def _gufunc_arg_shapes()

in hypothesis_gufunc/gufunc.py [0:0]

• 10 lines of code
• 9 McCabe index (conditional complexity)

def _gufunc_arg_shapes(parsed_sig, min_side, max_side):
    """Strategy to generate array shapes for arguments to a function consistent
    with its signature.

    Parameters
    ----------
    parsed_sig : list-like of tuples of str
        gufunc signature that has already been parsed, e.g., using
        `parse_gufunc_signature`.
    min_side : defaultdict of str to int
        Minimum size of any of the dimensions in `parsed_sig`.
    max_side : defaultdict of str to int
        Maximum size of any of the dimensions in `parsed_sig`.

    Returns
    -------
    shapes : list of tuples of int
        list of tuples where each tuple is the shape of an argument.

    """
    assert min_side.default_factory() <= max_side.default_factory()
    min_max_ok = all(min_side[kk] <= max_side[kk] for kk in set(min_side.keys()) | set(max_side.keys()))
    assert min_max_ok

    # Get all dimension names in signature, including numeric constants
    all_dimensions = set([k for arg in parsed_sig for k in arg])

    # Assume we have already checked for weird unicode characters that mess up
    # isdigit in validation of signature.
    dim_map_st = {
        k: (just(int(k)) if k.isdigit() else integers(min_value=min_side[k], max_value=max_side[k]))
        for k in all_dimensions
    }

    # Build strategy that draws ints for dimensions and subs them in
    return builds(_signature_map, map_dict=fixed_dictionaries(dim_map_st), parsed_sig=just(parsed_sig))