TypeError, match=msg):
        read_fwf(StringIO(data), header=header)


def test_full_file():
    # File with all values.
    test = """index                             A    B    C
2000-01-03T00:00:00  0.980268513777    3  foo
2000-01-04T00:00:00  1.04791624281    -4  bar
2000-01-05T00:00:00  0.498580885705   73  baz
2000-01-06T00:00:00  1.12020151869     1  foo
2000-01-07T00:00:00  0.487094399463    0  bar
2000-01-10T00:00:00  0.836648671666    2  baz
2000-01-11T00:00:00  0.157160753327   34  foo"""
    colspecs = ((0, 19), (21, 35), (38, 40), (42, 45))
    expected = read_fwf(StringIO(test), colspecs=colspecs)

    result = read_fwf(StringIO(test))
    tm.assert_frame_equal(result, expected)


def test_full_file_with_missing():
    # File with missing values.
    test = """index                             A    B    C
2000-01-03T00:00:00  0.980268513777    3  foo
2000-01-04T00:00:00  1.04791624281    -4  bar
                     0.498580885705   73  baz
2000-01-06T00:00:00  1.12020151869     1  foo
2000-01-07T00:00:00                    0  bar
2000-01-10T00:00:00  0.836648671666    2  baz
                                      34"""
    colspecs = ((0, 19), (21, 35), (38, 40), (42, 45))
    expected = read_fwf(StringIO(test), colspecs=colspecs)

    result = read_fwf(StringIO(test))
    tm.assert_frame_equal(result, expected)


def test_full_file_with_spaces():
    # File with spaces in columns.
    test = """
Account                 Name  Balance     CreditLimit   AccountCreated
101     Keanu Reeves          9315.45     10000.00           1/17/1998
312     Gerard Butler         90.00       1000.00             8/6/2003
868     Jennifer Love Hewitt  0           17000.00           5/25/1985
761     Jada Pinkett-Smith    49654.87    100000.00          12/5/2006
317     Bill Murray           789.65      5000.00             2/5/2007
""".strip(
        "\r\n"
    )
    colspecs = ((0, 7), (8, 28), (30, 38), (42, 53), (56, 70))
    expected = read_fwf(StringIO(test), colspecs=colspecs)

    result = read_fwf(StringIO(test))
    tm.assert_frame_equal(result, expected)


def test_full_file_with_spaces_and_missing():
    # File with spaces and missing values in columns.
    test = """
Account               Name    Balance     CreditLimit   AccountCreated
101                           10000.00                       1/17/1998
312     Gerard Butler         90.00       1000.00             8/6/2003
868                                                          5/25/1985
761     Jada Pinkett-Smith    49654.87    100000.00          12/5/2006
317     Bill Murray           789.65
""".strip(
        "\r\n"
    )
    colspecs = ((0, 7), (8, 28), (30, 38), (42, 53), (56, 70))
    expected = read_fwf(StringIO(test), colspecs=colspecs)

    result = read_fwf(StringIO(test))
    tm.assert_frame_equal(result, expected)


def test_messed_up_data():
    # Completely messed up file.
    test = """
   Account          Name             Balance     Credit Limit   Account Created
       101                           10000.00                       1/17/1998
       312     Gerard Butler         90.00       1000.00

       761     Jada Pinkett-Smith    49654.87    100000.00          12/5/2006
  317          Bill Murray           789.65
""".strip(
        "\r\n"
    )
    colspecs = ((2, 10), (15, 33), (37, 45), (49, 61), (64, 79))
    expected = read_fwf(StringIO(test), colspecs=colspecs)

    result = read_fwf(StringIO(test))
    tm.assert_frame_equal(result, expected)


def test_multiple_delimiters():
    test = r"""
col1~~~~~col2  col3++++++++++++++++++col4
~~22.....11.0+++foo~~~~~~~~~~Keanu Reeves
  33+++122.33\\\bar.........Gerard Butler
++44~~~~12.01   baz~~Jennifer Love Hewitt
~~55       11+++foo++++Jada Pinkett-Smith
..66++++++.03~~~bar           Bill Murray
""".strip(
        "\r\n"
    )
    delimiter = " +~.\\"
    colspecs = ((0, 4), (7, 13), (15, 19), (21, 41))
    expected = read_fwf(StringIO(test), colspecs=colspecs, delimiter=delimiter)

    result = read_fwf(StringIO(test), delimiter=delimiter)
    tm.assert_frame_equal(result, expected)


def test_variable_width_unicode():
    data = """
שלום שלום
ום   שלל
של   ום
""".strip(
        "\r\n"
    )
    encoding = "utf8"
    kwargs = {"header": None, "encoding": encoding}

    expected = read_fwf(
        BytesIO(data.encode(encoding)), colspecs=[(0, 4), (5, 9)], **kwargs
    )
    result = read_fwf(BytesIO(data.encode(encoding)), **kwargs)
    tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("dtype", [{}, {"a": "float64", "b": str, "c": "int32"}])
def test_dtype(dtype):
    data = """ a    b    c
1    2    3.2
3    4    5.2
"""
    colspecs = [(0, 5), (5, 10), (10, None)]
    result = read_fwf(StringIO(data), colspecs=colspecs, dtype=dtype)

    expected = DataFrame(
        {"a": [1, 3], "b": [2, 4], "c": [3.2, 5.2]}, columns=["a", "b", "c"]
    )

    for col, dt in dtype.items():
        expected[col] = expected[col].astype(dt)

    tm.assert_frame_equal(result, expected)


def test_skiprows_inference():
    # see gh-11256
    data = """
Text contained in the file header

DataCol1   DataCol2
     0.0        1.0
   101.6      956.1
""".strip()
    skiprows = 2

    depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
    with tm.assert_produces_warning(FutureWarning, match=depr_msg):
        expected = read_csv(StringIO(data), skiprows=skiprows, delim_whitespace=True)

    result = read_fwf(StringIO(data), skiprows=skiprows)
    tm.assert_frame_equal(result, expected)


def test_skiprows_by_index_inference():
    data = """
To be skipped
Not  To  Be  Skipped
Once more to be skipped
123  34   8      123
456  78   9      456
""".strip()
    skiprows = [0, 2]

    depr_msg = "The 'delim_whitespace' keyword in pd.read_csv is deprecated"
    with tm.assert_produces_warning(FutureWarning, match=depr_msg):
        expected = read_csv(StringIO(data), skiprows=skiprows, delim_whitespace=True)

    result = read_fwf(StringIO(data), skiprows=skiprows)
    tm.assert_frame_equal(result, expected)


def test_skiprows_inference_empty():
    data = """
AA   BBB  C
12   345  6
78   901  2
""".strip()

    msg = "No rows from which to infer column width"
    with pytest.raises(EmptyDataError, match=msg):
        read_fwf(StringIO(data), skiprows=3)


def test_whitespace_preservation():
    # see gh-16772
    header = None
    csv_data = """
 a ,bbb
 cc,dd """

    fwf_data = """
 a bbb
 ccdd """
    result = read_fwf(
        StringIO(fwf_data), widths=[3, 3], header=header, skiprows=[0], delimiter="\n\t"
    )
    expected = read_csv(StringIO(csv_data), header=header)
    tm.assert_frame_equal(result, expected)


def test_default_delimiter():
    header = None
    csv_data = """
a,bbb
cc,dd"""

    fwf_data = """
a \tbbb
cc\tdd """
    result = read_fwf(StringIO(fwf_data), widths=[3, 3], header=header, skiprows=[0])
    expected = read_csv(StringIO(csv_data), header=header)
    tm.assert_frame_equal(result, expected)


@pytest.mark.parametrize("infer", [True, False])
def test_fwf_compression(compression_only, infer, compression_to_extension):
    data = """1111111111
    2222222222
    3333333333""".strip()

    compression = compression_only
    extension = compression_to_extension[compression]

    kwargs = {"widths": [5, 5], "names": ["one", "two"]}
    expected = read_fwf(StringIO(data), **kwargs)

    data = bytes(data, encoding="utf-8")

    with tm.ensure_clean(filename="tmp." + extension) as path:
        tm.write_to_compressed(compression, path, data)

        if infer is not None:
            kwargs["compression"] = "infer" if infer else compression

        result = read_fwf(path, **kwargs)
        tm.assert_frame_equal(result, expected)


def test_binary_mode():
    """
    read_fwf supports opening files in binary mode.

    GH 18035.
    """
    data = """aaa aaa aaa
bba bab b a"""
    df_reference = DataFrame(
        [["bba", "bab", "b a"]], columns=["aaa", "aaa.1", "aaa.2"], index=[0]
    )
    with tm.ensure_clean() as path:
        Path(path).write_text(data, encoding="utf-8")
        with open(path, "rb") as file:
            df = read_fwf(file)
            file.seek(0)
            tm.assert_frame_equal(df, df_reference)


@pytest.mark.parametrize("memory_map", [True, False])
def test_encoding_mmap(memory_map):
    """
    encoding should be working, even when using a memory-mapped file.

    GH 23254.
    """
    encoding = "iso8859_1"
    with tm.ensure_clean() as path:
        Path(path).write_bytes(" 1 A Ä 2\n".encode(encoding))
        df = read_fwf(
            path,
            header=None,
            widths=[2, 2, 2, 2],
            encoding=encoding,
            memory_map=memory_map,
        )
    df_reference = DataFrame([[1, "A", "Ä", 2]])
    tm.assert_frame_equal(df, df_reference)


@pytest.mark.parametrize(
    "colspecs, names, widths, index_col",
    [
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("abcde"),
            None,
            None,
        ),
        (
            None,
            list("abcde"),
            [6] * 4,
            None,
        ),
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("abcde"),
            None,
            True,
        ),
        (
            None,
            list("abcde"),
            [6] * 4,
            False,
        ),
        (
            None,
            list("abcde"),
            [6] * 4,
            True,
        ),
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("abcde"),
            None,
            False,
        ),
    ],
)
def test_len_colspecs_len_names(colspecs, names, widths, index_col):
    # GH#40830
    data = """col1  col2  col3  col4
    bab   ba    2"""
    msg = "Length of colspecs must match length of names"
    with pytest.raises(ValueError, match=msg):
        read_fwf(
            StringIO(data),
            colspecs=colspecs,
            names=names,
            widths=widths,
            index_col=index_col,
        )


@pytest.mark.parametrize(
    "colspecs, names, widths, index_col, expected",
    [
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("abc"),
            None,
            0,
            DataFrame(
                index=["col1", "ba"],
                columns=["a", "b", "c"],
                data=[["col2", "col3", "col4"], ["b   ba", "2", np.nan]],
            ),
        ),
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("ab"),
            None,
            [0, 1],
            DataFrame(
                index=[["col1", "ba"], ["col2", "b   ba"]],
                columns=["a", "b"],
                data=[["col3", "col4"], ["2", np.nan]],
            ),
        ),
        (
            [(0, 6), (6, 12), (12, 18), (18, None)],
            list("a"),
            None,
            [0, 1, 2],
            DataFrame(
                index=[["col1", "ba"], ["col2", "b   ba"], ["col3", "2"]],
                columns=["a"],
                data=[["col4"], [np.nan]],
            ),
        ),
        (
            None,
            list("abc"),
            [6] * 4,
            0,
            DataFrame(
                index=["col1", "ba"],
                columns=["a", "b", "c"],
                data=[["col2", "col3", "col4"], ["b   ba", "2", np.nan]],
            ),
        ),
        (
            None,
            list("ab"),
            [6] * 4,
            [0, 1],
            DataFrame(
                index=[["col1", "ba"], ["col2", "b   ba"]],
                columns=["a", "b"],
                data=[["col3", "col4"], ["2", np.nan]],
            ),
        ),
        (
            None,
            list("a"),
            [6] * 4,
            [0, 1, 2],
            DataFrame(
                index=[["col1", "ba"], ["col2", "b   ba"], ["col3", "2"]],
                columns=["a"],
                data=[["col4"], [np.nan]],
            ),
        ),
    ],
)
def test_len_colspecs_len_names_with_index_col(
    colspecs, names, widths, index_col, expected
):
    # GH#40830
    data = """col1  col2  col3  col4
    bab   ba    2"""
    result = read_fwf(
        StringIO(data),
        colspecs=colspecs,
        names=names,
        widths=widths,
        index_col=index_col,
    )
    tm.assert_frame_equal(result, expected)


def test_colspecs_with_comment():
    # GH 14135
    result = read_fwf(
        StringIO("#\nA1K\n"), colspecs=[(1, 2), (2, 3)], comment="#", header=None
    )
    expected = DataFrame([[1, "K"]], columns=[0, 1])
    tm.assert_frame_equal(result, expected)


def test_skip_rows_and_n_rows():
    # GH#44021
    data = """a\tb
1\t a
2\t b
3\t c
4\t d
5\t e
6\t f
    """
    result = read_fwf(StringIO(data), nrows=4, skiprows=[2, 4])
    expected = DataFrame({"a": [1, 3, 5, 6], "b": ["a", "c", "e", "f"]})
    tm.assert_frame_equal(result, expected)


def test_skiprows_with_iterator():
    # GH#10261, GH#56323
    data = """0
1
2
3
4
5
6
7
8
9
    """
    df_iter = read_fwf(
        StringIO(data),
        colspecs=[(0, 2)],
        names=["a"],
        iterator=True,
        chunksize=2,
        skiprows=[0, 1, 2, 6, 9],
    )
    expected_frames = [
        DataFrame({"a": [3, 4]}),
        DataFrame({"a": [5, 7]}, index=[2, 3]),
        DataFrame({"a": [8]}, index=[4]),
    ]
    for i, result in enumerate(df_iter):
        tm.assert_frame_equal(result, expected_frames[i])


def test_names_and_infer_colspecs():
    # GH#45337
    data = """X   Y   Z
      959.0    345   22.2
    """
    result = read_fwf(StringIO(data), skiprows=1, usecols=[0, 2], names=["a", "b"])
    expected = DataFrame({"a": [959.0], "b": 22.2})
    tm.assert_frame_equal(result, expected)


def test_widths_and_usecols():
    # GH#46580
    data = """0  1    n -0.4100.1
0  2    p  0.2 90.1
0  3    n -0.3140.4"""
    result = read_fwf(
        StringIO(data),
        header=None,
        usecols=(0, 1, 3),
        widths=(3, 5, 1, 5, 5),
        index_col=False,
        names=("c0", "c1", "c3"),
    )
    expected = DataFrame(
        {
            "c0": 0,
            "c1": [1, 2, 3],
            "c3": [-0.4, 0.2, -0.3],
        }
    )
    tm.assert_frame_equal(result, expected)


def test_dtype_backend(string_storage, dtype_backend):
    # GH#50289
    if string_storage == "python":
        arr = StringArray(np.array(["a", "b"], dtype=np.object_))
        arr_na = StringArray(np.array([pd.NA, "a"], dtype=np.object_))
    elif dtype_backend == "pyarrow":
        pa = pytest.importorskip("pyarrow")
        from pandas.arrays import ArrowExtensionArray

        arr = ArrowExtensionArray(pa.array(["a", "b"]))
        arr_na = ArrowExtensionArray(pa.array([None, "a"]))
    else:
        pa = pytest.importorskip("pyarrow")
        arr = ArrowStringArray(pa.array(["a", "b"]))
        arr_na = ArrowStringArray(pa.array([None, "a"]))

    data = """a  b    c      d  e     f  g    h  i
1  2.5  True  a
3  4.5  False b  True  6  7.5  a"""
    with pd.option_context("mode.string_storage", string_storage):
        result = read_fwf(StringIO(data), dtype_backend=dtype_backend)

    expected = DataFrame(
        {
            "a": pd.Series([1, 3], dtype="Int64"),
            "b": pd.Series([2.5, 4.5], dtype="Float64"),
            "c": pd.Series([True, False], dtype="boolean"),
            "d": arr,
            "e": pd.Series([pd.NA, True], dtype="boolean"),
            "f": pd.Series([pd.NA, 6], dtype="Int64"),
            "g": pd.Series([pd.NA, 7.5], dtype="Float64"),
            "h": arr_na,
            "i": pd.Series([pd.NA, pd.NA], dtype="Int64"),
        }
    )
    if dtype_backend == "pyarrow":
        pa = pytest.importorskip("pyarrow")
        from pandas.arrays import ArrowExtensionArray

        expected = DataFrame(
            {
                col: ArrowExtensionArray(pa.array(expected[col], from_pandas=True))
                for col in expected.columns
            }
        )
        expected["i"] = ArrowExtensionArray(pa.array([None, None]))

    tm.assert_frame_equal(result, expected)


def test_invalid_dtype_backend():
    msg = (
        "dtype_backend numpy is invalid, only 'numpy_nullable' and "
        "'pyarrow' are allowed."
    )
    with pytest.raises(ValueError, match=msg):
        read_fwf("test", dtype_backend="numpy")


@pytest.mark.network
@pytest.mark.single_cpu
def test_url_urlopen(httpserver):
    data = """\
A         B            C            D
201158    360.242940   149.910199   11950.7
201159    444.953632   166.985655   11788.4
201160    364.136849   183.628767   11806.2
201161    413.836124   184.375703   11916.8
201162    502.953953   173.237159   12468.3
"""
    httpserver.serve_content(content=data)
    expected = pd.Index(list("ABCD"))
    with urlopen(httpserver.url) as f:
        result = read_fwf(f).columns

    tm.assert_index_equal(result, expected)