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Metadata-Version: 2.4
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Name: pydantic_core
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Version: 2.33.0
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Classifier: Development Status :: 3 - Alpha
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Classifier: Programming Language :: Python
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Classifier: Programming Language :: Python :: 3
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Classifier: Programming Language :: Python :: 3 :: Only
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: Programming Language :: Python :: 3.13
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Classifier: Programming Language :: Rust
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Classifier: Framework :: Pydantic
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Classifier: Intended Audience :: Developers
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Classifier: Intended Audience :: Information Technology
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: POSIX :: Linux
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Classifier: Operating System :: Microsoft :: Windows
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Classifier: Operating System :: MacOS
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Classifier: Typing :: Typed
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Requires-Dist: typing-extensions>=4.6.0,!=4.7.0
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License-File: LICENSE
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Summary: Core functionality for Pydantic validation and serialization
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Home-Page: https://github.com/pydantic/pydantic-core
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Author-email: Samuel Colvin <s@muelcolvin.com>, Adrian Garcia Badaracco <1755071+adriangb@users.noreply.github.com>, David Montague <david@pydantic.dev>, David Hewitt <mail@davidhewitt.dev>, Sydney Runkle <sydneymarierunkle@gmail.com>, Victorien Plot <contact@vctrn.dev>
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License: MIT
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Requires-Python: >=3.9
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Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
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Project-URL: Homepage, https://github.com/pydantic/pydantic-core
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Project-URL: Funding, https://github.com/sponsors/samuelcolvin
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Project-URL: Source, https://github.com/pydantic/pydantic-core
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# pydantic-core
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[](https://github.com/pydantic/pydantic-core/actions?query=event%3Apush+branch%3Amain+workflow%3Aci)
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[](https://codecov.io/gh/pydantic/pydantic-core)
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[](https://pypi.python.org/pypi/pydantic-core)
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[](https://github.com/pydantic/pydantic-core)
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[](https://github.com/pydantic/pydantic-core/blob/main/LICENSE)
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This package provides the core functionality for [pydantic](https://docs.pydantic.dev) validation and serialization.
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Pydantic-core is currently around 17x faster than pydantic V1.
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See [`tests/benchmarks/`](./tests/benchmarks/) for details.
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## Example of direct usage
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_NOTE: You should not need to use pydantic-core directly; instead, use pydantic, which in turn uses pydantic-core._
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```py
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from pydantic_core import SchemaValidator, ValidationError
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v = SchemaValidator(
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{
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'type': 'typed-dict',
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'fields': {
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'name': {
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'type': 'typed-dict-field',
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'schema': {
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'type': 'str',
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},
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},
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'age': {
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'type': 'typed-dict-field',
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'schema': {
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'type': 'int',
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'ge': 18,
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},
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},
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'is_developer': {
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'type': 'typed-dict-field',
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'schema': {
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'type': 'default',
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'schema': {'type': 'bool'},
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'default': True,
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},
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},
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},
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}
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)
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r1 = v.validate_python({'name': 'Samuel', 'age': 35})
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assert r1 == {'name': 'Samuel', 'age': 35, 'is_developer': True}
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# pydantic-core can also validate JSON directly
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r2 = v.validate_json('{"name": "Samuel", "age": 35}')
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assert r1 == r2
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try:
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v.validate_python({'name': 'Samuel', 'age': 11})
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except ValidationError as e:
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print(e)
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"""
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1 validation error for model
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age
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Input should be greater than or equal to 18
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[type=greater_than_equal, context={ge: 18}, input_value=11, input_type=int]
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"""
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```
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## Getting Started
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You'll need rust stable [installed](https://rustup.rs/), or rust nightly if you want to generate accurate coverage.
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With rust and python 3.9+ installed, compiling pydantic-core should be possible with roughly the following:
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```bash
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# clone this repo or your fork
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git clone git@github.com:pydantic/pydantic-core.git
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cd pydantic-core
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# create a new virtual env
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python3 -m venv env
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source env/bin/activate
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# install dependencies and install pydantic-core
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make install
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```
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That should be it, the example shown above should now run.
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You might find it useful to look at [`python/pydantic_core/_pydantic_core.pyi`](./python/pydantic_core/_pydantic_core.pyi) and
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[`python/pydantic_core/core_schema.py`](./python/pydantic_core/core_schema.py) for more information on the python API,
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beyond that, [`tests/`](./tests) provide a large number of examples of usage.
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If you want to contribute to pydantic-core, you'll want to use some other make commands:
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* `make build-dev` to build the package during development
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* `make build-prod` to perform an optimised build for benchmarking
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* `make test` to run the tests
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* `make testcov` to run the tests and generate a coverage report
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* `make lint` to run the linter
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* `make format` to format python and rust code
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* `make` to run `format build-dev lint test`
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## Profiling
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It's possible to profile the code using the [`flamegraph` utility from `flamegraph-rs`](https://github.com/flamegraph-rs/flamegraph). (Tested on Linux.) You can install this with `cargo install flamegraph`.
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Run `make build-profiling` to install a release build with debugging symbols included (needed for profiling).
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Once that is built, you can profile pytest benchmarks with (e.g.):
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```bash
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flamegraph -- pytest tests/benchmarks/test_micro_benchmarks.py -k test_list_of_ints_core_py --benchmark-enable
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```
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The `flamegraph` command will produce an interactive SVG at `flamegraph.svg`.
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## Releasing
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1. Bump package version locally. Do not just edit `Cargo.toml` on Github, you need both `Cargo.toml` and `Cargo.lock` to be updated.
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2. Make a PR for the version bump and merge it.
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3. Go to https://github.com/pydantic/pydantic-core/releases and click "Draft a new release"
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4. In the "Choose a tag" dropdown enter the new tag `v<the.new.version>` and select "Create new tag on publish" when the option appears.
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5. Enter the release title in the form "v<the.new.version> <YYYY-MM-DD>"
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6. Click Generate release notes button
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7. Click Publish release
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8. Go to https://github.com/pydantic/pydantic-core/actions and ensure that all build for release are done successfully.
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9. Go to https://pypi.org/project/pydantic-core/ and ensure that the latest release is published.
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10. Done 🎉
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root