============================================ Serpyco: a serializer for python dataclasses

What is Serpyco ?

Serpyco is a serialization library for Python 3.6+ dataclasses <https://docs.python.org/3/library/dataclasses.html>_ that works just by defining your dataclasses:

.. code-block:: python

import dataclasses
import typing

import serpyco

@dataclasses.dataclass
class Example(object):
    name: str
    num: int
    tags: typing.List[str]


serializer = serpyco.Serializer(Example)

result = serializer.dump(Example(name="foo", num=2, tags=["hello", "world"]))
print(result)

{'name': 'foo', 'num': 2, 'tags': ['hello', 'world']}

Serpyco works by analysing the dataclass fields and can recognize many types : List, Set, Tuple, Optional, Union... You can also embed other dataclasses in a definition.

The main use-case for Serpyco is to serialize objects for an API, but it can be helpful whenever you need to transform objects to/from builtin Python types.

Features

• Serialization and unserialization of dataclasses
• Validation of input/output data
• Very fast
• Extensible through custom encoders

Installing

Serpyco is best installed via pip:

.. code-block:: shell

pip install serpyco

It has only 3 (4 with python 3.6 dataclasses backport) dependencies:

• rapid-json: used for data validation and fast JSON dump/load
• python-dateutil: used for serializing datetime objects
• typing_inspect: used to inspect types as needed to create serializers

Documentation

• Documentation <https://sgrignard.gitlab.io/serpyco/docs>_
• API Reference <https://sgrignard.gitlab.io/serpyco/docs/api.html>_

Contributing

Serpyco is written using Python <https://www.python.org>_ and Cython <https://www.cython.org>_ for parts needing speed.

• Issue tracker <https://gitlab.com/sgrignard/serpyco/issues>_
• Source code <https://gitlab.com/sgrignard/serpyco>_