No project description provided
Project description
serpyco-rs: a serializer for python dataclasses
What is serpyco-rs ?
Serpyco is a serialization library for Python 3.9+ dataclasses that works just by defining your dataclasses:
import dataclasses
import serpyco_rs
@dataclasses.dataclass
class Example:
name: str
num: int
tags: list[str]
serializer = serpyco_rs.Serializer(Example)
result = serializer.dump(Example(name="foo", num=2, tags=["hello", "world"]))
print(result)
>> {'name': 'foo', 'num': 2, 'tags': ['hello', 'world']}
Inspired by serpyco.
serpyco-rs works by analysing the dataclass fields and can recognize many types : list
, tuple
, Optional
...
You can also embed other dataclasses in a definition.
The main use-case for serpyco-rs is to serialize objects for an API, but it can be helpful whenever you need to transform objects to/from builtin Python types.
Installation
Use pip to install:
$ pip install serpyco-rs
Features
- Serialization and deserialization of dataclasses
- Validation of input data
- Very fast
- Support recursive schemas
- Generate JSON Schema Specification (Draft 2020-12)
- Support custom encoders/decoders for fields
Supported field types
There is support for generic types from the standard typing module:
- Decimal
- UUID
- Time
- Date
- DateTime
- Enum
- List
- Dict
- Bytes (pass through)
- TypedDict
- Mapping
- Sequence
- Tuple (fixed size)
- Literal[str, ...]
- Tagged unions (restricted)
Benchmark
macOS Monterey / Apple M1 Pro / 16GB RAM / Python 3.11.0
dump
Library | Median latency (milliseconds) | Operations per second | Relative (latency) |
---|---|---|---|
serpyco_rs | 0.05 | 22188.2 | 1 |
serpyco | 0.05 | 20878.5 | 1.06 |
mashumaro | 0.06 | 15602.7 | 1.42 |
pydantic | 2.66 | 375.6 | 59 |
marshmallow | 1.05 | 951.7 | 23.33 |
load with validate
Library | Median latency (milliseconds) | Operations per second | Relative (latency) |
---|---|---|---|
serpyco_rs | 0.23 | 4400.1 | 1 |
serpyco | 0.28 | 3546.4 | 1.24 |
mashumaro | 0.23 | 4377.7 | 1.01 |
pydantic | 2.01 | 497.3 | 8.86 |
marshmallow | 4.55 | 219.9 | 20.03 |
load (only serpyco and serpyco_rs supported load without validate)
Library | Median latency (milliseconds) | Operations per second | Relative (latency) |
---|---|---|---|
serpyco_rs | 0.07 | 13882.9 | 1 |
serpyco | 0.08 | 12424.5 | 1.12 |
mashumaro | 0.23 | 4382.9 | 3.17 |
pydantic | 2.02 | 494.4 | 28.09 |
marshmallow | 4.59 | 217.5 | 63.8 |
Supported annotations
serpyco-rs
supports changing load/dump behavior with typing.Annotated
.
Currently available:
- Alias
- FiledFormat (CamelCase / NoFormat)
- NoneFormat (OmitNone / KeepNone)
- Discriminator
- Min / Max
- MinLength / MaxLength
- CustomEncoder
- NoneAsDefaultForOptional (ForceDefaultForOptional)
Alias
Alias
is needed to override the field name in the structure used for load
/ dump
.
from dataclasses import dataclass
from typing import Annotated
from serpyco_rs import Serializer
from serpyco_rs.metadata import Alias
@dataclass
class A:
foo: Annotated[int, Alias('bar')]
ser = Serializer(A)
print(ser.load({'bar': 1}))
>> A(foo=1)
print(ser.dump(A(foo=1)))
>> {'bar': 1}
FiledFormat
Used to have response bodies in camelCase while keeping your python code in snake_case.
from dataclasses import dataclass
from typing import Annotated
from serpyco_rs import Serializer
from serpyco_rs.metadata import CamelCase, NoFormat
@dataclass
class B:
buz_filed: str
@dataclass
class A:
foo_filed: int
bar_filed: Annotated[B, NoFormat]
ser = Serializer(Annotated[A, CamelCase]) # or ser = Serializer(A, camelcase_fields=True)
print(ser.dump(A(foo_filed=1, bar_filed=B(buz_filed='123'))))
>> {'fooFiled': 1, 'barFiled': {'buz_filed': '123'}}
print(ser.load({'fooFiled': 1, 'barFiled': {'buz_filed': '123'}}))
>> A(foo_filed=1, bar_filed=B(buz_filed='123'))
NoneFormat
Via OmitNone
we can drop None values for non required fields in the serialized dicts
from dataclasses import dataclass
from serpyco_rs import Serializer
@dataclass
class A:
required_val: bool | None
optional_val: bool | None = None
ser = Serializer(A, omit_none=True) # or Serializer(Annotated[A, OmitNone])
print(ser.dump(A(required_val=None, optional_val=None)))
>>> {'required_val': None}
Tagged unions
Supports tagged joins with discriminator field.
All classes in the union must be dataclasses or attrs with discriminator field Literal[str]
.
The discriminator field is always mandatory.
from typing import Annotated, Literal
from dataclasses import dataclass
from serpyco_rs import Serializer
from serpyco_rs.metadata import Discriminator
@dataclass
class Foo:
type: Literal['foo']
value: int
@dataclass(kw_only=True)
class Bar:
type: Literal['bar'] = 'bar'
value: str
ser = Serializer(list[Annotated[Foo | Bar, Discriminator('type')]])
print(ser.load([{'type': 'foo', 'value': 1}, {'type': 'bar', 'value': 'buz'}]))
>>> [Foo(type='foo', value=1), Bar(type='bar', value='buz')]
Min / Max
Supported for int
/ float
/ Decimal
types and only for validation on load.
from typing import Annotated
from serpyco_rs import Serializer
from serpyco_rs.metadata import Min, Max
ser = Serializer(Annotated[int, Min(1), Max(10)])
ser.load(123)
>> SchemaValidationError: [ErrorItem(message='123 is greater than the maximum of 10', instance_path='', schema_path='maximum')]
MinLength / MaxLength
MinLength
/ MaxLength
can be used to restrict the length of loaded strings.
from typing import Annotated
from serpyco_rs import Serializer
from serpyco_rs.metadata import MinLength
ser = Serializer(Annotated[str, MinLength(5)])
ser.load("1234")
>> SchemaValidationError: [ErrorItem(message='"1234" is shorter than 5 characters', instance_path='', schema_path='minLength')]
NoneAsDefaultForOptional
ForceDefaultForOptional
/ KeepDefaultForOptional
can be used to set None as default value for optional (nullable) fields.
from dataclasses import dataclass
from serpyco_rs import Serializer
@dataclass
class Foo:
val: int # not nullable + required
val1: int | None # nullable + required
val2: int | None = None # nullable + not required
ser_force_default = Serializer(Foo, force_default_for_optional=True) # or Serializer(Annotated[Foo, ForceDefaultForOptional])
ser = Serializer(Foo)
# all fields except val are optional and nullable
assert ser_force_default.load({'val': 1}) == Foo(val=1, val1=None, val2=None)
# val1 field is required and nullable and val1 should be present in the dict
ser.load({'val': 1})
>> SchemaValidationError: [ErrorItem(message='"val1" is a required property', instance_path='', schema_path='required')]
Custom encoders for fields
You can provide CustomEncoder with serialize
and deserialize
functions, or serialize_with
and deserialize_with
annotations.
from typing import Annotated
from dataclasses import dataclass
from serpyco_rs import Serializer
from serpyco_rs.metadata import CustomEncoder
@dataclass
class Foo:
val: Annotated[str, CustomEncoder[str, str](serialize=str.upper, deserialize=str.lower)]
ser = Serializer(Foo)
val = ser.dump(Foo(val='bar'))
>> {'val': 'BAR'}
assert ser.load(val) == Foo(val='bar')
Note: CustomEncoder
has no effect to validation and JSON Schema generation.
Bytes fields
serpyco-rs
can loads bytes fields as is (without base64 encoding and validation).
from dataclasses import dataclass
from serpyco_rs import Serializer
@dataclass
class Foo:
val: bytes
ser = Serializer(Foo, pass_through_bytes=True)
ser.load({'val': b'123'}) == Foo(val=b'123')
Load data from raw json
serpyco-rs
can load data from raw json string.
Load data from raw json string is faster than [or]json.loads
+ Serializer.load
about 20%+.
This is possible because serpyco-rs
uses serde_json
to load data from a raw json string and avoids unnecessary conversion of python objects to serde_json::Value for validation process.
from dataclasses import dataclass
from serpyco_rs import Serializer
@dataclass
class A:
foo: int
bar: str
ser = Serializer(A)
print(ser.load_json('{"foo": 1, "bar": "buz"}'))
>> A(foo=1, bar='buz')
Getting JSON Schema
serpyco-rs
can generate JSON Schema for your dataclasses (Draft 2020-12).
from dataclasses import dataclass
from serpyco_rs import Serializer
@dataclass
class A:
"""Description of A"""
foo: int
bar: str
ser = Serializer(A)
print(ser.get_json_schema())
>> {
'$schema': 'https://json-schema.org/draft/2020-12/schema',
'$ref': '#/components/schemas/A[no_format,keep_nones]',
'components': {
'schemas': {
'A[no_format,keep_nones]': {
'properties': {
'foo': {'type': 'integer'},
'bar': {'type': 'string'}
},
'required': ['foo', 'bar'],
'type': 'object',
'description': 'Description of A'
}
}
}
}
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distributions
Hashes for serpyco_rs-0.15.1-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f76867130b67e56f6d5981200c8e0f690f0def79a341626ef6b648146061f143 |
|
MD5 | 943a486e5a3e6a2aa0302cf0c68a54c4 |
|
BLAKE2b-256 | a92de1de38047b191ef3266c1c156db02edf51ef940ede911a6d09ae5a364ed0 |
Hashes for serpyco_rs-0.15.1-cp311-none-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | f0f945cebef85a83e52219d43f48e9a2451f5950c51c6d7aadc3a01b4c14d0f6 |
|
MD5 | 5000ee204fd5061058f3647d54398c12 |
|
BLAKE2b-256 | 734720b4ebc8d274bea6abccf5df776f8a799ce1cfc8e59b7b5579b03d1899af |
Hashes for serpyco_rs-0.15.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 1ca3d5a383669f141bd3f31717ee60ef49316042b3139a32be394acc4535fa5d |
|
MD5 | cbea74ee1043657014b54684c29cba53 |
|
BLAKE2b-256 | 9e19cc6bc31d48f8238ba250488ddd2993f50bdfd723b96929a7d5ff1d4a8536 |
Hashes for serpyco_rs-0.15.1-cp311-cp311-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bb6eea46e9f74e7a153b9df1e20c5c162c202b29cc4a4bb04294cad810e64781 |
|
MD5 | f35b7e1c8ed46ef7de1009381c9a2039 |
|
BLAKE2b-256 | ff17bc85783cc69f7cd0a4d2bbee915304558d19c6ca8137cb4da041f1a81345 |
Hashes for serpyco_rs-0.15.1-cp310-none-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 081912cfd62626fd12615079b378400ca2f22809bef19becf94698a344ed1eff |
|
MD5 | ce28f4b7caea48df6ee703d4fe8e07a3 |
|
BLAKE2b-256 | 5bd014b63b06b7e86e492311b62687b589e5c20fbd71a87e02fb41679d31f448 |
Hashes for serpyco_rs-0.15.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 3245ae764a8e22a86fada9bac9216aaf421deefb878e37e5aff4a3aa6f00824f |
|
MD5 | 855778b581d3cf395a39822392b3cb8a |
|
BLAKE2b-256 | 61da03780aa29e7cdbabf0474ab992adf12c49a7c62457256f96fc31b9279f04 |
Hashes for serpyco_rs-0.15.1-cp310-cp310-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 014d15f40adc1a598d178d94f7d6e7d91fe4448fe2a4c9d63657350ce41115b1 |
|
MD5 | 49614cc7d46ef23c619832aa00b43876 |
|
BLAKE2b-256 | 0877b693ef03334fc279ae5830d3d6351aa5551da779af65830927f13d77b4f9 |
Hashes for serpyco_rs-0.15.1-cp39-none-win_amd64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bee55ba2cf29bb1a4e57e6cdbf1e7111c17cd20d4931bad805543e3bed2df62d |
|
MD5 | 9ea6a2f11db09a9aaeee6d9e07e211e2 |
|
BLAKE2b-256 | 3b2d7ad4713016cf8a66910511726dd5646d0ade66c12243047865c016d8e766 |
Hashes for serpyco_rs-0.15.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | 0f9471a48a815ac1be0df5c43150cb3fb6b15299a1620247a8e999c48c6a4a19 |
|
MD5 | 18e1fdb38e40054d9ba5d9e4ec5ba38d |
|
BLAKE2b-256 | 4e31edf3b264352fba9738f967c4e6ef4de2495b9bf26e412df948081a701dd5 |
Hashes for serpyco_rs-0.15.1-cp39-cp39-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | bcd20d9f6c66beb6a408f5577bb4e0549b4f8f906dfa0b7f6c94175fa81f8b29 |
|
MD5 | 0af8113e8fffbb88ff4f0fa90986190f |
|
BLAKE2b-256 | cd53d61f0a45ad6bd76486b9d949412d6bf2c5d1a40651bf6b42db6c6fd13e33 |