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
}
)
dataclasses_serialization.serializer_base
A collection of utilities to make it easier to create serializers.
isinstance(o, t)
, issubclass(cls, clsinfo)
Extended versions of the builtin isinstance
and issubclass
, to treat dataclass
as a superclass for dataclasses, and to be usable with supported typing
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 dictionary dct
to a dataclass cls
, using deserialization_func
to deserialize the fields of cls
.
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 a DeserializationError
.
As Optional
s are implemented as Union
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
and deserialize
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 are dict
s.
Similarly, dataclass
es are deserialized using dict_to_dataclass
, and Union
s using union_deserialization
, using itself as the nested deserialization function.
Serialize a Python object with serializer.serialize(obj)
, and deserialize with serializer.deserialize(cls, serialized_obj)
.
Register more serialization/deserialization functions with serializer.register_serializer(cls, func)
, serializer.register_deserializer(cls, func)
, and serializer.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.
dataclasses_serialization.json
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
and from_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
and from_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)
dataclasses_serialization.bson
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
and from_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
and from_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