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Metadata-Version: 2.4
Name: pydantic_core
Version: 2.46.4
Classifier: Development Status :: 3 - Alpha
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.9
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 :: Python :: 3.14
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Classifier: Programming Language :: Python :: Implementation :: GraalPy
Classifier: Programming Language :: Rust
Classifier: Framework :: Pydantic
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: Operating System :: POSIX :: Linux
Classifier: Operating System :: Microsoft :: Windows
Classifier: Operating System :: MacOS
Classifier: Typing :: Typed
Requires-Dist: typing-extensions>=4.14.1
License-File: LICENSE
Summary: Core functionality for Pydantic validation and serialization
Home-Page: https://github.com/pydantic/pydantic
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>
License-Expression: MIT
Requires-Python: >=3.9
Description-Content-Type: text/markdown; charset=UTF-8; variant=GFM
Project-URL: Funding, https://github.com/sponsors/samuelcolvin
Project-URL: Homepage, https://github.com/pydantic
Project-URL: Source, https://github.com/pydantic/pydantic/tree/main/pydantic-core
# pydantic-core
[![CI](https://github.com/pydantic/pydantic-core/workflows/ci/badge.svg?event=push)](https://github.com/pydantic/pydantic-core/actions?query=event%3Apush+branch%3Amain+workflow%3Aci)
[![Coverage](https://codecov.io/gh/pydantic/pydantic-core/branch/main/graph/badge.svg)](https://codecov.io/gh/pydantic/pydantic-core)
[![pypi](https://img.shields.io/pypi/v/pydantic-core.svg)](https://pypi.python.org/pypi/pydantic-core)
[![versions](https://img.shields.io/pypi/pyversions/pydantic-core.svg)](https://github.com/pydantic/pydantic-core)
[![license](https://img.shields.io/github/license/pydantic/pydantic-core.svg)](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
### Prerequisites
You'll need:
1. **[Rust](https://rustup.rs/)** - Rust stable (or nightly for coverage)
2. **[uv](https://docs.astral.sh/uv/getting-started/installation/)** - Fast Python package manager (will install Python 3.9+ automatically)
3. **[git](https://git-scm.com/)** - For version control
4. **[make](https://www.gnu.org/software/make/)** - For running development commands (or use `nmake` on Windows)
### Quick Start
```bash
# Clone the repository (or from your fork)
git clone git@github.com:pydantic/pydantic-core.git
cd pydantic-core
# Install all dependencies using uv, setup pre-commit hooks, and build the development version
make install
```
Verify your installation by running:
```bash
make
```
This runs a full development cycle: formatting, building, linting, and testing
### Development Commands
Run `make help` to see all available commands, or use these common ones:
```bash
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 all # to run to run build-dev + format + lint + test
```
### Useful Resources
* [`python/pydantic_core/_pydantic_core.pyi`](./python/pydantic_core/_pydantic_core.pyi) - Python API types
* [`python/pydantic_core/core_schema.py`](./python/pydantic_core/core_schema.py) - Core schema definitions
* [`tests/`](./tests) - Comprehensive usage examples
## 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
TBC (needs to be integrated into `pydantic` repository release process).

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