README.md

perde: python-wrapped serde

Heavily under construction towards 0.1.0 🎅

Python wrapper around the powerful Rust serialization framework.

• Serialization & deserialization of python data structures.
• Supports various types including dataclasses, generic types, enum and common built-in types.
• Supports various serialization formats. By design, perde can support as many format as serde can.
• Provides string case conversion of field names, skipping serialization/deserialization options, structure flattening.
• Precise type checking based on type hints.
• Very fast.

Install

pip install perde

Usage

>>> import perde

Assume you have a dataclass,

>>> @dataclass
... class A:
...     a: int
...     b: str

To serialize class A to JSON,

>>> perde.json.dumps(A(a=10, b='x'))
'{"a":10,"b":"x"}'

To deserialize JSON to class A,

>>> perde.json.loads_as(A, '{"a":10,"b":"x"}')
A(a=10, b='x')

To deserialize JSON to a dictionary,

>>> perde.json.loads('{"a":10,"b":"x"}')
{'a': 10, 'b': 'x'}

More formats are supported.

>>> perde.yaml.dumps(A(10, "x"))
'---\na: 10\nb: x'
>>> perde.yaml.loads_as(A, '---\na: 10\nb: x')
A(a=10, b='x')
>>> perde.msgpack.dumps(A(10, "x"))
b'\x82\xa1a\n\xa1b\xa1x'
>>> perde.msgpack.loads_as(A, b'\x82\xa1a\n\xa1b\xa1x')
A(a=10, b='x')

Supported formats

• JSON (perde.json)
• YAML (perde.yaml)
• MessagePack (perde.msgpack)
• TOML (perde.toml)
• CBOR
• Pickle
• RON
• BSON
• Avro
• JSON5
• Postcard
• URL
• Environment variables
• AWS Parameter Store
• S-expressions
• D-Bus
• FlexBuffer
• XML

Supported types

• dataclass
• Primitive types
  • int
  • str
  • float
  • bool
  • bytes
  • bytearray
• Generic types
  • dict /typing.Dict
  • list / typing.List
  • set / typing.Set
  • frozenset / typing.FrozenSet
  • tuple / typing.Tuple
  • typing.Optional
  • typing.Union
  • typing.Any
• Enum types
  • Enum
  • IntEnum
  • Flag
  • IntFlag
• More built-in types
  • datetime.datetime
  • datetime.date
  • datetime.time
  • decimal.Decimal
  • uuid.UUID

Attributes

Attributes allow to modify the way of serialization/deserialization.

For example, to serialize/deserialize the field names as camelCase,

>>> @perde.attr(rename_all="camelCase")
... @dataclass
... class A:
...     foo_bar: int
...     bar_bar: int

>>> perde.json.dumps(A(foo_bar=1, bar_bar=2))
'{"fooBar":1,"barBar":2}'
>>> perde.json.loads_as(A, '{"fooBar":1,"barBar":2}')
A(foo_bar=1, bar_bar=2)

See the book for more details.

Benchmark

The benchmark repeats (de)serializing the data structure A 10000 times:

class A:
    a: int
    b: str
    c: float
    d: bool

• pyserde
• mashumaro
• attrs
• cattrs