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Edit: METADATA
Metadata-Version: 2.3 Name: pydantic_core Version: 2.20.1 Classifier: Development Status :: 3 - Alpha Classifier: Programming Language :: Python Classifier: Programming Language :: Python :: 3 Classifier: Programming Language :: Python :: 3 :: Only Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Classifier: Programming Language :: Python :: 3.11 Classifier: Programming Language :: Python :: 3.12 Classifier: Programming Language :: Python :: 3.13 Classifier: Programming Language :: Rust Classifier: Framework :: Pydantic Classifier: Intended Audience :: Developers Classifier: Intended Audience :: Information Technology Classifier: License :: OSI Approved :: MIT License Classifier: Operating System :: POSIX :: Linux Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: MacOS Classifier: Typing :: Typed Requires-Dist: typing-extensions >=4.6.0, !=4.7.0 License-File: LICENSE Summary: Core functionality for Pydantic validation and serialization Home-Page: https://github.com/pydantic/pydantic-core Author-email: Samuel Colvin <s@muelcolvin.com> License: MIT Requires-Python: >=3.8 Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM Project-URL: Homepage, https://github.com/pydantic/pydantic-core Project-URL: Funding, https://github.com/sponsors/samuelcolvin Project-URL: Source, https://github.com/pydantic/pydantic-core # pydantic-core [](https://github.com/pydantic/pydantic-core/actions?query=event%3Apush+branch%3Amain+workflow%3Aci) [](https://codecov.io/gh/pydantic/pydantic-core) [](https://pypi.python.org/pypi/pydantic-core) [](https://github.com/pydantic/pydantic-core) [](https://github.com/pydantic/pydantic-core/blob/main/LICENSE) This package provides the core functionality for [pydantic](https://docs.pydantic.dev) validation and serialization. Pydantic-core is currently around 17x faster than pydantic V1. See [`tests/benchmarks/`](./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._ ```py 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](https://rustup.rs/), or rust nightly if you want to generate accurate coverage. With rust and python 3.8+ installed, compiling pydantic-core should be possible with roughly the following: ```bash # clone this repo or your fork git clone git@github.com: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`](./python/pydantic_core/_pydantic_core.pyi) and [`python/pydantic_core/core_schema.py`](./python/pydantic_core/core_schema.py) for more information on the python API, beyond that, [`tests/`](./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` ## Profiling 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`. Run `make build-profiling` to install a release build with debugging symbols included (needed for profiling). Once that is built, you can profile pytest benchmarks with (e.g.): ```bash flamegraph -- pytest tests/benchmarks/test_micro_benchmarks.py -k test_list_of_ints_core_py --benchmark-enable ``` The `flamegraph` command will produce an interactive SVG at `flamegraph.svg`. ## Releasing 1. Bump package version locally. Do not just edit `Cargo.toml` on Github, you need both `Cargo.toml` and `Cargo.lock` to be updated. 2. Make a PR for the version bump and merge it. 3. Go to https://github.com/pydantic/pydantic-core/releases and click "Draft a new release" 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. 5. Enter the release title in the form "v<the.new.version> <YYYY-MM-DD>" 6. Click Generate release notes button 7. Click Publish release 8. Go to https://github.com/pydantic/pydantic-core/actions and ensure that all build for release are done successfully. 9. Go to https://pypi.org/project/pydantic-core/ and ensure that the latest release is published. 10. Done 🎉
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