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.github | ||
benches | ||
examples | ||
guide | ||
pyo3-build-config | ||
pyo3-macros | ||
pyo3-macros-backend | ||
src | ||
tests | ||
.gitignore | ||
Architecture.md | ||
CHANGELOG.md | ||
Cargo.toml | ||
Code-of-Conduct.md | ||
Contributing.md | ||
LICENSE | ||
Makefile | ||
README.md | ||
build.rs | ||
codecov.yml | ||
pyproject.toml | ||
tox.ini |
README.md
PyO3
Rust bindings for Python, including tools for creating native Python extension modules. Running and interacting with Python code from a Rust binary is also supported.
Usage
PyO3 supports Python 3.6 and up. The minimum required Rust version is 1.41.
PyPy is also supported. Some minor features are unavailable on PyPy - please refer to the pypy section in the guide for more information.
You can either write a native Python module in Rust, or use Python from a Rust binary.
However, on some OSs, you need some additional packages. E.g. if you are on Ubuntu 18.04, please run
sudo apt install python3-dev python-dev
Using Rust from Python
PyO3 can be used to generate a native Python module.
Cargo.toml
[package]
name = "string-sum"
version = "0.1.0"
edition = "2018"
[lib]
name = "string_sum"
# "cdylib" is necessary to produce a shared library for Python to import from.
#
# Downstream Rust code (including code in `bin/`, `examples/`, and `tests/`) will not be able
# to `use string_sum;` unless the "rlib" or "lib" crate type is also included, e.g.:
# crate-type = ["cdylib", "rlib"]
crate-type = ["cdylib"]
[dependencies.pyo3]
version = "0.13.2"
features = ["extension-module"]
src/lib.rs
use pyo3::prelude::*;
use pyo3::wrap_pyfunction;
/// Formats the sum of two numbers as string.
#[pyfunction]
fn sum_as_string(a: usize, b: usize) -> PyResult<String> {
Ok((a + b).to_string())
}
/// A Python module implemented in Rust.
#[pymodule]
fn string_sum(py: Python, m: &PyModule) -> PyResult<()> {
m.add_function(wrap_pyfunction!(sum_as_string, m)?)?;
Ok(())
}
While developing, you can symlink (or copy) and rename the shared library from the target folder: On MacOS, rename libstring_sum.dylib
to string_sum.so
, on Windows libstring_sum.dll
to string_sum.pyd
, and on Linux libstring_sum.so
to string_sum.so
. Then open a Python shell in the same folder and you'll be able to import string_sum
.
To build, test and publish your crate as a Python module, you can use maturin or setuptools-rust. You can find an example for setuptools-rust in examples/word-count, while maturin should work on your crate without any configuration.
Using Python from Rust
If you want your Rust application to create a Python interpreter internally and
use it to run Python code, add pyo3
to your Cargo.toml
like this:
[dependencies.pyo3]
version = "0.13.2"
features = ["auto-initialize"]
Example program displaying the value of sys.version
and the current user name:
use pyo3::prelude::*;
use pyo3::types::IntoPyDict;
fn main() -> Result<(), ()> {
Python::with_gil(|py| {
main_(py).map_err(|e| {
// We can't display Python exceptions via std::fmt::Display,
// so print the error here manually.
e.print_and_set_sys_last_vars(py);
})
})
}
fn main_(py: Python) -> PyResult<()> {
let sys = py.import("sys")?;
let version: String = sys.get("version")?.extract()?;
let locals = [("os", py.import("os")?)].into_py_dict(py);
let code = "os.getenv('USER') or os.getenv('USERNAME') or 'Unknown'";
let user: String = py.eval(code, None, Some(&locals))?.extract()?;
println!("Hello {}, I'm Python {}", user, version);
Ok(())
}
Our guide has a section with lots of examples about this topic.
Tools and libraries
- maturin Zero configuration build tool for Rust-made Python extensions.
- setuptools-rust Setuptools plugin for Rust support.
- pyo3-built Simple macro to expose metadata obtained with the
built
crate as aPyDict
- rust-numpy Rust binding of NumPy C-API
- dict-derive Derive FromPyObject to automatically transform Python dicts into Rust structs
- pyo3-log Bridge from Rust to Python logging
- pythonize Serde serializer for converting Rust objects to JSON-compatible Python objects
- pyo3-asyncio Utilities for working with Python's Asyncio library and async functions
Examples
- hyperjson A hyper-fast Python module for reading/writing JSON data using Rust's serde-json
- html-py-ever Using html5ever through kuchiki to speed up html parsing and css-selecting.
- point-process High level API for pointprocesses as a Python library
- autopy A simple, cross-platform GUI automation library for Python and Rust.
- Contains an example of building wheels on TravisCI and appveyor using cibuildwheel
- orjson Fast Python JSON library
- inline-python Inline Python code directly in your Rust code
- Rogue-Gym Customizable rogue-like game for AI experiments
- Contains an example of building wheels on Azure Pipelines
- fastuuid Python bindings to Rust's UUID library
- wasmer-python Python library to run WebAssembly binaries
- mocpy Astronomical Python library offering data structures for describing any arbitrary coverage regions on the unit sphere
- tokenizers Python bindings to the Hugging Face tokenizers (NLP) written in Rust
- pyre Fast Python HTTP server written in Rust
- jsonschema-rs Fast JSON Schema validation library
- css-inline CSS inlining for Python implemented in Rust
- cryptography Python cryptography library with some functionality in Rust
- polaroid Hyper Fast and safe image manipulation library for Python written in Rust
Contributing
Everyone is welcomed to contribute to PyO3! There are many ways to support the project, such as:
- help PyO3 users with issues on Github and Gitter
- improve documentation
- write features and bugfixes
- publish blogs and examples of how to use PyO3
Our contributing notes and architecture guide have more resources if you wish to volunteer time for PyO3 and are searching where to start.
If you don't have time to contribute yourself but still wish to support the project's future success, some of our maintainers have Github sponsorship pages:
License
PyO3 is licensed under the Apache-2.0 license. Python is licensed under the Python License.