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 PyObject::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

PyObject

Represents: a GIL independent reference to a Python object of unspecified type.

Used: Whenever you want to carry around references to "some" 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_ref().

Conversions:

  • To &PyAny: obj.as_ref(py)
  • To Py<ConcreteType>: obj.as_ref(py).extract::<Py<ConcreteType>>
  • To &ConcreteType (which must be a Python native type): obj.cast_as(py)

Py<SomeType>

Represents: a GIL independent reference to a Python object of known type. This can be a Python native type (like PyTuple), or a pyclass type implemented in Rust.

Used: Like PyObject, but with a known inner type.

Conversions:

  • To PyObject: obj.to_object(py)
  • To &SomeType or &PyCell<SomeType>: obj.as_ref(py). For pyclass types implemented in Rust, you get a PyCell (see below). For Python native types, mutating operations through PyO3's API don't require &mut access.

Note: PyObject is semantically equivalent to Py<PyAny> and might be merged with it in the future.

PyAny

Represents: a Python object of unspecified type, restricted to a GIL lifetime. Currently, PyAny can only ever occur as a reference, usually &PyAny.

Used: Whenever you want to refer to some Python object only as long as holding the GIL. For example, intermediate values and arguments to pyfunctions or pymethods implemented in Rust where any type is allowed.

Conversions:

  • To PyObject: obj.to_object(py)

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.

Conversions:

  • To PyAny: obj.as_ref()
  • To Py<T>: Py::from(obj)

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.

Conversions:

  • From PyAny: .downcast()

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.