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:
call1
andcall_method1
to call only with positionalargs
.call0
andcall_method0
to call with no arguments.
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 any 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 Vec
s 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, 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()) } 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
.
Warning: This will compile and execute code. Never pass untrusted code to this function!
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(()) }) }
Want to embed Python in Rust with additional modules?
Python maintains the sys.modules
dict as a cache of all imported modules.
An import in Python will first attempt to lookup the module from this dict,
and if not present will use various strategies to attempt to locate and load
the module.
The append_to_inittab
macro can be used to add additional #[pymodule]
modules to an embedded
Python interpreter. The macro must be invoked before initializing Python.
As an example, the below adds the module foo
to the embedded interpreter:
use pyo3::prelude::*; #[pyfunction] fn add_one(x: i64) -> i64 { x + 1 } #[pymodule] fn foo(_py: Python<'_>, foo_module: &PyModule) -> PyResult<()> { foo_module.add_function(wrap_pyfunction!(add_one, foo_module)?)?; Ok(()) } fn main() -> PyResult<()> { pyo3::append_to_inittab!(foo); Python::with_gil(|py| Python::run(py, "import foo; foo.add_one(6)", None, None)) }
If append_to_inittab
cannot be used due to constraints in the program,
an alternative is to create a module using PyModule::new
and insert it manually into sys.modules
:
use pyo3::prelude::*; use pyo3::types::PyDict; #[pyfunction] pub fn add_one(x: i64) -> i64 { x + 1 } fn main() -> PyResult<()> { Python::with_gil(|py| { // Create new module let foo_module = PyModule::new(py, "foo")?; foo_module.add_function(wrap_pyfunction!(add_one, foo_module)?)?; // Import and get sys.modules let sys = PyModule::import(py, "sys")?; let py_modules: &PyDict = sys.getattr("modules")?.downcast()?; // Insert foo into sys.modules py_modules.set_item("foo", foo_module)?; // Now we can import + run our python code Python::run(py, "import foo; foo.add_one(6)", None, None) }) }
Include multiple Python files
You can include a file at compile time by using
std::include_str
macro.
Or you can load a file at runtime by using
std::fs::read_to_string
function.
Many Python files can be included and loaded as modules. If one file depends on
another you must preserve correct order while declaring PyModule
.
Example directory structure:
.
├── Cargo.lock
├── Cargo.toml
├── python_app
│ ├── app.py
│ └── utils
│ └── foo.py
└── src
└── main.rs
python_app/app.py
:
from utils.foo import bar
def run():
return bar()
python_app/utils/foo.py
:
def bar():
return "baz"
The example below shows:
- how to include content of
app.py
andutils/foo.py
into your rust binary - how to call function
run()
(declared inapp.py
) that needs function imported fromutils/foo.py
src/main.rs
:
use pyo3::prelude::*;
fn main() -> PyResult<()> {
let py_foo = include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/python_app/utils/foo.py"));
let py_app = include_str!(concat!(env!("CARGO_MANIFEST_DIR"), "/python_app/app.py"));
let from_python = Python::with_gil(|py| -> PyResult<Py<PyAny>> {
PyModule::from_code(py, py_foo, "utils.foo", "utils.foo")?;
let app: Py<PyAny> = PyModule::from_code(py, py_app, "", "")?
.getattr("run")?
.into();
app.call0(py)
});
println!("py: {}", from_python?);
Ok(())
}
The example below shows:
- how to load content of
app.py
at runtime so that it sees its dependencies automatically - how to call function
run()
(declared inapp.py
) that needs function imported fromutils/foo.py
It is recommended to use absolute paths because then your binary can be run
from anywhere as long as your app.py
is in the expected directory (in this example
that directory is /usr/share/python_app
).
src/main.rs
:
use pyo3::prelude::*; use pyo3::types::PyList; use std::fs; use std::path::Path; fn main() -> PyResult<()> { let path = Path::new("/usr/share/python_app"); let py_app = fs::read_to_string(path.join("app.py"))?; let from_python = Python::with_gil(|py| -> PyResult<Py<PyAny>> { let syspath: &PyList = py.import("sys")?.getattr("path")?.downcast()?; syspath.insert(0, &path)?; let app: Py<PyAny> = PyModule::from_code(py, &py_app, "", "")? .getattr("run")? .into(); app.call0(py) }); println!("py: {}", from_python?); 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(); } } }) }