161 lines
6.4 KiB
Plaintext
161 lines
6.4 KiB
Plaintext
Metadata-Version: 2.3
|
|
Name: pydantic_core
|
|
Version: 2.18.2
|
|
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 :: 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
|
|
|
|
[![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
|
|
|
|
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 🎉
|
|
|