Interoperates @dataclass with json objects
Project description
jsondaora
Interoperates dataclasses and TypedDict annotations with json objects for python
Documentation: https://dutradda.github.io/jsondaora
Source Code: https://github.com/dutradda/jsondaora
Key Features
- Full compatibility with dataclasses module and TypedDict annotation
- Deserialize values from dict
- Deserialize values from bytes*
- Deserialization/serialization of chosen fields
- Deserialize the following standard types: Dict, List, Tuple, Set, Union and Any
- Dict serialization
- Direct json serialization with orjson (don't convert to dict recursively before serialization)
- Optional validation according with the json-schema specification*
* feature in development.
Requirements
- Python 3.8+
- orjson for json serialization
Installation
$ pip install jsondaora
Basic example
from typing import List, TypedDict
from jsondaora import (
as_typed_dict,
asdataclass,
dataclass_asjson,
jsondaora,
typed_dict_asjson,
)
@jsondaora
class Person:
name: str
age: int
class Music:
name: str
musics: List[Music]
jsondict = dict(name=b'John', age='40', musics=[dict(name='Imagine')])
person = asdataclass(jsondict, Person)
print('dataclass:')
print(person)
print(dataclass_asjson(person))
print()
# TypedDict
@jsondaora
class MusicT(TypedDict):
name: str
@jsondaora
class PersonT(TypedDict):
name: str
age: int
musics: List[MusicT]
jsondict = dict(name=b'John', age='40', musics=[dict(name='Imagine')])
person = as_typed_dict(jsondict, PersonT)
print('TypedDict:')
print(person)
print(typed_dict_asjson(person, Person))
dataclass:
Person(name='John', age=40, musics=[Person.Music(name='Imagine')])
b'{"name":"John","age":40,"musics":[{"name":"Imagine"}]}'
TypedDict:
{'name': 'John', 'age': 40, 'musics': [{'name': 'Imagine'}]}
b'{"name":"John","age":40,"musics":[{"name":"Imagine"}]}'
Example for choose fields to deserialize
from typing import List, TypedDict
from jsondaora import (
as_typed_dict,
asdataclass,
dataclass_asjson,
jsondaora,
typed_dict_asjson,
)
@jsondaora(deserialize_fields=('name'))
class Person:
name: str
age: int
class Music:
name: str
musics: List[Music]
jsondict = dict(name=b'John', age='40', musics=[dict(name='Imagine')])
person = asdataclass(jsondict, Person)
print('dataclass:')
print(person)
print(dataclass_asjson(person))
print()
# TypedDict
@jsondaora
class MusicT(TypedDict):
name: str
@jsondaora(deserialize_fields=('name',))
class PersonT(TypedDict):
name: str
age: int
musics: List[MusicT]
jsondict = dict(name=b'John', age='40', musics=[dict(name='Imagine')])
person = as_typed_dict(jsondict, PersonT)
print('TypedDict:')
print(person)
print(typed_dict_asjson(person, PersonT))
dataclass:
Person(name='John', age='40', musics=[{'name': 'Imagine'}])
b'{"name":"John","age":"40","musics":[{"name":"Imagine"}]}'
TypedDict:
{'name': 'John', 'musics': [{'name': 'Imagine'}], 'age': '40'}
b'{"name":"John","musics":[{"name":"Imagine"}],"age":"40"}'
Example for choose fields to serialize
from typing import List, TypedDict
from jsondaora import (
as_typed_dict,
asdataclass,
dataclass_asjson,
jsondaora,
typed_dict_asjson,
)
@jsondaora(serialize_fields=('name', 'age'))
class Person:
name: str
age: int
class Music:
name: str
musics: List[Music]
jsondict = dict(name='John', age=40, musics=[dict(name='Imagine')])
person = asdataclass(jsondict, Person)
print('dataclass:')
print(person)
print(dataclass_asjson(person))
print()
# TypedDict
@jsondaora
class Music(TypedDict):
name: str
@jsondaora(serialize_fields=('age',))
class PersonT(TypedDict):
name: str
age: int
musics: List[Music]
jsondict = dict(name=b'John', age='40', musics=[dict(name='Imagine')])
person = as_typed_dict(jsondict, PersonT)
print('TypedDict:')
print(person)
print(typed_dict_asjson(person, PersonT))
dataclass:
Person(name='John', age=40, musics=[Person.Music(name='Imagine')])
b'{"age":40,"name":"John"}'
TypedDict:
{'name': 'John', 'age': 40, 'musics': [{'name': 'Imagine'}]}
b'{"age":40}'
Wins Pydantic Benchmark
jsondaora
is up to 3.2 times faster than pydantic on it's benchmark
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