Source code for zfit.util.container

#  Copyright (c) 2020 zfit

from typing import Callable, Any, Iterable, Union

import tensorflow as tf

[docs]class DotDict(dict): """dot.notation access to dictionary attributes""" __getattr__ = dict.get __setattr__ = dict.__setitem__ __delattr__ = dict.__delitem__
[docs]def convert_to_container(value: Any, container: Callable = list, non_containers=None, convert_none=False) -> Union[None, Iterable]: """Convert `value` into a `container` storing `value` if `value` is not yet a python container. Args: value (object): container (callable): Converts a tuple to a container. non_containers (Optional[List[Container]]): Types that do not count as a container. Has to be a list of types. As an example, if `non_containers` is [list, tuple] and the value is [5, 3] (-> a list with two entries),this won't be converted to the `container` but end up as (if the container is e.g. a tuple): ([5, 3],) (a tuple with one entry). Returns: """ from ..core.interfaces import ZfitData, ZfitLoss, ZfitModel, ZfitSpace, ZfitParameter # here due to dependency if non_containers is None: non_containers = [] if not isinstance(non_containers, list): raise TypeError("`non_containers` have to be a list or a tuple") if value is None and not convert_none: return value if not isinstance(value, container): try: non_containers.extend([str, tf.Tensor, ZfitData, ZfitLoss, ZfitModel, ZfitSpace, ZfitParameter]) if isinstance(value, tuple(non_containers)): raise TypeError value = container(value) except TypeError: value = container((value,)) return value
[docs]def is_container(obj): """Check if `object` is a list or a tuple. Args: obj (): Returns: bool: True if it is a *container*, otherwise False """ return isinstance(obj, (list, tuple))