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"Adds some YAML functionality to the excellent `pydantic` library."

Project description


PyPI version Unit Tests

This is a small helper library that adds some YAML capabilities to pydantic, namely dumping to yaml via the yaml_model.yaml() function, and parsing from strings/files using YamlModel.parse_raw() and YamlModel.parse_file(). It also adds an Enum subclass that gets dumped to YAML as a string, and fixes dumping of some typical types.

Basic Usage

Example usage is seen below.

from pydantic_yaml import YamlEnum, YamlModel

class MyEnum(str, YamlEnum):
    a = "a"
    b = "b"

class MyModel(YamlModel):
    x: int = 1
    e: MyEnum = MyEnum.a

m1 = MyModel(x=2, e="b")
yml = m1.yaml()
jsn = m1.json()

m2 = MyModel.parse_raw(yml)  # This automatically assumes YAML
assert m1 == m2

m3 = MyModel.parse_raw(jsn)  # This will fallback to JSON
assert m1 == m3

m4 = MyModel.parse_raw(yml, proto="yaml")
assert m1 == m4

m5 = MyModel.parse_raw(yml, content_type="application/yaml")
assert m1 == m5


pip install pydantic_yaml

Make sure to install ruamel.yaml (recommended) or pyyaml as well. These are optional dependencies:

pip install pydantic_yaml[ruamel]

pip install pydantic_yaml[pyyaml]

Versioned Models

Since YAML is often used for config files, there is also a VersionedYamlModel class.

The version attribute is parsed according to the SemVer (Semantic Versioning) specification.

Usage example:

from pydantic import ValidationError
from pydantic_yaml import VersionedYamlModel

class A(VersionedYamlModel):
    foo: str = "bar"

class B(VersionedYamlModel):
    foo: str = "bar"

    class Config:
        min_version = "2.0.0"

yml = """
version: 1.0.0
foo: baz


except ValidationError as e:
    print("Correctly got ValidationError:", e, sep="\n")

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