dataclasses-codec 0.1.0

Simple Python dataclass serialization package with no dependencies

StupidSimple Dataclasses Codec

This native Python package allows to easily convert dataclasses into and from a serialized form. By default supports json.

Installation

pip install dataclasses-codec

Usage

The package provides functions to easily convert dataclasses into and from a serialized form. It uses by default the json_codec instance the package provides.

from dataclasses import dataclass
from dataclasses_codec import encode, decode, to_json, from_json

@dataclass
class MyDataclass:
    first_name: str
    last_name: str

obj = MyDataclass("John", "Doe")

# Serializable Python dictionary
encoded = encode(obj)
print(encoded)
# Output: {'first_name': 'John', 'last_name': 'Doe'}

decoded = decode(MyDataclass, encoded)
print(decoded)
# Output: MyDataclass(first_name="John", last_name="Doe")

# Native JSON handling

raw_json = to_json(obj)
print(raw_json)
# Output: '{"first_name": "John", "last_name": "Doe"}'

restored = from_json(MyDataclass, raw_json)
print(restored)
# Output: MyDataclass(first_name="John", last_name="Doe")

JSON codec

The JSON codec is a first class citizen of the package. It allows to easily convert dataclasses into and from JSON strings.

Serialization can be customized by using the json_field value. It supports native conversion of date and datetime fields. Dataclasses can be nested to form complex objects.

json_field extends the native dataclass field decorator to support custom serialization and deserialization.

from dataclasses import dataclass
from dataclasses_codec import json_codec, JSONOptional, JSON_MISSING
from dataclasses_codec.codecs.json import json_field
import datetime as dt

# Still a dataclass, so we can use its features like slots, frozen, etc.
@dataclass(slots=True)
class MyMetadataDataclass:
    created_at: dt.datetime
    updated_at: dt.datetime = json_field(
        serializer=lambda d: d.isoformat(),
        deserializer=lambda s: dt.datetime.fromisoformat(s)
    )
    enabled: bool | JSONOptional = JSON_MISSING # Explicitly mark a field as optional
    description: str | None = None # None is intentionally serialized as null


@dataclass
class MyDataclass:
    first_name: str
    last_name: str
    age: int
    metadata: MyMetadataDataclass = json_field(
        json_name="meta"
    )

obj = MyDataclass("John", "Doe", 30, MyMetadataDataclass(dt.datetime.now(), dt.datetime.now()))

raw_json = json_codec.to_json(obj)
print(raw_json)
# Output: '{"first_name": "John", "last_name": "Doe", "age": 30, "meta": {"created_at": "2025-10-25T11:53:35.918899", "updated_at": "2025-10-25T11:53:35.918902", "description": null}}'

JSON Mixins

The package provides JSON mixins to add the serialization and deserialization capabilities to a dataclass.

By default, the JSON codec is used. See: dataclasses_codec.codecs.json for more details.

from dataclasses import dataclass
from dataclasses_codec import JSONSerializable, JSONDeserializable

@dataclass
class MyDataclass(JSONSerializable, JSONDeserializable):
    first_name: str
    last_name: str
    age: int

obj = MyDataclass("John", "Doe", 30)

encoded = obj.to_dict(to_camel_case=True)
print(encoded)
# Output: {'firstName': 'John', 'lastName': 'Doe', 'age': 30}

restored = MyDataclass.from_dict(encoded, to_snake_case=True)
print(restored)
# Output: MyDataclass(first_name="John", last_name="Doe", age=30)

Extensibility

The package allows to extend the functionality of the codecs by implementing the Codec interface.

Each implementation should use is_dataclass to check if the object is a dataclass.

from dataclasses import dataclass, is_dataclass
from dataclasses_codec import Codec, encode
from dataclasses_codec.errors import CodecError

class MyCodec(Codec):
    def encode(self, obj, **kwargs):
        if not is_dataclass(obj):
            raise CodecError(f"obj is not a dataclass, found: '{obj}'")
        return obj
    def decode(self, cls, data, **kwargs):
        # Implement the decoding logic here
        raise CodecError("Decoding is not implemented for this codec")

@dataclass
class MyDataclass:
    first_name: str
    last_name: str
    age: int

obj = MyDataclass("John", "Doe", 30)

encoded = encode(obj, codec=MyCodec())
print(encoded)
# Output: {'first_name': 'John', 'last_name': 'Doe', 'age': 30}

Development

Running the tests

python -m unittest