dataclasses_serialization
provides serializers/deserializers for transforming between Python dataclasses, and JSON and BSON objects.
Suppose we have the following dataclass:
from dataclasses import dataclass
@dataclass
class InventoryItem:
name: str
unit_price: float
quantity_on_hand: int
Then we may serialize/deserialize it to/from JSON by using JSONSerializer
>>> from dataclasses_serialization.json import JSONSerializer
>>> JSONSerializer.serialize(InventoryItem("Apple", 0.2, 20))
{'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}
>>> JSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20})
InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
As Mongo collections store objects as BSON, you can use BSONSerializer
to dump dataclasses directly into Mongo.
from dataclasses_serialization.bson import BSONSerializer
collection.insert_one(BSONSerializer.serialize(item))
item = BSONSerializer.deserialize(InventoryItem, collection.find_one())
To create a custom serializer, create an instance of dataclasses_serialization.serializer_base.Serializer
:
from dataclasses_serialization.serializer_base import noop_serialization, noop_deserialization, dict_serialization, dict_deserialization, list_deserialization, Serializer
JSONSerializer = Serializer(
serialization_functions={
dict: lambda dct: dict_serialization(dct, key_serialization_func=JSONSerializer.serialize, value_serialization_func=JSONSerializer.serialize),
list: lambda lst: list(map(JSONSerializer.serialize, lst)),
(str, int, float, bool, type(None)): noop_serialization
},
deserialization_functions={
dict: lambda cls, dct: dict_deserialization(cls, dct, key_deserialization_func=JSONSerializer.deserialize, value_deserialization_func=JSONSerializer.deserialize),
list: lambda cls, lst: list_deserialization(cls, lst, deserialization_func=JSONSerializer.deserialize),
(str, int, float, bool, type(None)): noop_deserialization
}
)
A collection of utilities to make it easier to create serializers.
-
isinstance(o, t)
,issubclass(cls, clsinfo)
Extended versions of the builtin
isinstance
andissubclass
, to treatdataclass
as a superclass for dataclasses, and to be usable with supportedtyping
types. -
noop_serialization(obj)
,noop_deserialization(cls, obj)
The trivial serialization/deserialization functions, which serialize by doing nothing.
-
dict_to_dataclass(cls, dct, deserialization_func=noop_deserialization)
The inverse of
dataclasses.asdict
, which deserializes a dictionarydct
to a dataclasscls
, usingdeserialization_func
to deserialize the fields ofcls
.Fields are deserialized using the type provided by the dataclass. So bound generic dataclasses may be deserialized, while unbound ones may not.
-
union_deserialization(type_, obj, deserialization_func=noop_deserialization)
Deserialize a
Union
type_
, by trying each type in turn, and returning the first that does not raise aDeserializationError
.As
Optional
s are implemented asUnion
s, this function also works for them. -
dict_serialization(obj, key_serialization_func=noop_serialization, value_serialization_func=noop_serialization)
,dict_deserialization(type_, obj, key_deserialization_func=noop_deserialization, value_deserialization_func=noop_deserialization)
Serialize/deserialize a dictionary
obj
by applying the appropriate serialization/deserialization functions to keys and values. -
list_deserialization(type_, obj, deserialization_func=noop_deserialization)
Deserialize a list
obj
by applying the deserialization function to its values. -
Serializer(serialization_functions, deserialization_functions)
The general serialization class.
Takes two dictionaries of serialization and deserialization functions, and defers to them appropriately when serializing/deserializing and object by the
serialize
anddeserialize
methods. Serializer functions take a single parameter, the object to be serialized, and returns a serialized version of it. Deserializer functions take two parameters, the desired type of the deserialized object, and the object to be deserialized.If an object's type cannot be found directly in the serialization/deserialization functions, the
Serializer
uses its closest ancestor - raising an error in case of ambiguity.By default
dataclass
es are serialized as though they aredict
s. Similarly,dataclass
es are deserialized usingdict_to_dataclass
, andUnion
s usingunion_deserialization
, using itself as the nested deserialization function.Serialize a Python object with
serializer.serialize(obj)
, and deserialize withserializer.deserialize(cls, serialized_obj)
.Register more serialization/deserialization functions with
serializer.register_serializer(cls, func)
,serializer.register_deserializer(cls, func)
, andserializer.register(cls, serialization_func, deserialization_func)
. They can also be used as decorators like so:@serializer.register_serializer(int) def int_serializer(obj): ...
@serializer.register_deserializer(int) def int_deserializer(cls, obj): ...
-
SerializationError
,DeserializationError
Errors to be raised when serialization/deserialization fails, respectively.
-
JSONSerializer
Serializer/deserializer between Python dataclasses and JSON objects.
>>> JSONSerializer.serialize(InventoryItem("Apple", 0.2, 20)) {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20} >>> JSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}) InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
JSONSerializerMixin
Adds
as_json
andfrom_json
methods to dataclasses when used as a mixin.@dataclass class InventoryItem(JSONSerializerMixin): ...
>>> InventoryItem("Apple", 0.2, 20).as_json() {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20} >>> InventoryItem.from_json({'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}) InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
JSONStrSerializer
Serializer/deserializer between Python dataclasses and JSON strings.
>>> JSONStrSerializer.serialize(InventoryItem("Apple", 0.2, 20)) '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}' >>> JSONStrSerializer.deserialize(InventoryItem, '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}') InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
JSONStrSerializerMixin
Adds
as_json_str
andfrom_json_str
methods to dataclasses when used as a mixin.@dataclass class InventoryItem(JSONStrSerializerMixin): ...
>>> InventoryItem("Apple", 0.2, 20).as_json_str() '{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}' >>> InventoryItem.from_json_str('{"name": "Apple", "unit_price": 0.2, "quantity_on_hand": 20}') InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
BSONSerializer
Serializer/deserializer between Python dataclasses and BSON objects.
>>> BSONSerializer.serialize(InventoryItem("Apple", 0.2, 20)) {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20} >>> BSONSerializer.deserialize(InventoryItem, {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}) InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
BSONSerializerMixin
Adds
as_bson
andfrom_bson
methods to dataclasses when used as a mixin.@dataclass class InventoryItem(BSONSerializerMixin): ...
>>> InventoryItem("Apple", 0.2, 20).as_bson() {'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20} >>> InventoryItem.from_bson({'name': 'Apple', 'unit_price': 0.2, 'quantity_on_hand': 20}) InventoryItem(name='Apple', unit_price=0.2, quantity_on_hand=20)
-
BSONStrSerializer
Serializer/deserializer between Python dataclasses and binary BSON strings.
-
BSONStrSerializerMixin
Adds
as_bson_str
andfrom_bson_str
methods to dataclasses when used as a mixin.@dataclass class InventoryItem(BSONStrSerializerMixin): ...
Install and update using the standard Python package manager pip:
pip install dataclasses_serialization