Calling Python in Rust code

This chapter of the guide documents some ways to interact with Python code from Rust:

  • How to call Python functions
  • How to execute existing Python code

Calling Python functions

Any Python-native object reference (such as &PyAny, &PyList, or &PyCell<MyClass>) can be used to call Python functions.

PyO3 offers two APIs to make function calls:

  • call - call any callable Python object.
  • call_method - call a method on the Python object.

Both of these APIs take args and kwargs arguments (for positional and keyword arguments respectively). There are variants for less complex calls:

For convenience the Py<T> smart pointer also exposes these same six API methods, but needs a Python token as an additional first argument to prove the GIL is held.

The example below calls a Python function behind a PyObject (aka Py<PyAny>) reference:

use pyo3::prelude::*;
use pyo3::types::PyTuple;

fn main() -> PyResult<()> {
    let arg1 = "arg1";
    let arg2 = "arg2";
    let arg3 = "arg3";

    Python::with_gil(|py| {
        let fun: Py<PyAny> = PyModule::from_code(
            py,
            "def example(*args, **kwargs):
                if args != ():
                    print('called with args', args)
                if kwargs != {}:
                    print('called with kwargs', kwargs)
                if args == () and kwargs == {}:
                    print('called with no arguments')",
            "",
            "",
        )?.getattr("example")?.into();

        // call object without empty arguments
        fun.call0(py)?;

        // call object with PyTuple
        let args = PyTuple::new(py, &[arg1, arg2, arg3]);
        fun.call1(py, args)?;

        // pass arguments as rust tuple
        let args = (arg1, arg2, arg3);
        fun.call1(py, args)?;
        Ok(())
    })
}

Creating keyword arguments

For the call and call_method APIs, kwargs can be None or Some(&PyDict). You can use the IntoPyDict trait to convert other dict-like containers, e.g. HashMap or BTreeMap, as well as tuples with up to 10 elements and Vecs where each element is a two-element tuple.

use pyo3::prelude::*;
use pyo3::types::IntoPyDict;
use std::collections::HashMap;

fn main() -> PyResult<()> {
    let key1 = "key1";
    let val1 = 1;
    let key2 = "key2";
    let val2 = 2;

    Python::with_gil(|py| {
        let fun: Py<PyAny> = PyModule::from_code(
            py,
            "def example(*args, **kwargs):
                if args != ():
                    print('called with args', args)
                if kwargs != {}:
                    print('called with kwargs', kwargs)
                if args == () and kwargs == {}:
                    print('called with no arguments')",
            "",
            "",
        )?.getattr("example")?.into();


        // call object with PyDict
        let kwargs = [(key1, val1)].into_py_dict(py);
        fun.call(py, (), Some(kwargs))?;

        // pass arguments as Vec
        let kwargs = vec![(key1, val1), (key2, val2)];
        fun.call(py, (), Some(kwargs.into_py_dict(py)))?;

        // pass arguments as HashMap
        let mut kwargs = HashMap::<&str, i32>::new();
        kwargs.insert(key1, 1);
        fun.call(py, (), Some(kwargs.into_py_dict(py)))?;

        Ok(())
   })
}

Executing existing Python code

If you already have some existing Python code that you need to execute from Rust, the following FAQs can help you select the right PyO3 functionality for your situation:

Want to access Python APIs? Then use PyModule::import.

Pymodule::import can be used to get handle to a Python module from Rust. You can use this to import and use any Python module available in your environment.

use pyo3::prelude::*;

fn main() -> PyResult<()> {
    Python::with_gil(|py| {
        let builtins = PyModule::import(py, "builtins")?;
        let total: i32 = builtins.getattr("sum")?.call1((vec![1, 2, 3],))?.extract()?;
        assert_eq!(total, 6);
        Ok(())
    })
}

Want to run just an expression? Then use eval.

Python::eval is a method to execute a Python expression and return the evaluated value as a &PyAny object.

use pyo3::prelude::*;

fn main() -> Result<(), ()> {
Python::with_gil(|py| {
    let result = py.eval("[i * 10 for i in range(5)]", None, None).map_err(|e| {
        e.print_and_set_sys_last_vars(py);
    })?;
    let res: Vec<i64> = result.extract().unwrap();
    assert_eq!(res, vec![0, 10, 20, 30, 40]);
    Ok(())
})
}

Want to run statements? Then use run.

Python::run is a method to execute one or more Python statements. This method returns nothing (like any Python statement), but you can get access to manipulated objects via the locals dict.

You can also use the py_run! macro, which is a shorthand for Python::run. Since py_run! panics on exceptions, we recommend you use this macro only for quickly testing your Python extensions.

use pyo3::prelude::*;
use pyo3::{PyCell, PyObjectProtocol, py_run};

fn main() {
#[pyclass]
struct UserData {
    id: u32,
    name: String,
}

#[pymethods]
impl UserData {
    fn as_tuple(&self) -> (u32, String) {
        (self.id, self.name.clone())
    }
}

#[pyproto]
impl PyObjectProtocol for UserData {
    fn __repr__(&self) -> PyResult<String> {
        Ok(format!("User {}(id: {})", self.name, self.id))
    }
}

Python::with_gil(|py| {
    let userdata = UserData {
        id: 34,
        name: "Yu".to_string(),
    };
    let userdata = PyCell::new(py, userdata).unwrap();
    let userdata_as_tuple = (34, "Yu");
    py_run!(py, userdata userdata_as_tuple, r#"
assert repr(userdata) == "User Yu(id: 34)"
assert userdata.as_tuple() == userdata_as_tuple
    "#);
})
}

You have a Python file or code snippet? Then use PyModule::from_code.

PyModule::from_code can be used to generate a Python module which can then be used just as if it was imported with PyModule::import.

use pyo3::{prelude::*, types::{IntoPyDict, PyModule}};

fn main() -> PyResult<()> {
Python::with_gil(|py| {
    let activators = PyModule::from_code(py, r#"
def relu(x):
    """see https://en.wikipedia.org/wiki/Rectifier_(neural_networks)"""
    return max(0.0, x)

def leaky_relu(x, slope=0.01):
    return x if x >= 0 else x * slope
    "#, "activators.py", "activators")?;

    let relu_result: f64 = activators.getattr("relu")?.call1((-1.0,))?.extract()?;
    assert_eq!(relu_result, 0.0);

    let kwargs = [("slope", 0.2)].into_py_dict(py);
    let lrelu_result: f64 = activators
        .getattr("leaky_relu")?.call((-1.0,), Some(kwargs))?
        .extract()?;
    assert_eq!(lrelu_result, -0.2);
   Ok(())
})
}

Need to use a context manager from Rust?

Use context managers by directly invoking __enter__ and __exit__.

use pyo3::prelude::*;
use pyo3::types::PyModule;

fn main() {
    Python::with_gil(|py| {
        let custom_manager = PyModule::from_code(py, r#"
class House(object):
    def __init__(self, address):
        self.address = address
    def __enter__(self):
        print(f"Welcome to {self.address}!")
    def __exit__(self, type, value, traceback):
        if type:
            print(f"Sorry you had {type} trouble at {self.address}")
        else:
            print(f"Thank you for visiting {self.address}, come again soon!")

        "#, "house.py", "house").unwrap();

        let house_class = custom_manager.getattr("House").unwrap();
        let house = house_class.call1(("123 Main Street",)).unwrap();

        house.call_method0("__enter__").unwrap();

        let result = py.eval("undefined_variable + 1", None, None);

        // If the eval threw an exception we'll pass it through to the context manager.
        // Otherwise, __exit__  is called with empty arguments (Python "None").
        match result {
            Ok(_) => {
                let none = py.None();
                house.call_method1("__exit__", (&none, &none, &none)).unwrap();
            },
            Err(e) => {
                house.call_method1(
                    "__exit__",
                    (e.get_type(py), e.value(py), e.traceback(py))
                ).unwrap();
            }
        }
    })
}