PyO3 0.20 has increased minimum Rust version to 1.56. This enables use of newer language features and simplifies maintenance of the project.

PyDict::get_item in PyO3 0.19 and older was implemented using a Python API which would suppress all exceptions and return None in those cases. This included errors in __hash__ and __eq__ implementations of the key being looked up.

Newer recommendations by the Python core developers advise against using these APIs which suppress exceptions, instead allowing exceptions to bubble upwards. PyDict::get_item_with_error already implemented this recommended behavior, so that API has been renamed to PyDict::get_item.

Before:

use pyo3::prelude::*;
use pyo3::exceptions::PyTypeError;
use pyo3::types::{PyDict, IntoPyDict};

fn main() {
let _ =
Python::with_gil(|py| {
    let dict: &PyDict = [("a", 1)].into_py_dict(py);
    // `a` is in the dictionary, with value 1
    assert!(dict.get_item("a").map_or(Ok(false), |x| x.eq(1))?);
    // `b` is not in the dictionary
    assert!(dict.get_item("b").is_none());
    // `dict` is not hashable, so this fails with a `TypeError`
    assert!(dict
        .get_item_with_error(dict)
        .unwrap_err()
        .is_instance_of::<PyTypeError>(py));
});
}

After:

use pyo3::prelude::*;
use pyo3::exceptions::PyTypeError;
use pyo3::types::{PyDict, IntoPyDict};

fn main() {
let _ =
Python::with_gil(|py| -> PyResult<()> {
    let dict: &PyDict = [("a", 1)].into_py_dict(py);
    // `a` is in the dictionary, with value 1
    assert!(dict.get_item("a")?.map_or(Ok(false), |x| x.eq(1))?);
    // `b` is not in the dictionary
    assert!(dict.get_item("b")?.is_none());
    // `dict` is not hashable, so this fails with a `TypeError`
    assert!(dict
        .get_item(dict)
        .unwrap_err()
        .is_instance_of::<PyTypeError>(py));

    Ok(())
});
}

Trailing Option<T> arguments have an automatic default of None. To avoid unwanted changes when modifying function signatures, in PyO3 0.18 it was deprecated to have a required argument after an Option<T> argument without using #[pyo3(signature = (...))] to specify the intended defaults. In PyO3 0.20, this becomes a hard error.

Before:

#[pyfunction]
fn x_or_y(x: Option<u64>, y: u64) -> u64 {
    x.unwrap_or(y)
}

After:

#![allow(dead_code)]
use pyo3::prelude::*;

#[pyfunction]
#[pyo3(signature = (x, y))] // both x and y have no defaults and are required
fn x_or_y(x: Option<u64>, y: u64) -> u64 {
    x.unwrap_or(y)
}

In PyO3 0.18 the #[args] attribute for #[pymethods], and directly specifying the function signature in #[pyfunction], was deprecated. This functionality has been removed in PyO3 0.20.

Before:

#[pyfunction]
#[pyo3(a, b = "0", "/")]
fn add(a: u64, b: u64) -> u64 {
    a + b
}

After:

#![allow(dead_code)]
use pyo3::prelude::*;

#[pyfunction]
#[pyo3(signature = (a, b=0, /))]
fn add(a: u64, b: u64) -> u64 {
    a + b
}

The trait IntoPyPointer, which provided the into_ptr method on many types, has been removed. into_ptr is now available as an inherent method on all types that previously implemented this trait.

The trait AsPyPointer is now unsafe trait, meaning any external implementation of it must be marked as unsafe impl, and ensure that they uphold the invariant of returning valid pointers.

During __traverse__ implementations for Python's Garbage Collection it is forbidden to do anything other than visit the members of the #[pyclass] being traversed. This means making Python function calls or other API calls are forbidden.

Previous versions of PyO3 would allow access to Python (e.g. via Python::with_gil), which could cause the Python interpreter to crash or otherwise confuse the garbage collection algorithm.

Attempts to acquire the GIL will now panic. See #3165 for more detail.

use pyo3::prelude::*;

#[pyclass]
struct SomeClass {}

impl SomeClass {
    fn __traverse__(&self, pyo3::class::gc::PyVisit<'_>) -> Result<(), pyo3::class::gc::PyTraverseError>` {
        Python::with_gil(|| { /*...*/ })  // ERROR: this will panic
    }
}

When converting from anyhow::Error or eyre::Report to PyErr, if the inner error is a "simple" PyErr (with no source error), then the inner error will be used directly as the PyErr instead of wrapping it in a new PyRuntimeError with the original information converted into a string.

#[cfg(feature = "anyhow")]
#[allow(dead_code)]
mod anyhow_only {
use pyo3::prelude::*;
use pyo3::exceptions::PyValueError;
#[pyfunction]
fn raise_err() -> anyhow::Result<()> {
    Err(PyValueError::new_err("original error message").into())
}

fn main() {
    Python::with_gil(|py| {
        let rs_func = wrap_pyfunction!(raise_err, py).unwrap();
        pyo3::py_run!(
            py,
            rs_func,
            r"
        try:
            rs_func()
        except Exception as e:
            print(repr(e))
        "
        );
    })
}
}

Before, the above code would have printed RuntimeError('ValueError: original error message'), which might be confusing.

After, the same code will print ValueError: original error message, which is more straightforward.

However, if the anyhow::Error or eyre::Report has a source, then the original exception will still be wrapped in a PyRuntimeError.

While the API provided by Python::acquire_gil seems convenient, it is somewhat brittle as the design of the GIL token Python relies on proper nesting and panics if not used correctly, e.g.

#![allow(dead_code, deprecated)]
use pyo3::prelude::*;

#[pyclass]
struct SomeClass {}

struct ObjectAndGuard {
    object: Py<SomeClass>,
    guard: GILGuard,
}

impl ObjectAndGuard {
    fn new() -> Self {
        let guard = Python::acquire_gil();
        let object = Py::new(guard.python(), SomeClass {}).unwrap();

        Self { object, guard }
    }
}

let first = ObjectAndGuard::new();
let second = ObjectAndGuard::new();
// Panics because the guard within `second` is still alive.
drop(first);
drop(second);

The replacement is Python::with_gil which is more cumbersome but enforces the proper nesting by design, e.g.

#![allow(dead_code)]
use pyo3::prelude::*;

#[pyclass]
struct SomeClass {}

struct Object {
    object: Py<SomeClass>,
}

impl Object {
    fn new(py: Python<'_>) -> Self {
        let object = Py::new(py, SomeClass {}).unwrap();

        Self { object }
    }
}

// It either forces us to release the GIL before aquiring it again.
let first = Python::with_gil(|py| Object::new(py));
let second = Python::with_gil(|py| Object::new(py));
drop(first);
drop(second);

// Or it ensures releasing the inner lock before the outer one.
Python::with_gil(|py| {
    let first = Object::new(py);
    let second = Python::with_gil(|py| Object::new(py));
    drop(first);
    drop(second);
});

Furthermore, Python::acquire_gil provides ownership of a GILGuard which can be freely stored and passed around. This is usually not helpful as it may keep the lock held for a long time thereby blocking progress in other parts of the program. Due to the generative lifetime attached to the GIL token supplied by Python::with_gil, the problem is avoided as the GIL token can only be passed down the call chain. Often, this issue can also be avoided entirely as any GIL-bound reference &'py PyAny implies access to a GIL token Python<'py> via the PyAny::py method.

In #[pyfunction] and #[pymethods], if a "required" function input such as i32 came after an Option<_> input, then the Option<_> would be implicitly treated as required. (All trailing Option<_> arguments were treated as optional with a default value of None).

Starting with PyO3 0.18, this is deprecated and a future PyO3 version will require a #[pyo3(signature = (...))] option to explicitly declare the programmer's intention.

Before, x in the below example would be required to be passed from Python code:

#![allow(dead_code)]
use pyo3::prelude::*;

#[pyfunction]
fn required_argument_after_option(x: Option<i32>, y: i32) {}

After, specify the intended Python signature explicitly:

#![allow(dead_code)]
use pyo3::prelude::*;

// If x really was intended to be required
#[pyfunction(signature = (x, y))]
fn required_argument_after_option_a(x: Option<i32>, y: i32) {}

// If x was intended to be optional, y needs a default too
#[pyfunction(signature = (x=None, y=0))]
fn required_argument_after_option_b(x: Option<i32>, y: i32) {}

The #[pyo3(text_signature = "...")] option was previously the only supported way to set the __text_signature__ attribute on generated Python functions.

PyO3 is now able to automatically populate __text_signature__ for all functions automatically based on their Rust signature (or the new #[pyo3(signature = (...))] option). These automatically-generated __text_signature__ values will currently only render ... for all default values. Many #[pyo3(text_signature = "...")] options can be removed from functions when updating to PyO3 0.18, however in cases with default values a manual implementation may still be preferred for now.

As examples:

use pyo3::prelude::*;

// The `text_signature` option here is no longer necessary, as PyO3 will automatically
// generate exactly the same value.
#[pyfunction(text_signature = "(a, b, c)")]
fn simple_function(a: i32, b: i32, c: i32) {}

// The `text_signature` still provides value here as of PyO3 0.18, because the automatically
// generated signature would be "(a, b=..., c=...)".
#[pyfunction(signature = (a, b = 1, c = 2), text_signature = "(a, b=1, c=2)")]
fn function_with_defaults(a: i32, b: i32, c: i32) {}

fn main() {
    Python::with_gil(|py| {
        let simple = wrap_pyfunction_bound!(simple_function, py).unwrap();
        assert_eq!(simple.getattr("__text_signature__").unwrap().to_string(), "(a, b, c)");
        let defaulted = wrap_pyfunction_bound!(function_with_defaults, py).unwrap();
        assert_eq!(defaulted.getattr("__text_signature__").unwrap().to_string(), "(a, b=1, c=2)");
    })
}

Previously the type checks for PyMapping and PySequence (implemented in PyTryFrom) used the Python C-API functions PyMapping_Check and PySequence_Check. Unfortunately these functions are not sufficient for distinguishing such types, leading to inconsistent behavior (see pyo3/pyo3#2072).

PyO3 0.17 changes these downcast checks to explicitly test if the type is a subclass of the corresponding abstract base class collections.abc.Mapping or collections.abc.Sequence. Note this requires calling into Python, which may incur a performance penalty over the previous method. If this performance penalty is a problem, you may be able to perform your own checks and use try_from_unchecked (unsafe).

Another side-effect is that a pyclass defined in Rust with PyO3 will need to be registered with the corresponding Python abstract base class for downcasting to succeed. PySequence::register and PyMapping:register have been added to make it easy to do this from Rust code. These are equivalent to calling collections.abc.Mapping.register(MappingPyClass) or collections.abc.Sequence.register(SequencePyClass) from Python.

For example, for a mapping class defined in Rust:

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

#[pyclass(mapping)]
struct Mapping {
    index: HashMap<String, usize>,
}

#[pymethods]
impl Mapping {
    #[new]
    fn new(elements: Option<&PyList>) -> PyResult<Self> {
    // ...
    // truncated implementation of this mapping pyclass - basically a wrapper around a HashMap
}

You must register the class with collections.abc.Mapping before the downcast will work:

let m = Py::new(py, Mapping { index }).unwrap();
assert!(m.as_ref(py).downcast::<PyMapping>().is_err());
PyMapping::register::<Mapping>(py).unwrap();
assert!(m.as_ref(py).downcast::<PyMapping>().is_ok());

Note that this requirement may go away in the future when a pyclass is able to inherit from the abstract base class directly (see pyo3/pyo3#991).

Due to limitations in the inventory crate which the multiple-pymethods feature depends on, this feature now requires Rust 1.62. For more information see dtolnay/inventory#32.

This may cause inference errors.

Before:

use pyo3::prelude::*;

fn main() {
Python::with_gil(|py| {
    // Cannot infer either `Py<PyAny>` or `Py<PyString>`
    let _test = "test".into_py(py);
});
}

After, some type annotations may be necessary:

use pyo3::prelude::*;

fn main() {
Python::with_gil(|py| {
    let _test: Py<PyAny> = "test".into_py(py);
});
}

In preparation for removing the deprecated #[pyproto] attribute macro in a future PyO3 version, it is now gated behind an opt-in feature flag. This also gives a slight saving to compile times for code which does not use the deprecated macro.

The PyTypeObject trait already was near-useless; almost all functionality was already on the PyTypeInfo trait, which PyTypeObject had a blanket implementation based upon. In PyO3 0.17 the final method, PyTypeObject::type_object was moved to PyTypeInfo::type_object.

To migrate, update trait bounds and imports from PyTypeObject to PyTypeInfo.

Before:

use pyo3::Python;
use pyo3::type_object::PyTypeObject;
use pyo3::types::PyType;

fn get_type_object<T: PyTypeObject>(py: Python<'_>) -> &PyType {
    T::type_object(py)
}

After

use pyo3::{Python, PyTypeInfo};
use pyo3::types::PyType;

fn get_type_object<T: PyTypeInfo>(py: Python<'_>) -> &PyType {
    T::type_object(py)
}

Python::with_gil(|py| { get_type_object::<pyo3::types::PyList>(py); });

If this leads to errors, simply implement IntoPy. Because pyclasses already implement IntoPy, you probably don't need to worry about this.

To make PyO3 modules sound in the presence of Python sub-interpreters, for now it has been necessary to explicitly disable the ability to initialize a #[pymodule] more than once in the same process. Attempting to do this will now raise an ImportError.

PyO3 0.16 has increased minimum Rust version to 1.48 and minimum Python version to 3.7. This enables use of newer language features (enabling some of the other additions in 0.16) and simplifies maintenance of the project.

In PyO3 0.15, the #[pymethods] attribute macro gained support for implementing "magic methods" such as __str__ (aka "dunder" methods). This implementation was not quite finalized at the time, with a few edge cases to be decided upon. The existing #[pyproto] attribute macro was left untouched, because it covered these edge cases.

In PyO3 0.16, the #[pymethods] implementation has been completed and is now the preferred way to implement magic methods. To allow the PyO3 project to move forward, #[pyproto] has been deprecated (with expected removal in PyO3 0.18).

Migration from #[pyproto] to #[pymethods] is straightforward; copying the existing methods directly from the #[pyproto] trait implementation is all that is needed in most cases.

Before:

use pyo3::prelude::*;
use pyo3::class::{PyObjectProtocol, PyIterProtocol};
use pyo3::types::PyString;

#[pyclass]
struct MyClass {}

#[pyproto]
impl PyObjectProtocol for MyClass {
    fn __str__(&self) -> &'static [u8] {
        b"hello, world"
    }
}

#[pyproto]
impl PyIterProtocol for MyClass {
    fn __iter__(slf: PyRef<self>) -> PyResult<&PyAny> {
        PyString::new(slf.py(), "hello, world").iter()
    }
}

After

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

#[pyclass]
struct MyClass {}

#[pymethods]
impl MyClass {
    fn __str__(&self) -> &'static [u8] {
        b"hello, world"
    }

    fn __iter__(slf: PyRef<self>) -> PyResult<&PyAny> {
        PyString::new(slf.py(), "hello, world").iter()
    }
}

The Python object wrappers Py and PyAny had implementations of PartialEq so that object_a == object_b would compare the Python objects for pointer equality, which corresponds to the is operator, not the == operator in Python. This has been removed in favor of a new method: use object_a.is(object_b). This also has the advantage of not requiring the same wrapper type for object_a and object_b; you can now directly compare a Py<T> with a &PyAny without having to convert.

To check for Python object equality (the Python == operator), use the new method eq().

In PyO3 0.15, __getitem__, __setitem__ and __delitem__ in #[pymethods] would generate only the mapping implementation for a #[pyclass]. To match the Python behavior, these methods now generate both the mapping and sequence implementations.

This means that classes implementing these #[pymethods] will now also be treated as sequences, same as a Python class would be. Small differences in behavior may result:

• PyO3 will allow instances of these classes to be cast to PySequence as well as PyMapping.
• Python will provide a default implementation of __iter__ (if the class did not have one) which repeatedly calls __getitem__ with integers (starting at 0) until an IndexError is raised.

To explain this in detail, consider the following Python class:

class ExampleContainer:

    def __len__(self):
        return 5

    def __getitem__(self, idx: int) -> int:
        if idx < 0 or idx > 5:
            raise IndexError()
        return idx

This class implements a Python sequence.

The __len__ and __getitem__ methods are also used to implement a Python mapping. In the Python C-API, these methods are not shared: the sequence __len__ and __getitem__ are defined by the sq_length and sq_item slots, and the mapping equivalents are mp_length and mp_subscript. There are similar distinctions for __setitem__ and __delitem__.

Because there is no such distinction from Python, implementing these methods will fill the mapping and sequence slots simultaneously. A Python class with __len__ implemented, for example, will have both the sq_length and mp_length slots filled.

The PyO3 behavior in 0.16 has been changed to be closer to this Python behavior by default.

Prior to PyO3 0.16 the wrap_pymodule! and wrap_pyfunction! macros could use modules and functions whose defining fn was not reachable according Rust privacy rules.

For example, the following code was legal before 0.16, but in 0.16 is rejected because the wrap_pymodule! macro cannot access the private_submodule function:

mod foo {
    use pyo3::prelude::*;

    #[pymodule]
    fn private_submodule(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
        Ok(())
    }
}

use pyo3::prelude::*;
use foo::*;

#[pymodule]
fn my_module(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
    m.add_wrapped(wrap_pymodule!(private_submodule))?;
    Ok(())
}

To fix it, make the private submodule visible, e.g. with pub or pub(crate).

mod foo {
    use pyo3::prelude::*;

    #[pymodule]
    pub(crate) fn private_submodule(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
        Ok(())
    }
}

use pyo3::prelude::*;
use pyo3::wrap_pymodule;
use foo::*;

#[pymodule]
fn my_module(_py: Python<'_>, m: &PyModule) -> PyResult<()> {
    m.add_wrapped(wrap_pymodule!(private_submodule))?;
    Ok(())
}

For all types that take sequence indices (PyList, PyTuple and PySequence), the API has been made consistent to only take usize indices, for consistency with Rust's indexing conventions. Negative indices, which were only sporadically supported even in APIs that took isize, now aren't supported anywhere.

Further, the get_item methods now always return a PyResult instead of panicking on invalid indices. The Index trait has been implemented instead, and provides the same panic behavior as on Rust vectors.

Note that slice indices (accepted by PySequence::get_slice and other) still inherit the Python behavior of clamping the indices to the actual length, and not panicking/returning an error on out of range indices.

An additional advantage of using Rust's indexing conventions for these types is that these types can now also support Rust's indexing operators as part of a consistent API:

#![allow(deprecated)]
use pyo3::{Python, types::PyList};

Python::with_gil(|py| {
    let list = PyList::new(py, &[1, 2, 3]);
    assert_eq!(list[0..2].to_string(), "[1, 2]");
});

For projects embedding Python in Rust, PyO3 no longer automatically initializes a Python interpreter on the first call to Python::with_gil (or Python::acquire_gil) unless the auto-initialize feature is enabled.

#[pymethods] have been reworked with a simpler default implementation which removes the dependency on the inventory crate. This reduces dependencies and compile times for the majority of users.

The limitation of the new default implementation is that it cannot support multiple #[pymethods] blocks for the same #[pyclass]. If you need this functionality, you must enable the multiple-pymethods feature which will switch #[pymethods] to the inventory-based implementation.

Some protocol (aka __dunder__) methods such as __bytes__ and __format__ have been possible to implement two ways in PyO3 for some time: via a #[pyproto] (e.g. PyObjectProtocol for the methods listed here), or by writing them directly in #[pymethods]. This is only true for a handful of the #[pyproto] methods (for technical reasons to do with the way PyO3 currently interacts with the Python C-API).

In the interest of having only one way to do things, the #[pyproto] forms of these methods have been deprecated.

To migrate just move the affected methods from a #[pyproto] to a #[pymethods] block.

Before:

use pyo3::prelude::*;
use pyo3::class::basic::PyObjectProtocol;

#[pyclass]
struct MyClass {}

#[pyproto]
impl PyObjectProtocol for MyClass {
    fn __bytes__(&self) -> &'static [u8] {
        b"hello, world"
    }
}

After:

use pyo3::prelude::*;

#[pyclass]
struct MyClass {}

#[pymethods]
impl MyClass {
    fn __bytes__(&self) -> &'static [u8] {
        b"hello, world"
    }
}

PyO3 0.13 makes use of new Rust language features stabilized between Rust 1.40 and Rust 1.45. If you are using a Rust compiler older than Rust 1.45, you will need to update your toolchain to be able to continue using PyO3.

In PyO3 0.13 support was added for compiling against the CPython limited API. This had a number of implications for all PyO3 users, described here.

The largest of these is that all types created from PyO3 are what CPython calls "heap" types. The specific implications of this are:

• If you wish to subclass one of these types from Rust you must mark it #[pyclass(subclass)], as you would if you wished to allow subclassing it from Python code.
• Type objects are now mutable - Python code can set attributes on them.
• __module__ on types without #[pyclass(module="mymodule")] no longer returns builtins, it now raises AttributeError.

In PyO3 0.12 the PyErr type has been re-implemented to be significantly more compatible with the standard Rust error handling ecosystem. Specifically PyErr now implements Error + Send + Sync, which are the standard traits used for error types.

While this has necessitated the removal of a number of APIs, the resulting PyErr type should now be much more easier to work with. The following sections list the changes in detail and how to migrate to the new APIs.

For most uses no change will be needed. If you are trying to construct PyErr from a value that is not Send + Sync, you will need to first create the Python object and then use PyErr::from_instance.

Similarly, any types which implemented PyErrArguments will now need to be Send + Sync.

It is no longer possible to access the fields .ptype, .pvalue and .ptraceback of a PyErr. You should instead now use the new methods PyErr::ptype, PyErr::pvalue and PyErr::ptraceback.

As these were part the internals of PyErr which have been reworked, these APIs no longer exist.

If you used this API, it is recommended to use PyException::new_err (see the section on Exception types).

This implementation was redundant. Just construct the Result::Err variant directly.

Before:

let result: PyResult<()> = PyErr::new::<TypeError, _>("error message").into();

After (also using the new reworked exception types; see the following section):

use pyo3::{PyResult, exceptions::PyTypeError};
let result: PyResult<()> = Err(PyTypeError::new_err("error message"));

Previously exception types were zero-sized marker types purely used to construct PyErr. In PyO3 0.12, these types have been replaced with full definitions and are usable in the same way as PyAny, PyDict etc. This makes it possible to interact with Python exception objects.

The new types also have names starting with the "Py" prefix. For example, before:

let err: PyErr = TypeError::py_err("error message");

After:

use pyo3::{PyErr, PyResult, Python, type_object::PyTypeObject};
use pyo3::exceptions::{PyBaseException, PyTypeError};
Python::with_gil(|py| -> PyResult<()> {
let err: PyErr = PyTypeError::new_err("error message");

// Uses Display for PyErr, new for PyO3 0.12
assert_eq!(err.to_string(), "TypeError: error message");

// Now possible to interact with exception instances, new for PyO3 0.12
let instance: &PyBaseException = err.instance(py);
assert_eq!(
    instance.getattr("__class__")?,
    PyTypeError::type_object(py).as_ref()
);
Ok(())
}).unwrap();

To simplify the PyO3 conversion traits, the FromPy trait has been removed. Previously there were two ways to define the to-Python conversion for a type: FromPy<T> for PyObject and IntoPy<PyObject> for T.

Now there is only one way to define the conversion, IntoPy, so downstream crates may need to adjust accordingly.

Before:

use pyo3::prelude::*;
struct MyPyObjectWrapper(PyObject);

impl FromPy<MyPyObjectWrapper> for PyObject {
    fn from_py(other: MyPyObjectWrapper, _py: Python<'_>) -> Self {
        other.0
    }
}

After

use pyo3::prelude::*;
#[allow(dead_code)]
struct MyPyObjectWrapper(PyObject);

impl IntoPy<PyObject> for MyPyObjectWrapper {
    fn into_py(self, _py: Python<'_>) -> PyObject {
        self.0
    }
}

Similarly, code which was using the FromPy trait can be trivially rewritten to use IntoPy.

Before:

use pyo3::prelude::*;
Python::with_gil(|py| {
let obj = PyObject::from_py(1.234, py);
})

After:

use pyo3::prelude::*;
Python::with_gil(|py| {
let obj: PyObject = 1.234.into_py(py);
})

This should change very little from a usage perspective. If you implemented traits for both PyObject and Py<T>, you may find you can just remove the PyObject implementation.

As PyObject has been changed to be just a type alias, the only remaining implementor of AsPyRef was Py<T>. This removed the need for a trait, so the AsPyRef::as_ref method has been moved to Py::as_ref.

This should require no code changes except removing use pyo3::AsPyRef for code which did not use pyo3::prelude::*.

Before:

use pyo3::{AsPyRef, Py, types::PyList};
pyo3::Python::with_gil(|py| {
let list_py: Py<PyList> = PyList::empty(py).into();
let list_ref: &PyList = list_py.as_ref(py);
})

After:

use pyo3::{Py, types::PyList};
pyo3::Python::with_gil(|py| {
let list_py: Py<PyList> = PyList::empty(py).into();
let list_ref: &PyList = list_py.as_ref(py);
})

PyO3 now supports the stable Rust toolchain. The minimum required version is 1.39.0.

Because #[pyclass] structs can be sent between threads by the Python interpreter, they must implement Send or declared as unsendable (by #[pyclass(unsendable)]). Note that unsendable is added in PyO3 0.11.1 and Send is always required in PyO3 0.11.0.

This may "break" some code which previously was accepted, even though it could be unsound. There can be two fixes:

1. If you think that your #[pyclass] actually must be Sendable, then let's implement Send. A common, safer way is using thread-safe types. E.g., Arc instead of Rc, Mutex instead of RefCell, and Box<dyn Send + T> instead of Box<dyn T>.

   Before:

   use pyo3::prelude::*;
   use std::rc::Rc;
   use std::cell::RefCell;
   
   #[pyclass]
   struct NotThreadSafe {
       shared_bools: Rc<RefCell<Vec<bool>>>,
       closure: Box<dyn Fn()>,
   }

   After:

   #![allow(dead_code)]
   use pyo3::prelude::*;
   use std::sync::{Arc, Mutex};
   
   #[pyclass]
   struct ThreadSafe {
       shared_bools: Arc<Mutex<Vec<bool>>>,
       closure: Box<dyn Fn() + Send>,
   }

   In situations where you cannot change your #[pyclass] to automatically implement Send (e.g., when it contains a raw pointer), you can use unsafe impl Send. In such cases, care should be taken to ensure the struct is actually thread safe. See the Rustonomicon for more.

2. If you think that your #[pyclass] should not be accessed by another thread, you can use unsendable flag. A class marked with unsendable panics when accessed by another thread, making it thread-safe to expose an unsendable object to the Python interpreter.

   Before:

   use pyo3::prelude::*;
   
   #[pyclass]
   struct Unsendable {
       pointers: Vec<*mut std::os::raw::c_char>,
   }

   After:

   #![allow(dead_code)]
   use pyo3::prelude::*;
   
   #[pyclass(unsendable)]
   struct Unsendable {
       pointers: Vec<*mut std::os::raw::c_char>,
   }

Previously, a few methods such as Object::get_refcnt did not take Python as an argument (to ensure that the Python GIL was held by the current thread). Technically, this was not sound. To migrate, just pass a py argument to any calls to these methods.

Before:

pyo3::Python::with_gil(|py| {
py.None().get_refcnt();
})

After:

pyo3::Python::with_gil(|py| {
py.None().get_refcnt(py);
})

All methods are moved to PyAny. And since now all native types (e.g., PyList) implements Deref<Target=PyAny>, all you need to do is remove ObjectProtocol from your code. Or if you use ObjectProtocol by use pyo3::prelude::*, you have to do nothing.

Before:

use pyo3::ObjectProtocol;

pyo3::Python::with_gil(|py| {
let obj = py.eval("lambda: 'Hi :)'", None, None).unwrap();
let hi: &pyo3::types::PyString = obj.call0().unwrap().downcast().unwrap();
assert_eq!(hi.len().unwrap(), 5);
})

After:

pyo3::Python::with_gil(|py| {
let obj = py.eval("lambda: 'Hi :)'", None, None).unwrap();
let hi: &pyo3::types::PyString = obj.call0().unwrap().downcast().unwrap();
assert_eq!(hi.len().unwrap(), 5);
})

While PyO3 itself still requires specialization and nightly Rust, now you don't have to use #![feature(specialization)] in your crate.

PyRawObject is now removed and our syntax for constructors has changed.

Before:

#[pyclass]
struct MyClass {}

#[pymethods]
impl MyClass {
    #[new]
    fn new(obj: &PyRawObject) {
        obj.init(MyClass {})
    }
}

After:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {}

#[pymethods]
impl MyClass {
    #[new]
    fn new() -> Self {
        MyClass {}
    }
}

Basically you can return Self or Result<Self> directly. For more, see the constructor section of this guide.

PyO3 0.9 introduces PyCell, which is a RefCell-like object wrapper for ensuring Rust's rules regarding aliasing of references are upheld. For more detail, see the Rust Book's section on Rust's rules of references

For #[pymethods] or #[pyfunction]s, your existing code should continue to work without any change. Python exceptions will automatically be raised when your functions are used in a way which breaks Rust's rules of references.

Here is an example.

use pyo3::prelude::*;

#[pyclass]
struct Names {
    names: Vec<String>,
}

#[pymethods]
impl Names {
    #[new]
    fn new() -> Self {
        Names { names: vec![] }
    }
    fn merge(&mut self, other: &mut Names) {
        self.names.append(&mut other.names)
    }
}
Python::with_gil(|py| {
    let names = Py::new(py, Names::new()).unwrap();
    pyo3::py_run!(py, names, r"
    try:
       names.merge(names)
       assert False, 'Unreachable'
    except RuntimeError as e:
       assert str(e) == 'Already borrowed'
    ");
})

Names has a merge method, which takes &mut self and another argument of type &mut Self. Given this #[pyclass], calling names.merge(names) in Python raises a PyBorrowMutError exception, since it requires two mutable borrows of names.

However, for #[pyproto] and some functions, you need to manually fix the code.

Object creation

In 0.8 object creation was done with PyRef::new and PyRefMut::new. In 0.9 these have both been removed. To upgrade code, please use PyCell::new instead. If you need PyRef or PyRefMut, just call .borrow() or .borrow_mut() on the newly-created PyCell.

Before:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {}
Python::with_gil(|py| {
let obj_ref = PyRef::new(py, MyClass {}).unwrap();
})

After:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {}
Python::with_gil(|py| {
let obj = PyCell::new(py, MyClass {}).unwrap();
let obj_ref = obj.borrow();
})

Object extraction

For PyClass types T, &T and &mut T no longer have FromPyObject implementations. Instead you should extract PyRef<T> or PyRefMut<T>, respectively. If T implements Clone, you can extract T itself. In addition, you can also extract &PyCell<T>, though you rarely need it.

Before:

let obj: &PyAny = create_obj();
let obj_ref: &MyClass = obj.extract().unwrap();
let obj_ref_mut: &mut MyClass = obj.extract().unwrap();

After:

use pyo3::prelude::*;
use pyo3::types::IntoPyDict;
#[pyclass] #[derive(Clone)] struct MyClass {}
#[pymethods] impl MyClass { #[new]fn new() -> Self { MyClass {} }}
Python::with_gil(|py| {
let typeobj = py.get_type::<MyClass>();
let d = [("c", typeobj)].into_py_dict(py);
let create_obj = || py.eval("c()", None, Some(d)).unwrap();
let obj: &PyAny = create_obj();
let obj_cell: &PyCell<MyClass> = obj.extract().unwrap();
let obj_cloned: MyClass = obj.extract().unwrap(); // extracted by cloning the object
{
    let obj_ref: PyRef<'_, MyClass> = obj.extract().unwrap();
    // we need to drop obj_ref before we can extract a PyRefMut due to Rust's rules of references
}
let obj_ref_mut: PyRefMut<'_, MyClass> = obj.extract().unwrap();
})

#[pyproto]

Most of the arguments to methods in #[pyproto] impls require a FromPyObject implementation. So if your protocol methods take &T or &mut T (where T: PyClass), please use PyRef or PyRefMut instead.

Before:

use pyo3::prelude::*;
use pyo3::class::PySequenceProtocol;
#[pyclass]
struct ByteSequence {
    elements: Vec<u8>,
}
#[pyproto]
impl PySequenceProtocol for ByteSequence {
    fn __concat__(&self, other: &Self) -> PyResult<Self> {
        let mut elements = self.elements.clone();
        elements.extend_from_slice(&other.elements);
        Ok(Self { elements })
    }
}

After:

use pyo3::prelude::*;
use pyo3::class::PySequenceProtocol;
#[pyclass]
struct ByteSequence {
    elements: Vec<u8>,
}
#[pyproto]
impl PySequenceProtocol for ByteSequence {
    fn __concat__(&self, other: PyRef<'p, Self>) -> PyResult<Self> {
        let mut elements = self.elements.clone();
        elements.extend_from_slice(&other.elements);
        Ok(Self { elements })
    }
}