Adds some YAML functionality to the excellent `pydantic` library.
Pydantic-YAML adds YAML capabilities to Pydantic, which is an excellent Python library for data validation and settings management. If you aren't familiar with Pydantic, I would suggest you first check out their docs.
from enum import Enum from pydantic import BaseModel, validator from pydantic_yaml import parse_yaml_raw_as, to_yaml_str class MyEnum(str, Enum): """A custom enumeration that is YAML-safe.""" a = "a" b = "b" class InnerModel(BaseModel): """A normal pydantic model that can be used as an inner class.""" fld: float = 1.0 class MyModel(BaseModel): """Our custom Pydantic model.""" x: int = 1 e: MyEnum = MyEnum.a m: InnerModel = InnerModel() @validator("x") def _chk_x(cls, v: int) -> int: # noqa """You can add your normal pydantic validators, like this one.""" assert v > 0 return v m1 = MyModel(x=2, e="b", m=InnerModel(fld=1.5)) # This dumps to YAML and JSON respectively yml = to_yaml_str(m1) jsn = m1.json() # This parses YAML as the MyModel type m2 = parse_yaml_raw_as(MyModel, yml) assert m1 == m2 # JSON is also valid YAML, so this works too m3 = parse_yaml_raw_as(MyModel, jsn) assert m1 == m3
With Pydantic v2, you can also dump dataclasses:
from pydantic import RootModel from pydantic.dataclasses import dataclass from pydantic.version import VERSION as PYDANTIC_VERSION from pydantic_yaml import to_yaml_str assert PYDANTIC_VERSION >= "2" @dataclass class YourType: foo: str = "bar" obj = YourType(foo="wuz") assert to_yaml_str(RootModel[YourType](obj)) == 'foo: wuz\n'
Currently we use the JSON dumping of Pydantic to perform most of the magic.
This uses the
Config inner class,
as in Pydantic:
class MyModel(BaseModel): # ... class Config: # You can override these fields, which affect JSON and YAML: json_dumps = my_custom_dumper json_loads = lambda x: MyModel() # As well as other Pydantic configuration: allow_mutation = False
You can control some YAML-specfic options via the keyword options:
to_yaml_str(model, indent=4) # Makes it wider to_yaml_str(model, map_indent=9, sequence_indent=7) # ... you monster.
You can additionally pass your own
from ruamel.yaml import YAML my_writer = YAML(typ="safe") my_writer.default_flow_style = True to_yaml_file("foo.yaml", model, custom_yaml_writer=my_writer)
A separate configuration for YAML specifically will be added later, likely in v2.
Breaking Changes for
The API for
pydantic-yaml version 1.0.0 has been greatly simplified!
This functionality has currently been removed!
YamlModelMixin base classes are no longer needed.
The plan is to re-add it before v1 fully releases,
to allow the
However, this will be availble only for
This functionality has been removed, as it's questionably useful for most users. There is an example in the docs that's available.
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