Crate pyo3[−][src]

Expand description

Rust bindings to the Python interpreter.

PyO3 can be used to write native Python modules or run Python code and modules from Rust.

See the guide for a detailed introduction.

PyO3’s object types

PyO3 has several core types that you should familiarize yourself with:

The Python<’py> object

Holding the global interpreter lock (GIL) is modeled with the Python<'py> token. All APIs that require that the GIL is held require this token as proof that you really are holding the GIL. It can be explicitly acquired and is also implicitly acquired by PyO3 as it wraps Rust functions and structs into Python functions and objects.

The GIL-dependent types

For example &PyAny. These are only ever seen as references, with a lifetime that is only valid for as long as the GIL is held, which is why using them doesn’t require a Python<'py> token. The underlying Python object, if mutable, can be mutated through any reference.

See the guide for an explanation of the different Python object types.

The GIL-independent types

When wrapped in Py<...>, like with Py<PyAny> or Py<SomePyClass>, Python objects no longer have a limited lifetime which makes them easier to store in structs and pass between functions. However, you cannot do much with them without a Python<'py> token, for which you’d need to reacquire the GIL.

PyErr

The vast majority of operations in this library will return PyResult<...>. This is an alias for the type Result<..., PyErr>.

A PyErr represents a Python exception. A PyErr returned to Python code will be raised as a Python exception. Errors from PyO3 itself are also exposed as Python exceptions.

Feature flags

PyO3 uses feature flags to enable you to opt-in to additional functionality. For a detailed description, see the Features Reference chapter of the guide.

Default feature flags

The following features are turned on by default:

macros: Enables various macros, including all the attribute macros.

Optional feature flags

The following features are optional:

abi3: Restricts PyO3’s API to a subset of the full Python API which is guaranteed by PEP 384 to be forward-compatible with future Python versions.
auto-initialize: Changes Python::with_gil and Python::acquire_gil to automatically initialize the Python interpreter if needed.
extension-module: This will tell the linker to keep the Python symbols unresolved, so that your module can also be used with statically linked Python interpreters. Use this feature when building an extension module.
hashbrown: Enables conversions between Python objects and hashbrown’s HashMap and HashSet types.
indexmap: Enables conversions between Python dictionary and indexmap’s IndexMap.
multiple-pymethods: Enables the use of multiple #[pymethods] blocks per #[pyclass]. This adds a dependency on the inventory crate, which is not supported on all platforms.
num-bigint: Enables conversions between Python objects and num-bigint’s BigInt and BigUint types.
num-complex: Enables conversions between Python objects and num-complex’s Complex type.
serde: Allows implementing serde’s Serialize and Deserialize traits for Py<T> for all T that implement Serialize and Deserialize.

Unstable features

nightly: Gates some optimizations that rely on #![feature(specialization)], for which you’d also need nightly Rust. You should not use this feature.

`rustc` environment flags

PyO3 uses rustc’s --cfg flags to enable or disable code used for different Python versions. If you want to do this for your own crate, you can do so with the pyo3-build-config crate.

Py_3_6, Py_3_7, Py_3_8, Py_3_9, Py_3_10: Marks code that is only enabled when compiling for a given minimum Python version.
Py_LIMITED_API: Marks code enabled when the abi3 feature flag is enabled.
PyPy - Marks code enabled when compiling for PyPy.

Minimum supported Rust and Python versions

PyO3 supports the following software versions:

Python 3.6 and up (CPython and PyPy)
Rust 1.41 and up

Example: Building a native Python module

PyO3 can be used to generate a native Python module. The easiest way to try this out for the first time is to use maturin. maturin is a tool for building and publishing Rust-based Python packages with minimal configuration. The following steps set up some files for an example Python module, install maturin, and then show how build and import the Python module.

First, create a new folder (let’s call it string_sum) containing the following two files:

Cargo.toml

[package]
name = "string-sum"
version = "0.1.0"
edition = "2018"

[lib]
name = "string_sum"
crate-type = ["cdylib"]

[dependencies.pyo3]
version = "*"
features = ["extension-module"]

src/lib.rs

use pyo3::prelude::*;

/// 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(())
}

With those two files in place, now maturin needs to be installed. This can be done using Python’s package manager pip. First, load up a new Python virtualenv, and install maturin into it:

$ cd string_sum
$ python -m venv .env
$ source .env/bin/activate
$ pip install maturin

Now build and execute the module:

$ maturin develop
$ python
>>> import string_sum
>>> string_sum.sum_as_string(5, 20)
'25'

As well as with maturin, it is possible to build using setuptools-rust or manually. Both offer more flexibility than maturin but require further configuration.

Example: Using Python from Rust

To embed Python into a Rust binary, you need to ensure that your Python installation contains a shared library. The following steps demonstrate how to ensure this (for Ubuntu), and then give some example code which runs an embedded Python interpreter.

To install the Python shared library on Ubuntu:

sudo apt install python3-dev

Start a new project with cargo new and add pyo3 to the Cargo.toml like this:

[dependencies.pyo3]
version = "*"
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() -> PyResult<()> {
    Python::with_gil(|py| {
        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(())
    })
}

The guide has a section with lots of examples about this topic.

Other Examples

The PyO3 README contains quick-start examples for both using Rust from Python and Python from Rust.

The PyO3 repository’s examples subdirectory contains some basic packages to demonstrate usage of PyO3.

There are many projects using PyO3 - see a list of some at https://github.com/PyO3/pyo3#examples

Re-exports

pub use crate::class::*;

pub use crate::conversion::AsPyPointer;

pub use crate::conversion::FromPyObject;

pub use crate::conversion::FromPyPointer;

pub use crate::conversion::IntoPy;

pub use crate::conversion::IntoPyPointer;

pub use crate::conversion::PyTryFrom;

pub use crate::conversion::PyTryInto;

pub use crate::conversion::ToBorrowedObject;

pub use crate::conversion::ToPyObject;

pub use crate::pycell::PyCell;

pub use crate::pycell::PyRef;

pub use crate::pycell::PyRefMut;

pub use crate::pyclass::PyClass;

pub use crate::pyclass_init::PyClassInitializer;

pub use crate::type_object::PyTypeInfo;

Modules

buffer

PyBuffer implementation

class

Python object protocols

conversion

Conversions between various states of Rust and Python types and their wrappers.

exceptions

Exception types defined by Python.

ffi

Raw FFI declarations for Python’s C API.

impl_

Internals of PyO3 which are accessed by code expanded from PyO3’s procedural macros. Usage of any of these APIs in downstream code is implicitly acknowledging that these APIs may change at any time without documentation in the CHANGELOG and without breaking semver guarantees.

marshal

Support for the Python marshal format. Not supported in limited API builds.

once_cell

A write-once cell mediated by the Python GIL.

panic

Helper to convert Rust panics to Python exceptions.

prelude

A collection of items you most likely want to have in scope when working with pyo3

proc_macro

The proc macros, all of which are part of the prelude.

pycell

Includes PyCell implementation.