pydantic-core

This package provides the core functionality for pydantic validation and serialization.

Pydantic-core is currently around 17x faster than pydantic V1. See tests/benchmarks/ for details.

Example of direct usage

NOTE: You should not need to use pydantic-core directly; instead, use pydantic, which in turn uses pydantic-core.

from pydantic_core import SchemaValidator, ValidationError


v = SchemaValidator(
    {
        'type': 'typed-dict',
        'fields': {
            'name': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'str',
                },
            },
            'age': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'int',
                    'ge': 18,
                },
            },
            'is_developer': {
                'type': 'typed-dict-field',
                'schema': {
                    'type': 'default',
                    'schema': {'type': 'bool'},
                    'default': True,
                },
            },
        },
    }
)

r1 = v.validate_python({'name': 'Samuel', 'age': 35})
assert r1 == {'name': 'Samuel', 'age': 35, 'is_developer': True}

# pydantic-core can also validate JSON directly
r2 = v.validate_json('{"name": "Samuel", "age": 35}')
assert r1 == r2

try:
    v.validate_python({'name': 'Samuel', 'age': 11})
except ValidationError as e:
    print(e)
    """
    1 validation error for model
    age
      Input should be greater than or equal to 18
      [type=greater_than_equal, context={ge: 18}, input_value=11, input_type=int]
    """

Getting Started

You'll need rust stable installed, or rust nightly if you want to generate accurate coverage.

With rust and python 3.7+ installed, compiling pydantic-core should be possible with roughly the following:

# clone this repo or your fork
git clone [email protected]:pydantic/pydantic-core.git
cd pydantic-core
# create a new virtual env
python3 -m venv env
source env/bin/activate
# install dependencies and install pydantic-core
make install

That should be it, the example shown above should now run.

You might find it useful to look at python/pydantic_core/_pydantic_core.pyi and python/pydantic_core/core_schema.py for more information on the python API, beyond that, tests/ provide a large number of examples of usage.

If you want to contribute to pydantic-core, you'll want to use some other make commands:

• make build-dev to build the package during development
• make build-prod to perform an optimised build for benchmarking
• make test to run the tests
• make testcov to run the tests and generate a coverage report
• make lint to run the linter
• make format to format python and rust code
• make to run format build-dev lint test