155 lines
6.9 KiB
Markdown
155 lines
6.9 KiB
Markdown
# PyO3
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[](https://travis-ci.org/PyO3/pyo3)
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[](https://github.com/PyO3/pyo3/actions)
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[](https://codecov.io/gh/PyO3/pyo3)
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[](https://crates.io/crates/pyo3)
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[](https://gitter.im/PyO3/Lobby)
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[Rust](http://www.rust-lang.org/) bindings for [Python](https://www.python.org/). This includes running and interacting with Python code from a Rust binary, as well as writing native Python modules.
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* User Guide: [stable](https://pyo3.rs) | [master](https://pyo3.rs/master)
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* API Documentation: [stable](https://docs.rs/pyo3/) | [master](https://pyo3.rs/master/doc)
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A comparison with rust-cpython can be found [in the guide](https://pyo3.rs/master/rust_cpython.html).
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## Usage
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PyO3 supports Python 3.5 and up. The minimum required Rust version is 1.42.0-nightly 2020-01-21.
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If you have never used nightly Rust, the official guide has
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[a great section](https://doc.rust-lang.org/book/appendix-07-nightly-rust.html#rustup-and-the-role-of-rust-nightly)
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about installing it.
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PyPy is also supported (via cpyext) for Python 3.5 only, targeted PyPy version is 7.0.0.
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Please refer to the guide for installation instruction against PyPy.
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You can either write a native Python module in Rust, or use Python from a Rust binary.
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However, on some OSs, you need some additional packages. E.g. if you are on *Ubuntu 18.04*, please run
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```bash
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sudo apt install python3-dev python-dev
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```
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## Using Rust from Python
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PyO3 can be used to generate a native Python module.
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**`Cargo.toml`**
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```toml
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[package]
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name = "string-sum"
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version = "0.1.0"
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edition = "2018"
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[lib]
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name = "string_sum"
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crate-type = ["cdylib"]
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[dependencies.pyo3]
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version = "0.9.0-alpha.1"
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features = ["extension-module"]
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```
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**`src/lib.rs`**
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```rust
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use pyo3::prelude::*;
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use pyo3::wrap_pyfunction;
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#[pyfunction]
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/// Formats the sum of two numbers as string
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fn sum_as_string(a: usize, b: usize) -> PyResult<String> {
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Ok((a + b).to_string())
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}
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/// This module is a python module implemented in Rust.
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#[pymodule]
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fn string_sum(py: Python, m: &PyModule) -> PyResult<()> {
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m.add_wrapped(wrap_pyfunction!(sum_as_string))?;
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Ok(())
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}
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```
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On Windows and Linux, you can build normally with `cargo build --release`. On macOS, you need to set additional linker arguments. One option is to compile with `cargo rustc --release -- -C link-arg=-undefined -C link-arg=dynamic_lookup`, the other is to create a `.cargo/config` with the following content:
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```toml
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[target.x86_64-apple-darwin]
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rustflags = [
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"-C", "link-arg=-undefined",
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"-C", "link-arg=dynamic_lookup",
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]
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```
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For developing, you can 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`.
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To build, test and publish your crate as a Python module, you can use [maturin](https://github.com/PyO3/maturin) or [setuptools-rust](https://github.com/PyO3/setuptools-rust). You can find an example for setuptools-rust in [examples/word-count](examples/word-count), while maturin should work on your crate without any configuration.
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## Using Python from Rust
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Add `pyo3` to your `Cargo.toml` like this:
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```toml
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[dependencies]
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pyo3 = "0.9.0-alpha.1"
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```
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Example program displaying the value of `sys.version` and the current user name:
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```rust
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use pyo3::prelude::*;
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use pyo3::types::IntoPyDict;
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fn main() -> Result<(), ()> {
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let gil = Python::acquire_gil();
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let py = gil.python();
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main_(py).map_err(|e| {
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// We can't display python error type via ::std::fmt::Display,
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// so print error here manually.
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e.print_and_set_sys_last_vars(py);
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})
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}
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fn main_(py: Python) -> PyResult<()> {
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let sys = py.import("sys")?;
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let version: String = sys.get("version")?.extract()?;
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let locals = [("os", py.import("os")?)].into_py_dict(py);
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let code = "os.getenv('USER') or os.getenv('USERNAME') or 'Unknown'";
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let user: String = py.eval(code, None, Some(&locals))?.extract()?;
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println!("Hello {}, I'm Python {}", user, version);
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Ok(())
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}
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```
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Our guide has [a section](https://pyo3.rs/master/python_from_rust.html) with lots of examples
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about this topic.
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## Examples and tooling
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* [examples/word-count](examples/word-count) _Counting the occurrences of a word in a text file_
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* [hyperjson](https://github.com/mre/hyperjson) _A hyper-fast Python module for reading/writing JSON data using Rust's serde-json_
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* [rust-numpy](https://github.com/PyO3/rust-numpy) _Rust binding of NumPy C-API_
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* [html-py-ever](https://github.com/PyO3/setuptools-rust/tree/master/html-py-ever) _Using [html5ever](https://github.com/servo/html5ever) through [kuchiki](https://github.com/kuchiki-rs/kuchiki) to speed up html parsing and css-selecting._
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* [pyo3-built](https://github.com/PyO3/pyo3-built) _Simple macro to expose metadata obtained with the [`built`](https://crates.io/crates/built) crate as a [`PyDict`](https://pyo3.github.io/pyo3/pyo3/struct.PyDict.html)_
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* [point-process](https://github.com/ManifoldFR/point-process-rust/tree/master/pylib) _High level API for pointprocesses as a Python library_
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* [autopy](https://github.com/autopilot-rs/autopy) _A simple, cross-platform GUI automation library for Python and Rust._
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* Contains an example of building wheels on TravisCI and appveyor using [cibuildwheel](https://github.com/joerick/cibuildwheel)
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* [orjson](https://github.com/ijl/orjson) _Fast Python JSON library_
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* [inline-python](https://github.com/dronesforwork/inline-python) _Inline Python code directly in your Rust code_
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* [Rogue-Gym](https://github.com/kngwyu/rogue-gym) _Customizable rogue-like game for AI experiments_
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* Contains an example of building wheels on Azure Pipelines
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* [fastuuid](https://github.com/thedrow/fastuuid/) _Python bindings to Rust's UUID library_
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* [python-ext-wasm](https://github.com/wasmerio/python-ext-wasm) _Python library to run WebAssembly binaries_
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* [dict-derive](https://github.com/gperinazzo/dict-derive) _Derive FromPyObject to automatically transform Python dicts into Rust structs_
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* [mocpy](https://github.com/cds-astro/mocpy) _Astronomical Python library offering data structures for describing any arbitrary coverage regions on the unit sphere_
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* [tokenizers](https://github.com/huggingface/tokenizers/tree/master/bindings/python) _Python bindings to the Hugging Face tokenizers (NLP) written in Rust_
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## License
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PyO3 is licensed under the [Apache-2.0 license](http://opensource.org/licenses/APACHE-2.0).
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Python is licensed under the [Python License](https://docs.python.org/2/license.html).
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