Struct pyo3::marker::Python

pub struct Python<'py>(_);

A marker token that represents holding the GIL.

It serves three main purposes:

• It provides a global API for the Python interpreter, such as Python::eval.
• It can be passed to functions that require a proof of holding the GIL, such as Py::clone_ref.
• Its lifetime represents the scope of holding the GIL which can be used to create Rust references that are bound to it, such as &PyAny.

Note that there are some caveats to using it that you might need to be aware of. See the Deadlocks and Releasing and freeing memory paragraphs for more information about that.

Obtaining a Python token

The following are the recommended ways to obtain a Python token, in order of preference:

• In a function or method annotated with #[pyfunction] or #[pymethods] you can declare it as a parameter, and PyO3 will pass in the token when Python code calls it.
• If you already have something with a lifetime bound to the GIL, such as &PyAny, you can use its .py() method to get a token.
• When you need to acquire the GIL yourself, such as when calling Python code from Rust, you should call Python::with_gil to do that and pass your code as a closure to it.

Deadlocks

Note that the GIL can be temporarily released by the Python interpreter during a function call (e.g. importing a module). In general, you don’t need to worry about this because the GIL is reacquired before returning to the Rust code:

`Python` exists   |=====================================|
GIL actually held |==========|         |================|
Rust code running |=======|                |==|  |======|

This behaviour can cause deadlocks when trying to lock a Rust mutex while holding the GIL:

• Thread 1 acquires the GIL
• Thread 1 locks a mutex
• Thread 1 makes a call into the Python interpreter which releases the GIL
• Thread 2 acquires the GIL
• Thread 2 tries to locks the mutex, blocks
• Thread 1’s Python interpreter call blocks trying to reacquire the GIL held by thread 2

To avoid deadlocking, you should release the GIL before trying to lock a mutex or awaiting in asynchronous code, e.g. with Python::allow_threads.

Releasing and freeing memory

The Python type can be used to create references to variables owned by the Python interpreter, using functions such as Python::eval and PyModule::import. These references are tied to a GILPool whose references are not cleared until it is dropped. This can cause apparent “memory leaks” if it is kept around for a long time.

use pyo3::prelude::*;
use pyo3::types::PyString;

Python::with_gil(|py| -> PyResult<()> {
    for _ in 0..10 {
        let hello: &PyString = py.eval("\"Hello World!\"", None, None)?.extract()?;
        println!("Python says: {}", hello.to_str()?);
        // Normally variables in a loop scope are dropped here, but `hello` is a reference to
        // something owned by the Python interpreter. Dropping this reference does nothing.
    }
    Ok(())
})
// This is where the `hello`'s reference counts start getting decremented.

The variable hello is dropped at the end of each loop iteration, but the lifetime of the pointed-to memory is bound to Python::with_gil’s GILPool which will not be dropped until the end of Python::with_gil’s scope. Only then is each hello’s Python reference count decreased. This means that at the last line of the example there are 10 copies of hello in Python’s memory, not just one at a time as we might expect from Rust’s scoping rules.

See the Memory Management chapter of the guide for more information about how PyO3 uses GILPool to manage memory.

Implementations

impl Python<'_>

pub fn with_gil<F, R>(f: F) -> Rwhere F: for<'py> FnOnce(Python<'py>) -> R,

Acquires the global interpreter lock, allowing access to the Python interpreter. The provided closure F will be executed with the acquired Python marker token.

If implementing #[pymethods] or #[pyfunction], declare py: Python as an argument. PyO3 will pass in the token to grant access to the GIL context in which the function is running, avoiding the need to call with_gil.

If the auto-initialize feature is enabled and the Python runtime is not already initialized, this function will initialize it. See prepare_freethreaded_python for details.

If the current thread does not yet have a Python “thread state” associated with it, a new one will be automatically created before F is executed and destroyed after F completes.

Panics

• If the auto-initialize feature is not enabled and the Python interpreter is not initialized.

Examples

use pyo3::prelude::*;

Python::with_gil(|py| -> PyResult<()> {
    let x: i32 = py.eval("5", None, None)?.extract()?;
    assert_eq!(x, 5);
    Ok(())
})

pub unsafe fn with_gil_unchecked<F, R>(f: F) -> Rwhere F: for<'py> FnOnce(Python<'py>) -> R,

Like Python::with_gil except Python interpreter state checking is skipped.

Normally when the GIL is acquired, we check that the Python interpreter is an appropriate state (e.g. it is fully initialized). This function skips those checks.

Safety

If Python::with_gil would succeed, it is safe to call this function.

In most cases, you should use Python::with_gil.

A justified scenario for calling this function is during multi-phase interpreter initialization when Python::with_gil would fail before _Py_InitializeMain is called because the interpreter is only partially initialized.

Behavior in other scenarios is not documented.

impl<'py> Python<'py>

pub fn allow_threads<T, F>(self, f: F) -> Twhere F: Ungil + FnOnce() -> T, T: Ungil,

Temporarily releases the GIL, thus allowing other Python threads to run. The GIL will be reacquired when F’s scope ends.

If you don’t need to touch the Python interpreter for some time and have other Python threads around, this will let you run Rust-only code while letting those other Python threads make progress.

Only types that implement Ungil can cross the closure. See the module level documentation for more information.

If you need to pass Python objects into the closure you can use Py<T>to create a reference independent of the GIL lifetime. However, you cannot do much with those without a Python token, for which you’d need to reacquire the GIL.

Example: Releasing the GIL while running a computation in Rust-only code

use pyo3::prelude::*;

#[pyfunction]
fn sum_numbers(py: Python<'_>, numbers: Vec<u32>) -> PyResult<u32> {
    // We release the GIL here so any other Python threads get a chance to run.
    py.allow_threads(move || {
        // An example of an "expensive" Rust calculation
        let sum = numbers.iter().sum();

        Ok(sum)
    })
}

Please see the Parallelism chapter of the guide for a thorough discussion of using Python::allow_threads in this manner.

Example: Passing borrowed Python references into the closure is not allowed

use pyo3::prelude::*;
use pyo3::types::PyString;

fn parallel_print(py: Python<'_>) {
    let s = PyString::new(py, "This object cannot be accessed without holding the GIL >_<");
    py.allow_threads(move || {
        println!("{:?}", s); // This causes a compile error.
    });
}

pub fn eval( self, code: &str, globals: Option<&PyDict>, locals: Option<&PyDict> ) -> PyResult<&'py PyAny>

Evaluates a Python expression in the given context and returns the result.

If globals is None, it defaults to Python module __main__. If locals is None, it defaults to the value of globals.

Examples

let result = py.eval("[i * 10 for i in range(5)]", None, None).unwrap();
let res: Vec<i64> = result.extract().unwrap();
assert_eq!(res, vec![0, 10, 20, 30, 40])

pub fn run( self, code: &str, globals: Option<&PyDict>, locals: Option<&PyDict> ) -> PyResult<()>

Executes one or more Python statements in the given context.

If globals is None, it defaults to Python module __main__. If locals is None, it defaults to the value of globals.

Examples

use pyo3::{
    prelude::*,
    types::{PyBytes, PyDict},
};
Python::with_gil(|py| {
    let locals = PyDict::new(py);
    py.run(
        r#"
import base64
s = 'Hello Rust!'
ret = base64.b64encode(s.encode('utf-8'))
"#,
        None,
        Some(locals),
    )
    .unwrap();
    let ret = locals.get_item("ret").unwrap();
    let b64: &PyBytes = ret.downcast().unwrap();
    assert_eq!(b64.as_bytes(), b"SGVsbG8gUnVzdCE=");
});

You can use py_run! for a handy alternative of run if you don’t need globals and unwrapping is OK.

pub fn get_type<T>(self) -> &'py PyTypewhere T: PyTypeInfo,

Gets the Python type object for type T.

pub fn import<N>(self, name: N) -> PyResult<&'py PyModule>where N: IntoPy<Py<PyString>>,

Imports the Python module with the specified name.

pub fn None(self) -> PyObject

Gets the Python builtin value None.

pub fn Ellipsis(self) -> PyObject

Gets the Python builtin value Ellipsis, or ....

pub fn NotImplemented(self) -> PyObject

Gets the Python builtin value NotImplemented.

pub fn version(self) -> &'py str

Gets the running Python interpreter version as a string.

Examples

Python::with_gil(|py| {
    // The full string could be, for example:
    // "3.10.0 (tags/v3.10.0:b494f59, Oct  4 2021, 19:00:18) [MSC v.1929 64 bit (AMD64)]"
    assert!(py.version().starts_with("3."));
});

pub fn version_info(self) -> PythonVersionInfo<'py>

Gets the running Python interpreter version as a struct similar to sys.version_info.

Examples

Python::with_gil(|py| {
    // PyO3 supports Python 3.7 and up.
    assert!(py.version_info() >= (3, 7));
    assert!(py.version_info() >= (3, 7, 0));
});

pub fn checked_cast_as<T>( self, obj: PyObject ) -> Result<&'py T, PyDowncastError<'py>>where T: PyTryFrom<'py>,

Registers the object in the release pool, and tries to downcast to specific type.

pub unsafe fn cast_as<T>(self, obj: PyObject) -> &'py Twhere T: PyNativeType + PyTypeInfo,

Registers the object in the release pool, and does an unchecked downcast to the specific type.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_owned_ptr<T>(self, ptr: *mut PyObject) -> &'py Twhere T: FromPyPointer<'py>,

Registers the object pointer in the release pool, and does an unchecked downcast to the specific type.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_owned_ptr_or_err<T>( self, ptr: *mut PyObject ) -> PyResult<&'py T>where T: FromPyPointer<'py>,

Registers the owned object pointer in the release pool.

Returns Err(PyErr) if the pointer is NULL. Does an unchecked downcast to the specific type.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_owned_ptr_or_opt<T>( self, ptr: *mut PyObject ) -> Option<&'py T>where T: FromPyPointer<'py>,

Registers the owned object pointer in release pool.

Returns None if the pointer is NULL. Does an unchecked downcast to the specific type.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_borrowed_ptr<T>(self, ptr: *mut PyObject) -> &'py Twhere T: FromPyPointer<'py>,

Does an unchecked downcast to the specific type.

Panics if the pointer is NULL.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_borrowed_ptr_or_err<T>( self, ptr: *mut PyObject ) -> PyResult<&'py T>where T: FromPyPointer<'py>,

Does an unchecked downcast to the specific type.

Returns Err(PyErr) if the pointer is NULL.

Safety

Callers must ensure that ensure that the cast is valid.

pub unsafe fn from_borrowed_ptr_or_opt<T>( self, ptr: *mut PyObject ) -> Option<&'py T>where T: FromPyPointer<'py>,

Does an unchecked downcast to the specific type.

Returns None if the pointer is NULL.

Safety

Callers must ensure that ensure that the cast is valid.

pub fn check_signals(self) -> PyResult<()>

Lets the Python interpreter check and handle any pending signals. This will invoke the corresponding signal handlers registered in Python (if any).

Returns Err(PyErr) if any signal handler raises an exception.

These signals include SIGINT (normally raised by CTRL + C), which by default raises KeyboardInterrupt. For this reason it is good practice to call this function regularly as part of long-running Rust functions so that users can cancel it.

Example

use pyo3::prelude::*;

#[pyfunction]
fn loop_forever(py: Python<'_>) -> PyResult<()> {
    loop {
        // As this loop is infinite it should check for signals every once in a while.
        // Using `?` causes any `PyErr` (potentially containing `KeyboardInterrupt`)
        // to break out of the loop.
        py.check_signals()?;

        // do work here
    }
}

Note

This function calls PyErr_CheckSignals() which in turn may call signal handlers. As Python’s signal API allows users to define custom signal handlers, calling this function allows arbitrary Python code inside signal handlers to run.

pub unsafe fn new_pool(self) -> GILPool

Create a new pool for managing PyO3’s owned references.

When this GILPool is dropped, all PyO3 owned references created after this GILPool will all have their Python reference counts decremented, potentially allowing Python to drop the corresponding Python objects.

Typical usage of PyO3 will not need this API, as Python::with_gil automatically creates a GILPool where appropriate.

Advanced uses of PyO3 which perform long-running tasks which never free the GIL may need to use this API to clear memory, as PyO3 usually does not clear memory until the GIL is released.

Examples

Python::with_gil(|py| {
    // Some long-running process like a webserver, which never releases the GIL.
    loop {
        // Create a new pool, so that PyO3 can clear memory at the end of the loop.
        let pool = unsafe { py.new_pool() };

        // It is recommended to *always* immediately set py to the pool's Python, to help
        // avoid creating references with invalid lifetimes.
        let py = pool.python();

        // do stuff...
    }
});

Safety

Extreme care must be taken when using this API, as misuse can lead to accessing invalid memory. In addition, the caller is responsible for guaranteeing that the GIL remains held for the entire lifetime of the returned GILPool.

Two best practices are required when using this API:

• From the moment new_pool() is called, only the Python token from the returned GILPool (accessible using .python()) should be used in PyO3 APIs. All other older Python tokens with longer lifetimes are unsafe to use until the GILPool is dropped, because they can be used to create PyO3 owned references which have lifetimes which outlive the GILPool.
• Similarly, methods on existing owned references will implicitly refer back to the Python token which that reference was originally created with. If the returned values from these methods are owned references they will inherit the same lifetime. As a result, Rust’s lifetime rules may allow them to outlive the GILPool, even though this is not safe for reasons discussed above. Care must be taken to never access these return values after the GILPool is dropped, unless they are converted to Py<T> before the pool is dropped.

impl Python<'_>

pub fn with_pool<F, R>(&self, f: F) -> Rwhere F: for<'py> FnOnce(Python<'py>) -> R + Ungil,

Creates a scope using a new pool for managing PyO3’s owned references.

This is a safe alterantive to new_pool as it limits the closure to using the new GIL token at the cost of being unable to capture existing GIL-bound references.

Note that on stable Rust, this API suffers from the same the SendWrapper loophole as allow_threads, c.f. the documentation of the Ungil trait,

Examples

Python::with_gil(|py| {
    // Some long-running process like a webserver, which never releases the GIL.
    loop {
        // Create a new scope, so that PyO3 can clear memory at the end of the loop.
        py.with_pool(|py| {
            // do stuff...
        });
    }
});

The Ungil bound on the closure does prevent hanging on to existing GIL-bound references

Python::with_gil(|py| {
    let old_str = PyString::new(py, "a message from the past");

    py.with_pool(|_py| {
        print!("{:?}", old_str);
    });
});

or continuing to use the old GIL token

Python::with_gil(|old_py| {
    old_py.with_pool(|_new_py| {
        let _none = old_py.None();
    });
});

impl<'unbound> Python<'unbound>

pub unsafe fn assume_gil_acquired() -> Python<'unbound>

Unsafely creates a Python token with an unbounded lifetime.

Many of PyO3 APIs use Python<'_> as proof that the GIL is held, but this function can be used to call them unsafely.

Safety

• This token and any borrowed Python references derived from it can only be safely used whilst the currently executing thread is actually holding the GIL.
• This function creates a token with an unbounded lifetime. Safe code can assume that holding a Python<'py> token means the GIL is and stays acquired for the lifetime 'py. If you let it or borrowed Python references escape to safe code you are responsible for bounding the lifetime 'unbound appropriately. For more on unbounded lifetimes, see the nomicon.

Trait Implementations

impl<'py> Clone for Python<'py>

fn clone(&self) -> Python<'py>

Returns a copy of the value.

fn clone_from(&mut self, source: &Self)

Performs copy-assignment from source.

impl<'py> Copy for Python<'py>