human
I wrote the below code

    from pwnlib.util import cyclic
    filler = kwargs.pop('filler', cyclic.de_bruijn())
    length = kwargs.pop('length', None)
    preprocessor = kwargs.pop('preprocessor', (lambda x: None))
    if (kwargs != {}):
        raise TypeError(('fit()    does    not    support    argument    %r' % kwargs.popitem()[0]))
    packer = make_packer()
    filler = iters.cycle(filler)
    out = ''
    if ((not length) and (not pieces)):
        return ''
    if (not pieces):
        return ''.join((filler.next() for f in range(length)))
    def fill(out, value):
        while (value not in out):
            out += filler.next()
        return (out, out.index(value))
    pieces_ = dict()
    for (k, v) in pieces.items():
        if isinstance(k, (int, long)):
            if (k >= 1633771873):
                (out, k) = fill(out, pack(k))
        elif isinstance(k, str):
            (out, k) = fill(out, k)
        else:
            raise TypeError(("fit():    offset    must    be    of    type    int    or    str,    but    got    '%s'" % type(k)))
        pieces_[k] = v
    pieces = pieces_
    for (k, v) in pieces.items():
        pieces[k] = _flat([v], preprocessor, packer)
    last = max(pieces)
    if (length and last and ((last + len(pieces[last])) > length)):
        raise ValueError(('fit():    Pieces    do    not    fit    within    `length`    (=    %d)    bytes' % length))
    out = list(out)
    l = 0
    for (k, v) in sorted(pieces.items()):
        if (k < l):
            raise ValueError(('fit():    data    at    offset    %d    overlaps    with    previous    data    which    ends    at    offset    %d' % (k, l)))
        while (len(out) < k):
            out.append(filler.next())
        v = _flat([v], preprocessor, packer)
        l = (k + len(v))
        for i in range(len(out), l):
            filler.next()
        out[k:l] = v
    if length:
        if (l > length):
            raise ValueError(('fit():    Pieces    does    not    fit    within    `length`    (=    %d)    bytes' % length))
       ...

What's a good function header?

=====
Here's a good function header?
assistant
#Here's a good function header.

@LocalContext
def fit(pieces=None, **kwargs):