72 lines
2.3 KiB
Python
72 lines
2.3 KiB
Python
from datetime import datetime
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import typing
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from typing import Dict, List, Type
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from dateutil import parser
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def from_json(cls, data):
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"""
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Converts data from a JSON parse into Python data structures.
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Arguments:
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cls: the template class to deserialize into
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data: the data to deserialize to the class
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"""
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# Approach for deserialization here:
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# https://stackoverflow.com/a/40639688/2319844
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# If it's a forward reference, evaluate it to figure out the actual
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# type. This allows for types that have to be put into a string.
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if isinstance(cls, typing.ForwardRef):
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cls = cls._evaluate(globals(), locals())
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annotations: Dict[str, Type] = getattr(cls, '__annotations__', {})
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# Handle primitive of objects
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if data is None:
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instance = None
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elif cls == str:
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instance = data
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elif cls == int:
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instance = int(data)
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elif cls == bool:
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instance = bool(data)
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elif cls == datetime:
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instance = parser.parse(data)
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# Handle generics. List[*], Dict[*, *] in particular.
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elif type(cls) == typing._GenericAlias:
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# Having to use this because things changed in Python 3.7.
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class_name = cls._name
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# TODO: this is not very elegant since it doesn't allow things which
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# sublass from List or Dict.
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if class_name == 'List':
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list_type = cls.__args__[0]
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instance: List[list_type] = list()
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for value in data:
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instance.append(from_json(list_type, value))
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elif class_name == 'Dict':
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key_type, val_type = cls.__args__
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instance: Dict[key_type, val_type] = dict()
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for key, value in data.items():
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key = from_json(key_type, key)
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value = from_json(val_type, value)
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instance[key] = value
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else:
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raise Exception(
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'Trying to deserialize an unsupported type: {cls._name}')
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# Handle everything else by first instantiating the class, then adding
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# all of the sub-elements, recursively calling from_json on them.
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else:
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instance: cls = cls()
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for field, field_type in annotations.items():
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value = data.get(field)
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setattr(instance, field, from_json(field_type, value))
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return instance
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