GIL lifetimes, mutability and Python object types
On first glance, PyO3 provides a huge number of different types that can be used to wrap or refer to Python objects. This page delves into the details and gives an overview of their intended meaning, with examples when each type is best used.
Mutability and Rust types
Since Python has no concept of ownership, and works solely with boxed objects, any Python object can be referenced any number of times, and mutation is allowed from any reference.
The situation is helped a little by the Global Interpreter Lock (GIL), which ensures that only one thread can use the Python interpreter and its API at the same time, while non-Python operations (system calls and extension code) can unlock the GIL. (See the section on parallelism for how to do that in PyO3.)
In PyO3, holding the GIL is modeled by acquiring a token of the type
Python<'py>
, which serves three purposes:
- It provides some global API for the Python interpreter, such as
eval
. - It can be passed to functions that require a proof of holding the GIL,
such as
Py::clone_ref
. - Its lifetime can be used to create Rust references that implicitly guarantee
holding the GIL, such as
&'py PyAny
.
The latter two points are the reason why some APIs in PyO3 require the py: Python
argument, while others don't.
The PyO3 API for Python objects is written such that instead of requiring a
mutable Rust reference for mutating operations such as
PyList::append
, a shared reference (which, in turn, can only
be created through Python<'_>
with a GIL lifetime) is sufficient.
However, Rust structs wrapped as Python objects (called pyclass
types) usually
do need &mut
access. Due to the GIL, PyO3 can guarantee thread-safe acces
to them, but it cannot statically guarantee uniqueness of &mut
references once
an object's ownership has been passed to the Python interpreter, ensuring
references is done at runtime using PyCell
, a scheme very similar to
std::cell::RefCell
.
Object types
PyAny
Represents: a Python object of unspecified type, restricted to a GIL
lifetime. Currently, PyAny
can only ever occur as a reference, &PyAny
.
Used: Whenever you want to refer to some Python object and will have the
GIL for the whole duration you need to access that object. For example,
intermediate values and arguments to pyfunction
s or pymethod
s implemented
in Rust where any type is allowed.
Many general methods for interacting with Python objects are on the PyAny
struct,
such as getattr
, setattr
, and .call
.
Conversions:
For a &PyAny
object reference any
where the underlying object is a Python-native type such as
a list:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::types::PyList; Python::with_gil(|py| -> PyResult<()> { let obj: &PyAny = PyList::empty(py); // To &PyList with PyAny::downcast let _: &PyList = obj.downcast()?; // To Py<PyAny> (aka PyObject) with .into() let _: Py<PyAny> = obj.into(); // To Py<PyList> with PyAny::extract let _: Py<PyList> = obj.extract()?; Ok(()) }).unwrap(); }
For a &PyAny
object reference any
where the underlying object is a #[pyclass]
:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::{Py, Python, PyAny, PyResult}; #[pyclass] #[derive(Clone)] struct MyClass { } Python::with_gil(|py| -> PyResult<()> { let obj: &PyAny = Py::new(py, MyClass { })?.into_ref(py); // To &PyCell<MyClass> with PyAny::downcast let _: &PyCell<MyClass> = obj.downcast()?; // To Py<PyAny> (aka PyObject) with .into() let _: Py<PyAny> = obj.into(); // To Py<MyClass> with PyAny::extract let _: Py<MyClass> = obj.extract()?; // To MyClass with PyAny::extract, if MyClass: Clone let _: MyClass = obj.extract()?; // To PyRef<MyClass> or PyRefMut<MyClass> with PyAny::extract let _: PyRef<MyClass> = obj.extract()?; let _: PyRefMut<MyClass> = obj.extract()?; Ok(()) }).unwrap(); }
PyTuple
, PyDict
, and many more
Represents: a native Python object of known type, restricted to a GIL
lifetime just like PyAny
.
Used: Whenever you want to operate with native Python types while holding
the GIL. Like PyAny
, this is the most convenient form to use for function
arguments and intermediate values.
These types all implement Deref<Target = PyAny>
, so they all expose the same
methods which can be found on PyAny
.
To see all Python types exposed by PyO3
you should consult the
pyo3::types
module.
Conversions:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::types::PyList; Python::with_gil(|py| -> PyResult<()> { let list = PyList::empty(py); // Use methods from PyAny on all Python types with Deref implementation let _ = list.repr()?; // To &PyAny automatically with Deref implementation let _: &PyAny = list; // To &PyAny explicitly with .as_ref() let _: &PyAny = list.as_ref(); // To Py<T> with .into() or Py::from() let _: Py<PyList> = list.into(); // To PyObject with .into() or .to_object(py) let _: PyObject = list.into(); Ok(()) }).unwrap(); }
Py<T>
and PyObject
Represents: a GIL-independent reference to a Python object. This can be a Python native type
(like PyTuple
), or a pyclass
type implemented in Rust. The most commonly-used variant,
Py<PyAny>
, is also known as PyObject
.
Used: Whenever you want to carry around references to a Python object without caring about a GIL lifetime. For example, storing Python object references in a Rust struct that outlives the Python-Rust FFI boundary, or returning objects from functions implemented in Rust back to Python.
Can be cloned using Python reference counts with .clone()
.
Conversions:
For a Py<PyList>
, the conversions are as below:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::types::PyList; Python::with_gil(|py| { let list: Py<PyList> = PyList::empty(py).into(); // To &PyList with Py::as_ref() (borrows from the Py) let _: &PyList = list.as_ref(py); let list_clone = list.clone(); // Because `.into_ref()` will consume `list`. // To &PyList with Py::into_ref() (moves the pointer into PyO3's object storage) let _: &PyList = list.into_ref(py); let list = list_clone; // To Py<PyAny> (aka PyObject) with .into() let _: Py<PyAny> = list.into(); }) }
For a #[pyclass] struct MyClass
, the conversions for Py<MyClass>
are below:
#![allow(unused)] fn main() { use pyo3::prelude::*; Python::with_gil(|py| { #[pyclass] struct MyClass { } Python::with_gil(|py| -> PyResult<()> { let my_class: Py<MyClass> = Py::new(py, MyClass { })?; // To &PyCell<MyClass> with Py::as_ref() (borrows from the Py) let _: &PyCell<MyClass> = my_class.as_ref(py); let my_class_clone = my_class.clone(); // Because `.into_ref()` will consume `my_class`. // To &PyCell<MyClass> with Py::into_ref() (moves the pointer into PyO3's object storage) let _: &PyCell<MyClass> = my_class.into_ref(py); let my_class = my_class_clone.clone(); // To Py<PyAny> (aka PyObject) with .into_py(py) let _: Py<PyAny> = my_class.into_py(py); let my_class = my_class_clone; // To PyRef<MyClass> with Py::borrow or Py::try_borrow let _: PyRef<MyClass> = my_class.try_borrow(py)?; // To PyRefMut<MyClass> with Py::borrow_mut or Py::try_borrow_mut let _: PyRefMut<MyClass> = my_class.try_borrow_mut(py)?; Ok(()) }).unwrap(); }); }
PyCell<SomeType>
Represents: a reference to a Rust object (instance of PyClass
) which is
wrapped in a Python object. The cell part is an analog to stdlib's
RefCell
to allow access to &mut
references.
Used: for accessing pure-Rust API of the instance (members and functions
taking &SomeType
or &mut SomeType
) while maintaining the aliasing rules of
Rust references.
Like pyo3's Python native types, PyCell<T>
implements Deref<Target = PyAny>
,
so it also exposes all of the methods on PyAny
.
Conversions:
PyCell<T>
can be used to access &T
and &mut T
via PyRef<T>
and PyRefMut<T>
respectively.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct MyClass { } Python::with_gil(|py| -> PyResult<()> { let cell: &PyCell<MyClass> = PyCell::new(py, MyClass { })?; // To PyRef<T> with .borrow() or .try_borrow() let py_ref: PyRef<MyClass> = cell.try_borrow()?; let _: &MyClass = &*py_ref; drop(py_ref); // To PyRefMut<T> with .borrow_mut() or .try_borrow_mut() let mut py_ref_mut: PyRefMut<MyClass> = cell.try_borrow_mut()?; let _: &mut MyClass = &mut *py_ref_mut; Ok(()) }).unwrap(); }
PyCell<T>
can also be accessed like a Python-native type.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct MyClass { } Python::with_gil(|py| -> PyResult<()> { let cell: &PyCell<MyClass> = PyCell::new(py, MyClass { })?; // Use methods from PyAny on PyCell<T> with Deref implementation let _ = cell.repr()?; // To &PyAny automatically with Deref implementation let _: &PyAny = cell; // To &PyAny explicitly with .as_ref() let _: &PyAny = cell.as_ref(); Ok(()) }).unwrap(); }
PyRef<SomeType>
and PyRefMut<SomeType>
Represents: reference wrapper types employed by PyCell
to keep track of
borrows, analog to Ref
and RefMut
used by RefCell
.
Used: while borrowing a PyCell
. They can also be used with .extract()
on types like Py<T>
and PyAny
to get a reference quickly.
Related traits and types
PyClass
This trait marks structs defined in Rust that are also usable as Python classes,
usually defined using the #[pyclass]
macro.
PyNativeType
This trait marks structs that mirror native Python types, such as PyList
.