def _infer_type_dict()

in python-package/lets_plot/plot/series_meta.py [0:0]

• 43 lines of code
• 27 McCabe index (conditional complexity)

def _infer_type_dict(var_name: str, var_content) -> str:
    if isinstance(var_content, Iterable):
        if not any(True for _ in var_content):  # empty
            return TYPE_UNKNOWN
    else:
        return TYPE_UNKNOWN

    type_set = set(type(val) for val in var_content)
    if type(None) in type_set:
        type_set.remove(type(None))

    if len(type_set) == 0:
        return TYPE_UNKNOWN

    if len(type_set) > 1:
        if all(issubclass(type_obj, int) or issubclass(type_obj, float) for type_obj in type_set):
            return TYPE_FLOATING
        else:
            return 'unknown(mixed types)'

    lp_dtype = TYPE_UNKNOWN
    type_obj = list(type_set)[0]
    if type_obj == bool:
        lp_dtype = TYPE_BOOLEAN
    elif issubclass(type_obj, int):
        lp_dtype = TYPE_INTEGER
    elif issubclass(type_obj, float):
        lp_dtype = TYPE_FLOATING
    elif issubclass(type_obj, str):
        lp_dtype = TYPE_STRING

    elif issubclass(type_obj, datetime):
        lp_dtype = TYPE_DATE_TIME
    elif issubclass(type_obj, date) and not issubclass(type_obj, datetime):
        lp_dtype = TYPE_DATE
    elif issubclass(type_obj, time):
        lp_dtype = TYPE_TIME

    elif numpy and issubclass(type_obj, numpy.datetime64):
        lp_dtype = TYPE_DATE_TIME
    elif numpy and issubclass(type_obj, numpy.timedelta64):
        # ToDo: time delta?
        # lp_dtype = TYPE_DATE_TIME
        lp_dtype = 'unknown(python:' + str(type_obj) + ')'

    elif numpy and issubclass(type_obj, numpy.integer):
        lp_dtype = TYPE_INTEGER
    elif numpy and issubclass(type_obj, numpy.floating):
        lp_dtype = TYPE_FLOATING
    else:
        lp_dtype = 'unknown(python:' + str(type_obj) + ')'

    return lp_dtype