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

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)