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Fast serialization of dataclasses using Cython

Project description

What is Serpyco ?

Serpyco is a serialization library for Python 3.6+ dataclasses that works just by defining your dataclasses:

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:

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

Contributing

Serpyco is written using Python and Cython for parts needing speed.

Project details


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serpyco-1.3.9.tar.gz (39.9 kB view hashes)

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