def to_csv(
    df,
    filename,
    single_file=False,
    encoding="utf-8",
    mode="wt",
    name_function=None,
    compression=None,
    compute=True,
    scheduler=None,
    storage_options=None,
    header_first_partition_only=None,
    compute_kwargs=None,
    **kwargs,
):
    """
    Store Dask DataFrame to CSV files

    One filename per partition will be created. You can specify the
    filenames in a variety of ways.

    Use a globstring::

    >>> df.to_csv('/path/to/data/export-*.csv')  # doctest: +SKIP

    The * will be replaced by the increasing sequence 0, 1, 2, ...

    ::

        /path/to/data/export-0.csv
        /path/to/data/export-1.csv

    Use a globstring and a ``name_function=`` keyword argument.  The
    name_function function should expect an integer and produce a string.
    Strings produced by name_function must preserve the order of their
    respective partition indices.

    >>> from datetime import date, timedelta
    >>> def name(i):
    ...     return str(date(2015, 1, 1) + i * timedelta(days=1))

    >>> name(0)
    '2015-01-01'
    >>> name(15)
    '2015-01-16'

    >>> df.to_csv('/path/to/data/export-*.csv', name_function=name)  # doctest: +SKIP

    ::

        /path/to/data/export-2015-01-01.csv
        /path/to/data/export-2015-01-02.csv
        ...

    You can also provide an explicit list of paths::

    >>> paths = ['/path/to/data/alice.csv', '/path/to/data/bob.csv', ...]  # doctest: +SKIP
    >>> df.to_csv(paths) # doctest: +SKIP

    You can also provide a directory name:

    >>> df.to_csv('/path/to/data') # doctest: +SKIP

    The files will be numbered 0, 1, 2, (and so on) suffixed with '.part':

    ::

        /path/to/data/0.part
        /path/to/data/1.part

    Parameters
    ----------
    df : dask.DataFrame
        Data to save
    filename : string or list
        Absolute or relative filepath(s). Prefix with a protocol like ``s3://``
        to save to remote filesystems.
    single_file : bool, default False
        Whether to save everything into a single CSV file. Under the
        single file mode, each partition is appended at the end of the
        specified CSV file.
    encoding : string, default 'utf-8'
        A string representing the encoding to use in the output file.
    mode : str, default 'w'
        Python file mode. The default is 'w' (or 'wt'), for writing
        a new file or overwriting an existing file in text mode. 'a'
        (or 'at') will append to an existing file in text mode or
        create a new file if it does not already exist. See :py:func:`open`.
    name_function : callable, default None
        Function accepting an integer (partition index) and producing a
        string to replace the asterisk in the given filename globstring.
        Should preserve the lexicographic order of partitions. Not
        supported when ``single_file`` is True.
    compression : string, optional
        A string representing the compression to use in the output file,
        allowed values are 'gzip', 'bz2', 'xz',
        only used when the first argument is a filename.
    compute : bool, default True
        If True, immediately executes. If False, returns a set of delayed
        objects, which can be computed at a later time.
    storage_options : dict
        Parameters passed on to the backend filesystem class.
    header_first_partition_only : bool, default None
        If set to True, only write the header row in the first output
        file. By default, headers are written to all partitions under
        the multiple file mode (``single_file`` is False) and written
        only once under the single file mode (``single_file`` is True).
        It must be True under the single file mode.
    compute_kwargs : dict, optional
        Options to be passed in to the compute method
    kwargs : dict, optional
        Additional parameters to pass to :meth:`pandas.DataFrame.to_csv`.

    Returns
    -------
    The names of the file written if they were computed right away.
    If not, the delayed tasks associated with writing the files.

    Raises
    ------
    ValueError
        If ``header_first_partition_only`` is set to False or
        ``name_function`` is specified when ``single_file`` is True.

    See Also
    --------
    fsspec.open_files
    """
    from dask.dataframe.io.csv import to_csv as _to_csv

    return _to_csv(
        df.optimize(),
        filename,
        single_file=single_file,
        encoding=encoding,
        mode=mode,
        name_function=name_function,
        compression=compression,
        compute=compute,
        scheduler=scheduler,
        storage_options=storage_options,
        header_first_partition_only=header_first_partition_only,
        compute_kwargs=compute_kwargs,
        **kwargs,
    )