Python classes

PyO3 exposes a group of attributes powered by Rust's proc macro system for defining Python classes as Rust structs.

The main attribute is #[pyclass], which is placed upon a Rust struct or enum to generate a Python type for it. They will usually also have one #[pymethods]-annotated impl block for the struct, which is used to define Python methods and constants for the generated Python type. (If the multiple-pymethods feature is enabled, each #[pyclass] is allowed to have multiple #[pymethods] blocks.) #[pymethods] may also have implementations for Python magic methods such as __str__.

This chapter will discuss the functionality and configuration these attributes offer. Below is a list of links to the relevant section of this chapter for each:

#[pyclass]
- #[pyo3(get, set)]
#[pymethods]
Magic methods and slots
Classes as function arguments

Defining a new class

To define a custom Python class, add the #[pyclass] attribute to a Rust struct or enum.

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

#[pyclass]
struct MyClass {
    inner: i32,
}

// A "tuple" struct
#[pyclass]
struct Number(i32);

// PyO3 supports unit-only enums (which contain only unit variants)
// These simple enums behave similarly to Python's enumerations (enum.Enum)
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum MyEnum {
    Variant,
    OtherVariant = 30, // PyO3 supports custom discriminants.
}

// PyO3 supports custom discriminants in unit-only enums
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum HttpResponse {
    Ok = 200,
    NotFound = 404,
    Teapot = 418,
    // ...
}

// PyO3 also supports enums with Struct and Tuple variants
// These complex enums have sligtly different behavior from the simple enums above
// They are meant to work with instance checks and match statement patterns
// The variants can be mixed and matched
// Struct variants have named fields while tuple enums generate generic names for fields in order _0, _1, _2, ...
// Apart from this both types are functionally identical
#[pyclass]
enum Shape {
    Circle { radius: f64 },
    Rectangle { width: f64, height: f64 },
    RegularPolygon(u32, f64),
    Nothing(),
}

The above example generates implementations for PyTypeInfo and PyClass for MyClass, Number, MyEnum, HttpResponse, and Shape. To see these generated implementations, refer to the implementation details at the end of this chapter.

Restrictions

To integrate Rust types with Python, PyO3 needs to place some restrictions on the types which can be annotated with #[pyclass]. In particular, they must have no lifetime parameters, no generic parameters, and must be thread-safe. The reason for each of these is explained below.

No lifetime parameters

Rust lifetimes are used by the Rust compiler to reason about a program's memory safety. They are a compile-time only concept; there is no way to access Rust lifetimes at runtime from a dynamic language like Python.

As soon as Rust data is exposed to Python, there is no guarantee that the Rust compiler can make on how long the data will live. Python is a reference-counted language and those references can be held for an arbitrarily long time which is untraceable by the Rust compiler. The only possible way to express this correctly is to require that any #[pyclass] does not borrow data for any lifetime shorter than the 'static lifetime, i.e. the #[pyclass] cannot have any lifetime parameters.

When you need to share ownership of data between Python and Rust, instead of using borrowed references with lifetimes consider using reference-counted smart pointers such as Arc or Py.

No generic parameters

A Rust struct Foo<T> with a generic parameter T generates new compiled implementations each time it is used with a different concrete type for T. These new implementations are generated by the compiler at each usage site. This is incompatible with wrapping Foo in Python, where there needs to be a single compiled implementation of Foo which is integrated with the Python interpreter.

Currently, the best alternative is to write a macro which expands to a new #[pyclass] for each instantiation you want:

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

struct GenericClass<T> {
    data: T,
}

macro_rules! create_interface {
    ($name: ident, $type: ident) => {
        #[pyclass]
        pub struct $name {
            inner: GenericClass<$type>,
        }
        #[pymethods]
        impl $name {
            #[new]
            pub fn new(data: $type) -> Self {
                Self {
                    inner: GenericClass { data: data },
                }
            }
        }
    };
}

create_interface!(IntClass, i64);
create_interface!(FloatClass, String);

Must be thread-safe

Python objects are freely shared between threads by the Python interpreter. This means that:

Python objects may be created and destroyed by different Python threads; therefore #[pyclass]objects must beSend`.
Python objects may be accessed by multiple python threads simultaneously; therefore #[pyclass] objects must be Sync.

For now, don't worry about these requirements; simple classes will already be thread-safe. There is a detailed discussion on thread-safety later in the guide.

Constructor

By default, it is not possible to create an instance of a custom class from Python code. To declare a constructor, you need to define a method and annotate it with the #[new] attribute. Only Python's __new__ method can be specified, __init__ is not available.

#![allow(dead_code)]
use pyo3::prelude::*;
#[pyclass]
struct Number(i32);

#[pymethods]
impl Number {
    #[new]
    fn new(value: i32) -> Self {
        Number(value)
    }
}

Alternatively, if your new method may fail you can return PyResult<Self>.

#![allow(dead_code)]
use pyo3::prelude::*;
use pyo3::exceptions::PyValueError;
#[pyclass]
struct Nonzero(i32);

#[pymethods]
impl Nonzero {
    #[new]
    fn py_new(value: i32) -> PyResult<Self> {
        if value == 0 {
            Err(PyValueError::new_err("cannot be zero"))
        } else {
            Ok(Nonzero(value))
        }
    }
}

If you want to return an existing object (for example, because your new method caches the values it returns), new can return pyo3::Py<Self>.

As you can see, the Rust method name is not important here; this way you can still, use new() for a Rust-level constructor.

If no method marked with #[new] is declared, object instances can only be created from Rust, but not from Python.

For arguments, see the Method arguments section below.

Adding the class to a module

The next step is to create the module initializer and add our class to it:

#![allow(dead_code)]
use pyo3::prelude::*;
#[pyclass]
struct Number(i32);

#[pymodule]
fn my_module(m: &Bound<'_, PyModule>) -> PyResult<()> {
    m.add_class::<Number>()?;
    Ok(())
}

Bound and interior mutability

Often is useful to turn a #[pyclass] type T into a Python object and access it from Rust code. The [Py<T>] and [Bound<'py, T>] smart pointers are the ways to represent a Python object in PyO3's API. More detail can be found about them in the Python objects section of the guide.

Most Python objects do not offer exclusive (&mut) access (see the section on Python's memory model). However, Rust structs wrapped as Python objects (called pyclass types) often do need &mut access. Due to the GIL, PyO3 can guarantee exclusive access to them.

The Rust borrow checker cannot reason about &mut references once an object's ownership has been passed to the Python interpreter. This means that borrow checking is done at runtime using with a scheme very similar to std::cell::RefCell<T>. This is known as interior mutability.

Users who are familiar with RefCell<T> can use Py<T> and Bound<'py, T> just like RefCell<T>.

For users who are not very familiar with RefCell<T>, here is a reminder of Rust's rules of borrowing:

At any given time, you can have either (but not both of) one mutable reference or any number of immutable references.
References can never outlast the data they refer to.

Py<T> and Bound<'py, T>, like RefCell<T>, ensure these borrowing rules by tracking references at runtime.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    #[pyo3(get)]
    num: i32,
}
Python::with_gil(|py| {
    let obj = Bound::new(py, MyClass { num: 3 }).unwrap();
    {
        let obj_ref = obj.borrow(); // Get PyRef
        assert_eq!(obj_ref.num, 3);
        // You cannot get PyRefMut unless all PyRefs are dropped
        assert!(obj.try_borrow_mut().is_err());
    }
    {
        let mut obj_mut = obj.borrow_mut(); // Get PyRefMut
        obj_mut.num = 5;
        // You cannot get any other refs until the PyRefMut is dropped
        assert!(obj.try_borrow().is_err());
        assert!(obj.try_borrow_mut().is_err());
    }

    // You can convert `Bound` to a Python object
    pyo3::py_run!(py, obj, "assert obj.num == 5");
});

A Bound<'py, T> is restricted to the GIL lifetime 'py. To make the object longer lived (for example, to store it in a struct on the Rust side), use Py<T>. Py<T> needs a Python<'_> token to allow access:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    num: i32,
}

fn return_myclass() -> Py<MyClass> {
    Python::with_gil(|py| Py::new(py, MyClass { num: 1 }).unwrap())
}

let obj = return_myclass();

Python::with_gil(move |py| {
    let bound = obj.bind(py); // Py<MyClass>::bind returns &Bound<'py, MyClass>
    let obj_ref = bound.borrow(); // Get PyRef<T>
    assert_eq!(obj_ref.num, 1);
});

frozen classes: Opting out of interior mutability

As detailed above, runtime borrow checking is currently enabled by default. But a class can opt of out it by declaring itself frozen. It can still use interior mutability via standard Rust types like RefCell or Mutex, but it is not bound to the implementation provided by PyO3 and can choose the most appropriate strategy on field-by-field basis.

Classes which are frozen and also Sync, e.g. they do use Mutex but not RefCell, can be accessed without needing the Python GIL via the Bound::get and Py::get methods:

use std::sync::atomic::{AtomicUsize, Ordering};
use pyo3::prelude::*;

#[pyclass(frozen)]
struct FrozenCounter {
    value: AtomicUsize,
}

let py_counter: Py<FrozenCounter> = Python::with_gil(|py| {
    let counter = FrozenCounter {
        value: AtomicUsize::new(0),
    };

    Py::new(py, counter).unwrap()
});

py_counter.get().value.fetch_add(1, Ordering::Relaxed);

Python::with_gil(move |_py| drop(py_counter));

Frozen classes are likely to become the default thereby guiding the PyO3 ecosystem towards a more deliberate application of interior mutability. Eventually, this should enable further optimizations of PyO3's internals and avoid downstream code paying the cost of interior mutability when it is not actually required.

Customizing the class

#[pyclass] can be used with the following parameters:

Parameter	Description
`constructor`	This is currently only allowed on variants of complex enums. It allows customization of the generated class constructor for each variant. It uses the same syntax and supports the same options as the `signature` attribute of functions and methods.
`crate = "some::path"`	Path to import the `pyo3` crate, if it's not accessible at `::pyo3`.
`dict`	Gives instances of this class an empty `__dict__` to store custom attributes.
`eq`	Implements `__eq__` using the `PartialEq` implementation of the underlying Rust datatype.
`eq_int`	Implements `__eq__` using `__int__` for simple enums.
`extends = BaseType`	Use a custom baseclass. Defaults to `PyAny`
`freelist = N`	Implements a free list of size N. This can improve performance for types that are often created and deleted in quick succession. Profile your code to see whether `freelist` is right for you.
`frozen`	Declares that your pyclass is immutable. It removes the borrow checker overhead when retrieving a shared reference to the Rust struct, but disables the ability to get a mutable reference.
`get_all`	Generates getters for all fields of the pyclass.
`hash`	Implements `__hash__` using the `Hash` implementation of the underlying Rust datatype.
`mapping`	Inform PyO3 that this class is a `Mapping`, and so leave its implementation of sequence C-API slots empty.
`module = "module_name"`	Python code will see the class as being defined in this module. Defaults to `builtins`.
`name = "python_name"`	Sets the name that Python sees this class as. Defaults to the name of the Rust struct.
`ord`	Implements `__lt__`, `__gt__`, `__le__`, & `__ge__` using the `PartialOrd` implementation of the underlying Rust datatype. Requires `eq`
`rename_all = "renaming_rule"`	Applies renaming rules to every getters and setters of a struct, or every variants of an enum. Possible values are: "camelCase", "kebab-case", "lowercase", "PascalCase", "SCREAMING-KEBAB-CASE", "SCREAMING_SNAKE_CASE", "snake_case", "UPPERCASE".
`sequence`	Inform PyO3 that this class is a `Sequence`, and so leave its C-API mapping length slot empty.
`set_all`	Generates setters for all fields of the pyclass.
`str`	Implements `__str__` using the `Display` implementation of the underlying Rust datatype or by passing an optional format string `str="<format string>"`. Note: The optional format string is only allowed for structs. `name` and `rename_all` are incompatible with the optional format string. Additional details can be found in the discussion on this PR.
`subclass`	Allows other Python classes and `#[pyclass]` to inherit from this class. Enums cannot be subclassed.
`unsendable`	Required if your struct is not `Send`. Rather than using `unsendable`, consider implementing your struct in a thread-safe way by e.g. substituting `Rc` with `Arc`. By using `unsendable`, your class will panic when accessed by another thread. Also note the Python's GC is multi-threaded and while unsendable classes will not be traversed on foreign threads to avoid UB, this can lead to memory leaks.
`weakref`	Allows this class to be weakly referenceable.

All of these parameters can either be passed directly on the #[pyclass(...)] annotation, or as one or more accompanying #[pyo3(...)] annotations, e.g.:

// Argument supplied directly to the `#[pyclass]` annotation.
#[pyclass(name = "SomeName", subclass)]
struct MyClass {}

// Argument supplied as a separate annotation.
#[pyclass]
#[pyo3(name = "SomeName", subclass)]
struct MyClass {}

These parameters are covered in various sections of this guide.

Return type

Generally, #[new] methods have to return T: Into<PyClassInitializer<Self>> or PyResult<T> where T: Into<PyClassInitializer<Self>>.

For constructors that may fail, you should wrap the return type in a PyResult as well. Consult the table below to determine which type your constructor should return:

	Cannot fail	May fail
No inheritance	`T`	`PyResult<T>`
Inheritance(T Inherits U)	`(T, U)`	`PyResult<(T, U)>`
Inheritance(General Case)	`PyClassInitializer<T>`	`PyResult<PyClassInitializer<T>>`

Inheritance

By default, object, i.e. PyAny is used as the base class. To override this default, use the extends parameter for pyclass with the full path to the base class. Currently, only classes defined in Rust and builtins provided by PyO3 can be inherited from; inheriting from other classes defined in Python is not yet supported (#991).

For convenience, (T, U) implements Into<PyClassInitializer<T>> where U is the base class of T. But for a more deeply nested inheritance, you have to return PyClassInitializer<T> explicitly.

To get a parent class from a child, use PyRef instead of &self for methods, or PyRefMut instead of &mut self. Then you can access a parent class by self_.as_super() as &PyRef<Self::BaseClass>, or by self_.into_super() as PyRef<Self::BaseClass> (and similar for the PyRefMut case). For convenience, self_.as_ref() can also be used to get &Self::BaseClass directly; however, this approach does not let you access base classes higher in the inheritance hierarchy, for which you would need to chain multiple as_super or into_super calls.

use pyo3::prelude::*;

#[pyclass(subclass)]
struct BaseClass {
    val1: usize,
}

#[pymethods]
impl BaseClass {
    #[new]
    fn new() -> Self {
        BaseClass { val1: 10 }
    }

    pub fn method1(&self) -> PyResult<usize> {
        Ok(self.val1)
    }
}

#[pyclass(extends=BaseClass, subclass)]
struct SubClass {
    val2: usize,
}

#[pymethods]
impl SubClass {
    #[new]
    fn new() -> (Self, BaseClass) {
        (SubClass { val2: 15 }, BaseClass::new())
    }

    fn method2(self_: PyRef<'_, Self>) -> PyResult<usize> {
        let super_ = self_.as_super(); // Get &PyRef<BaseClass>
        super_.method1().map(|x| x * self_.val2)
    }
}

#[pyclass(extends=SubClass)]
struct SubSubClass {
    val3: usize,
}

#[pymethods]
impl SubSubClass {
    #[new]
    fn new() -> PyClassInitializer<Self> {
        PyClassInitializer::from(SubClass::new()).add_subclass(SubSubClass { val3: 20 })
    }

    fn method3(self_: PyRef<'_, Self>) -> PyResult<usize> {
        let base = self_.as_super().as_super(); // Get &PyRef<'_, BaseClass>
        base.method1().map(|x| x * self_.val3)
    }

    fn method4(self_: PyRef<'_, Self>) -> PyResult<usize> {
        let v = self_.val3;
        let super_ = self_.into_super(); // Get PyRef<'_, SubClass>
        SubClass::method2(super_).map(|x| x * v)
    }

      fn get_values(self_: PyRef<'_, Self>) -> (usize, usize, usize) {
          let val1 = self_.as_super().as_super().val1;
          let val2 = self_.as_super().val2;
          (val1, val2, self_.val3)
      }

    fn double_values(mut self_: PyRefMut<'_, Self>) {
        self_.as_super().as_super().val1 *= 2;
        self_.as_super().val2 *= 2;
        self_.val3 *= 2;
    }

    #[staticmethod]
    fn factory_method(py: Python<'_>, val: usize) -> PyResult<PyObject> {
        let base = PyClassInitializer::from(BaseClass::new());
        let sub = base.add_subclass(SubClass { val2: val });
        if val % 2 == 0 {
            Ok(Py::new(py, sub)?.into_any())
        } else {
            let sub_sub = sub.add_subclass(SubSubClass { val3: val });
            Ok(Py::new(py, sub_sub)?.into_any())
        }
    }
}
Python::with_gil(|py| {
    let subsub = pyo3::Py::new(py, SubSubClass::new()).unwrap();
    pyo3::py_run!(py, subsub, "assert subsub.method1() == 10");
    pyo3::py_run!(py, subsub, "assert subsub.method2() == 150");
    pyo3::py_run!(py, subsub, "assert subsub.method3() == 200");
    pyo3::py_run!(py, subsub, "assert subsub.method4() == 3000");
    pyo3::py_run!(py, subsub, "assert subsub.get_values() == (10, 15, 20)");
    pyo3::py_run!(py, subsub, "assert subsub.double_values() == None");
    pyo3::py_run!(py, subsub, "assert subsub.get_values() == (20, 30, 40)");
    let subsub = SubSubClass::factory_method(py, 2).unwrap();
    let subsubsub = SubSubClass::factory_method(py, 3).unwrap();
    let cls = py.get_type::<SubSubClass>();
    pyo3::py_run!(py, subsub cls, "assert not isinstance(subsub, cls)");
    pyo3::py_run!(py, subsubsub cls, "assert isinstance(subsubsub, cls)");
});

You can inherit native types such as PyDict, if they implement PySizedLayout. This is not supported when building for the Python limited API (aka the abi3 feature of PyO3).

To convert between the Rust type and its native base class, you can take slf as a Python object. To access the Rust fields use slf.borrow() or slf.borrow_mut(), and to access the base class use slf.downcast::<BaseClass>().

#[cfg(not(Py_LIMITED_API))] {
use pyo3::prelude::*;
use pyo3::types::PyDict;
use std::collections::HashMap;

#[pyclass(extends=PyDict)]
#[derive(Default)]
struct DictWithCounter {
    counter: HashMap<String, usize>,
}

#[pymethods]
impl DictWithCounter {
    #[new]
    fn new() -> Self {
        Self::default()
    }

    fn set(slf: &Bound<'_, Self>, key: String, value: Bound<'_, PyAny>) -> PyResult<()> {
        slf.borrow_mut().counter.entry(key.clone()).or_insert(0);
        let dict = slf.downcast::<PyDict>()?;
        dict.set_item(key, value)
    }
}
Python::with_gil(|py| {
    let cnt = pyo3::Py::new(py, DictWithCounter::new()).unwrap();
    pyo3::py_run!(py, cnt, "cnt.set('abc', 10); assert cnt['abc'] == 10")
});
}

If SubClass does not provide a base class initialization, the compilation fails.

use pyo3::prelude::*;

#[pyclass]
struct BaseClass {
    val1: usize,
}

#[pyclass(extends=BaseClass)]
struct SubClass {
    val2: usize,
}

#[pymethods]
impl SubClass {
    #[new]
    fn new() -> Self {
        SubClass { val2: 15 }
    }
}

The __new__ constructor of a native base class is called implicitly when creating a new instance from Python. Be sure to accept arguments in the #[new] method that you want the base class to get, even if they are not used in that fn:

#[allow(dead_code)]
#[cfg(not(Py_LIMITED_API))] {
use pyo3::prelude::*;
use pyo3::types::PyDict;

#[pyclass(extends=PyDict)]
struct MyDict {
    private: i32,
}

#[pymethods]
impl MyDict {
    #[new]
    #[pyo3(signature = (*args, **kwargs))]
    fn new(args: &Bound<'_, PyAny>, kwargs: Option<&Bound<'_, PyAny>>) -> Self {
        Self { private: 0 }
    }

    // some custom methods that use `private` here...
}
Python::with_gil(|py| {
    let cls = py.get_type::<MyDict>();
    pyo3::py_run!(py, cls, "cls(a=1, b=2)")
});
}

Here, the args and kwargs allow creating instances of the subclass passing initial items, such as MyDict(item_sequence) or MyDict(a=1, b=2).

Object properties

PyO3 supports two ways to add properties to your #[pyclass]:

For simple struct fields with no side effects, a #[pyo3(get, set)] attribute can be added directly to the field definition in the #[pyclass].
For properties which require computation you can define #[getter] and #[setter] functions in the #[pymethods] block.

We'll cover each of these in the following sections.

Object properties using `#[pyo3(get, set)]`

For simple cases where a member variable is just read and written with no side effects, you can declare getters and setters in your #[pyclass] field definition using the pyo3 attribute, like in the example below:

use pyo3::prelude::*;
#[allow(dead_code)]
#[pyclass]
struct MyClass {
    #[pyo3(get, set)]
    num: i32,
}

The above would make the num field available for reading and writing as a self.num Python property. To expose the property with a different name to the field, specify this alongside the rest of the options, e.g. #[pyo3(get, set, name = "custom_name")].

Properties can be readonly or writeonly by using just #[pyo3(get)] or #[pyo3(set)] respectively.

To use these annotations, your field type must implement some conversion traits:

For get the field type must implement both IntoPy<PyObject> and Clone.
For set the field type must implement FromPyObject.

For example, implementations of those traits are provided for the Cell type, if the inner type also implements the trait. This means you can use #[pyo3(get, set)] on fields wrapped in a Cell.

Object properties using `#[getter]` and `#[setter]`

For cases which don't satisfy the #[pyo3(get, set)] trait requirements, or need side effects, descriptor methods can be defined in a #[pymethods] impl block.

This is done using the #[getter] and #[setter] attributes, like in the example below:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    num: i32,
}

#[pymethods]
impl MyClass {
    #[getter]
    fn num(&self) -> PyResult<i32> {
        Ok(self.num)
    }
}

A getter or setter's function name is used as the property name by default. There are several ways how to override the name.

If a function name starts with get_ or set_ for getter or setter respectively, the descriptor name becomes the function name with this prefix removed. This is also useful in case of Rust keywords like type (raw identifiers can be used since Rust 2018).

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    num: i32,
}
#[pymethods]
impl MyClass {
    #[getter]
    fn get_num(&self) -> PyResult<i32> {
        Ok(self.num)
    }

    #[setter]
    fn set_num(&mut self, value: i32) -> PyResult<()> {
        self.num = value;
        Ok(())
    }
}

In this case, a property num is defined and available from Python code as self.num.

Both the #[getter] and #[setter] attributes accept one parameter. If this parameter is specified, it is used as the property name, i.e.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
   num: i32,
}
#[pymethods]
impl MyClass {
    #[getter(number)]
    fn num(&self) -> PyResult<i32> {
        Ok(self.num)
    }

    #[setter(number)]
    fn set_num(&mut self, value: i32) -> PyResult<()> {
        self.num = value;
        Ok(())
    }
}

In this case, the property number is defined and available from Python code as self.number.

Attributes defined by #[setter] or #[pyo3(set)] will always raise AttributeError on del operations. Support for defining custom del behavior is tracked in #1778.

Instance methods

To define a Python compatible method, an impl block for your struct has to be annotated with the #[pymethods] attribute. PyO3 generates Python compatible wrappers for all functions in this block with some variations, like descriptors, class method static methods, etc.

Since Rust allows any number of impl blocks, you can easily split methods between those accessible to Python (and Rust) and those accessible only to Rust. However to have multiple #[pymethods]-annotated impl blocks for the same struct you must enable the multiple-pymethods feature of PyO3.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    num: i32,
}
#[pymethods]
impl MyClass {
    fn method1(&self) -> PyResult<i32> {
        Ok(10)
    }

    fn set_method(&mut self, value: i32) -> PyResult<()> {
        self.num = value;
        Ok(())
    }
}

Calls to these methods are protected by the GIL, so both &self and &mut self can be used. The return type must be PyResult<T> or T for some T that implements IntoPy<PyObject>; the latter is allowed if the method cannot raise Python exceptions.

A Python parameter can be specified as part of method signature, in this case the py argument gets injected by the method wrapper, e.g.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
#[allow(dead_code)]
    num: i32,
}
#[pymethods]
impl MyClass {
    fn method2(&self, py: Python<'_>) -> PyResult<i32> {
        Ok(10)
    }
}

From the Python perspective, the method2 in this example does not accept any arguments.

Class methods

To create a class method for a custom class, the method needs to be annotated with the #[classmethod] attribute. This is the equivalent of the Python decorator @classmethod.

use pyo3::prelude::*;
use pyo3::types::PyType;
#[pyclass]
struct MyClass {
    #[allow(dead_code)]
    num: i32,
}
#[pymethods]
impl MyClass {
    #[classmethod]
    fn cls_method(cls: &Bound<'_, PyType>) -> PyResult<i32> {
        Ok(10)
    }
}

Declares a class method callable from Python.

The first parameter is the type object of the class on which the method is called. This may be the type object of a derived class.
The first parameter implicitly has type &Bound<'_, PyType>.
For details on parameter-list, see the documentation of Method arguments section.
The return type must be PyResult<T> or T for some T that implements IntoPy<PyObject>.

Constructors which accept a class argument

To create a constructor which takes a positional class argument, you can combine the #[classmethod] and #[new] modifiers:

#![allow(dead_code)]
use pyo3::prelude::*;
use pyo3::types::PyType;
#[pyclass]
struct BaseClass(PyObject);

#[pymethods]
impl BaseClass {
    #[new]
    #[classmethod]
    fn py_new(cls: &Bound<'_, PyType>) -> PyResult<Self> {
        // Get an abstract attribute (presumably) declared on a subclass of this class.
        let subclass_attr: Bound<'_, PyAny> = cls.getattr("a_class_attr")?;
        Ok(Self(subclass_attr.unbind()))
    }
}

Static methods

To create a static method for a custom class, the method needs to be annotated with the #[staticmethod] attribute. The return type must be T or PyResult<T> for some T that implements IntoPy<PyObject>.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    #[allow(dead_code)]
    num: i32,
}
#[pymethods]
impl MyClass {
    #[staticmethod]
    fn static_method(param1: i32, param2: &str) -> PyResult<i32> {
        Ok(10)
    }
}

Class attributes

To create a class attribute (also called class variable), a method without any arguments can be annotated with the #[classattr] attribute.

use pyo3::prelude::*;
#[pyclass]
struct MyClass {}
#[pymethods]
impl MyClass {
    #[classattr]
    fn my_attribute() -> String {
        "hello".to_string()
    }
}

Python::with_gil(|py| {
    let my_class = py.get_type::<MyClass>();
    pyo3::py_run!(py, my_class, "assert my_class.my_attribute == 'hello'")
});

Note: if the method has a Result return type and returns an Err, PyO3 will panic during class creation.

If the class attribute is defined with const code only, one can also annotate associated constants:

use pyo3::prelude::*;
#[pyclass]
struct MyClass {}
#[pymethods]
impl MyClass {
    #[classattr]
    const MY_CONST_ATTRIBUTE: &'static str = "foobar";
}

Classes as function arguments

Free functions defined using #[pyfunction] interact with classes through the same mechanisms as the self parameters of instance methods, i.e. they can take GIL-bound references, GIL-bound reference wrappers or GIL-indepedent references:

#![allow(dead_code)]
use pyo3::prelude::*;
#[pyclass]
struct MyClass {
    my_field: i32,
}

// Take a reference when the underlying `Bound` is irrelevant.
#[pyfunction]
fn increment_field(my_class: &mut MyClass) {
    my_class.my_field += 1;
}

// Take a reference wrapper when borrowing should be automatic,
// but interaction with the underlying `Bound` is desired.
#[pyfunction]
fn print_field(my_class: PyRef<'_, MyClass>) {
    println!("{}", my_class.my_field);
}

// Take a reference to the underlying Bound
// when borrowing needs to be managed manually.
#[pyfunction]
fn increment_then_print_field(my_class: &Bound<'_, MyClass>) {
    my_class.borrow_mut().my_field += 1;

    println!("{}", my_class.borrow().my_field);
}

// Take a GIL-indepedent reference when you want to store the reference elsewhere.
#[pyfunction]
fn print_refcnt(my_class: Py<MyClass>, py: Python<'_>) {
    println!("{}", my_class.get_refcnt(py));
}

Classes can also be passed by value if they can be cloned, i.e. they automatically implement FromPyObject if they implement Clone, e.g. via #[derive(Clone)]:

#![allow(dead_code)]
use pyo3::prelude::*;
#[pyclass]
#[derive(Clone)]
struct MyClass {
    my_field: Box<i32>,
}

#[pyfunction]
fn dissamble_clone(my_class: MyClass) {
    let MyClass { mut my_field } = my_class;
    *my_field += 1;
}

Note that #[derive(FromPyObject)] on a class is usually not useful as it tries to construct a new Rust value by filling in the fields by looking up attributes of any given Python value.

Method arguments

Similar to #[pyfunction], the #[pyo3(signature = (...))] attribute can be used to specify the way that #[pymethods] accept arguments. Consult the documentation for function signatures to see the parameters this attribute accepts.

The following example defines a class MyClass with a method method. This method has a signature that sets default values for num and name, and indicates that py_args should collect all extra positional arguments and py_kwargs all extra keyword arguments:

use pyo3::prelude::*;
use pyo3::types::{PyDict, PyTuple};

#[pyclass]
struct MyClass {
    num: i32,
}
#[pymethods]
impl MyClass {
    #[new]
    #[pyo3(signature = (num=-1))]
    fn new(num: i32) -> Self {
        MyClass { num }
    }

    #[pyo3(signature = (num=10, *py_args, name="Hello", **py_kwargs))]
    fn method(
        &mut self,
        num: i32,
        py_args: &Bound<'_, PyTuple>,
        name: &str,
        py_kwargs: Option<&Bound<'_, PyDict>>,
    ) -> String {
        let num_before = self.num;
        self.num = num;
        format!(
            "num={} (was previously={}), py_args={:?}, name={}, py_kwargs={:?} ",
            num, num_before, py_args, name, py_kwargs,
        )
    }
}

In Python, this might be used like:

>>> import mymodule
>>> mc = mymodule.MyClass()
>>> print(mc.method(44, False, "World", 666, x=44, y=55))
py_args=('World', 666), py_kwargs=Some({'x': 44, 'y': 55}), name=Hello, num=44, num_before=-1
>>> print(mc.method(num=-1, name="World"))
py_args=(), py_kwargs=None, name=World, num=-1, num_before=44

The #[pyo3(text_signature = "...") option for #[pyfunction] also works for #[pymethods].

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

#[pyclass]
struct MyClass {}

#[pymethods]
impl MyClass {
    #[new]
    #[pyo3(text_signature = "(c, d)")]
    fn new(c: i32, d: &str) -> Self {
        Self {}
    }
    // the self argument should be written $self
    #[pyo3(text_signature = "($self, e, f)")]
    fn my_method(&self, e: i32, f: i32) -> i32 {
        e + f
    }
    // similarly for classmethod arguments, use $cls
    #[classmethod]
    #[pyo3(text_signature = "($cls, e, f)")]
    fn my_class_method(cls: &Bound<'_, PyType>, e: i32, f: i32) -> i32 {
        e + f
    }
    #[staticmethod]
    #[pyo3(text_signature = "(e, f)")]
    fn my_static_method(e: i32, f: i32) -> i32 {
        e + f
    }
}

fn main() -> PyResult<()> {
    Python::with_gil(|py| {
        let inspect = PyModule::import(py, "inspect")?.getattr("signature")?;
        let module = PyModule::new(py, "my_module")?;
        module.add_class::<MyClass>()?;
        let class = module.getattr("MyClass")?;

        if cfg!(not(Py_LIMITED_API)) || py.version_info() >= (3, 10)  {
            let doc: String = class.getattr("__doc__")?.extract()?;
            assert_eq!(doc, "");

            let sig: String = inspect
                .call1((&class,))?
                .call_method0("__str__")?
                .extract()?;
            assert_eq!(sig, "(c, d)");
        } else {
            let doc: String = class.getattr("__doc__")?.extract()?;
            assert_eq!(doc, "");

            inspect.call1((&class,)).expect_err("`text_signature` on classes is not compatible with compilation in `abi3` mode until Python 3.10 or greater");
         }

        {
            let method = class.getattr("my_method")?;

            assert!(method.getattr("__doc__")?.is_none());

            let sig: String = inspect
                .call1((method,))?
                .call_method0("__str__")?
                .extract()?;
            assert_eq!(sig, "(self, /, e, f)");
        }

        {
            let method = class.getattr("my_class_method")?;

            assert!(method.getattr("__doc__")?.is_none());

            let sig: String = inspect
                .call1((method,))?
                .call_method0("__str__")?
                .extract()?;
            assert_eq!(sig, "(e, f)");  // inspect.signature skips the $cls arg
        }

        {
            let method = class.getattr("my_static_method")?;

            assert!(method.getattr("__doc__")?.is_none());

            let sig: String = inspect
                .call1((method,))?
                .call_method0("__str__")?
                .extract()?;
            assert_eq!(sig, "(e, f)");
        }

        Ok(())
    })
}

Note that text_signature on #[new] is not compatible with compilation in abi3 mode until Python 3.10 or greater.

Method receivers and lifetime elision

PyO3 supports writing instance methods using the normal method receivers for shared &self and unique &mut self references. This interacts with lifetime elision insofar as the lifetime of a such a receiver is assigned to all elided output lifetime parameters.

This is a good default for general Rust code where return values are more likely to borrow from the receiver than from the other arguments, if they contain any lifetimes at all. However, when returning bound references Bound<'py, T> in PyO3-based code, the GIL lifetime 'py should usually be derived from a GIL token py: Python<'py> passed as an argument instead of the receiver.

Specifically, signatures like

fn frobnicate(&self, py: Python) -> Bound<Foo>;

will not work as they are inferred as

fn frobnicate<'a, 'py>(&'a self, py: Python<'py>) -> Bound<'a, Foo>;

instead of the intended

fn frobnicate<'a, 'py>(&'a self, py: Python<'py>) -> Bound<'py, Foo>;

and should usually be written as

fn frobnicate<'py>(&self, py: Python<'py>) -> Bound<'py, Foo>;

The same problem does not exist for #[pyfunction]s as the special case for receiver lifetimes does not apply and indeed a signature like

fn frobnicate(bar: &Bar, py: Python) -> Bound<Foo>;

will yield compiler error E0106 "missing lifetime specifier".

`#[pyclass]` enums

Enum support in PyO3 comes in two flavors, depending on what kind of variants the enum has: simple and complex.

Simple enums

A simple enum (a.k.a. C-like enum) has only unit variants.

PyO3 adds a class attribute for each variant, so you can access them in Python without defining #[new]. PyO3 also provides default implementations of __richcmp__ and __int__, so they can be compared using ==:

use pyo3::prelude::*;
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum MyEnum {
    Variant,
    OtherVariant,
}

Python::with_gil(|py| {
    let x = Py::new(py, MyEnum::Variant).unwrap();
    let y = Py::new(py, MyEnum::OtherVariant).unwrap();
    let cls = py.get_type::<MyEnum>();
    pyo3::py_run!(py, x y cls, r#"
        assert x == cls.Variant
        assert y == cls.OtherVariant
        assert x != y
    "#)
})

You can also convert your simple enums into int:

use pyo3::prelude::*;
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum MyEnum {
    Variant,
    OtherVariant = 10,
}

Python::with_gil(|py| {
    let cls = py.get_type::<MyEnum>();
    let x = MyEnum::Variant as i32; // The exact value is assigned by the compiler.
    pyo3::py_run!(py, cls x, r#"
        assert int(cls.Variant) == x
        assert int(cls.OtherVariant) == 10
    "#)
})

PyO3 also provides __repr__ for enums:

use pyo3::prelude::*;
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum MyEnum{
    Variant,
    OtherVariant,
}

Python::with_gil(|py| {
    let cls = py.get_type::<MyEnum>();
    let x = Py::new(py, MyEnum::Variant).unwrap();
    pyo3::py_run!(py, cls x, r#"
        assert repr(x) == 'MyEnum.Variant'
        assert repr(cls.OtherVariant) == 'MyEnum.OtherVariant'
    "#)
})

All methods defined by PyO3 can be overridden. For example here's how you override __repr__:

use pyo3::prelude::*;
#[pyclass(eq, eq_int)]
#[derive(PartialEq)]
enum MyEnum {
    Answer = 42,
}

#[pymethods]
impl MyEnum {
    fn __repr__(&self) -> &'static str {
        "42"
    }
}

Python::with_gil(|py| {
    let cls = py.get_type::<MyEnum>();
    pyo3::py_run!(py, cls, "assert repr(cls.Answer) == '42'")
})

Enums and their variants can also be renamed using #[pyo3(name)].

use pyo3::prelude::*;
#[pyclass(eq, eq_int, name = "RenamedEnum")]
#[derive(PartialEq)]
enum MyEnum {
    #[pyo3(name = "UPPERCASE")]
    Variant,
}

Python::with_gil(|py| {
    let x = Py::new(py, MyEnum::Variant).unwrap();
    let cls = py.get_type::<MyEnum>();
    pyo3::py_run!(py, x cls, r#"
        assert repr(x) == 'RenamedEnum.UPPERCASE'
        assert x == cls.UPPERCASE
    "#)
})

Ordering of enum variants is optionally added using #[pyo3(ord)]. Note: Implementation of the PartialOrd trait is required when passing the ord argument. If not implemented, a compile time error is raised.

use pyo3::prelude::*;
#[pyclass(eq, ord)]
#[derive(PartialEq, PartialOrd)]
enum MyEnum{
    A,
    B,
    C,
}

Python::with_gil(|py| {
    let cls = py.get_type::<MyEnum>();
    let a = Py::new(py, MyEnum::A).unwrap();
    let b = Py::new(py, MyEnum::B).unwrap();
    let c = Py::new(py, MyEnum::C).unwrap();
    pyo3::py_run!(py, cls a b c, r#"
        assert (a < b) == True
        assert (c <= b) == False
        assert (c > a) == True
    "#)
})

You may not use enums as a base class or let enums inherit from other classes.

use pyo3::prelude::*;
#[pyclass(subclass)]
enum BadBase {
    Var1,
}

use pyo3::prelude::*;

#[pyclass(subclass)]
struct Base;

#[pyclass(extends=Base)]
enum BadSubclass {
    Var1,
}

#[pyclass] enums are currently not interoperable with IntEnum in Python.

Complex enums

An enum is complex if it has any non-unit (struct or tuple) variants.

PyO3 supports only struct and tuple variants in a complex enum. Unit variants aren't supported at present (the recommendation is to use an empty tuple enum instead).

PyO3 adds a class attribute for each variant, which may be used to construct values and in match patterns. PyO3 also provides getter methods for all fields of each variant.

use pyo3::prelude::*;
#[pyclass]
enum Shape {
    Circle { radius: f64 },
    Rectangle { width: f64, height: f64 },
    RegularPolygon(u32, f64),
    Nothing { },
}

#[cfg(Py_3_10)]
Python::with_gil(|py| {
    let circle = Shape::Circle { radius: 10.0 }.into_pyobject(py)?;
    let square = Shape::RegularPolygon(4, 10.0).into_pyobject(py)?;
    let cls = py.get_type::<Shape>();
    pyo3::py_run!(py, circle square cls, r#"
        assert isinstance(circle, cls)
        assert isinstance(circle, cls.Circle)
        assert circle.radius == 10.0

        assert isinstance(square, cls)
        assert isinstance(square, cls.RegularPolygon)
        assert square[0] == 4 # Gets _0 field
        assert square[1] == 10.0 # Gets _1 field

        def count_vertices(cls, shape):
            match shape:
                case cls.Circle():
                    return 0
                case cls.Rectangle():
                    return 4
                case cls.RegularPolygon(n):
                    return n
                case cls.Nothing():
                    return 0

        assert count_vertices(cls, circle) == 0
        assert count_vertices(cls, square) == 4
    "#);
  Ok::<_, PyErr>(())
})
.unwrap();

WARNING: Py::new and .into_pyobject are currently inconsistent. Note how the constructed value is not an instance of the specific variant. For this reason, constructing values is only recommended using .into_pyobject.

use pyo3::prelude::*;
#[pyclass]
enum MyEnum {
    Variant { i: i32 },
}

Python::with_gil(|py| {
    let x = Py::new(py, MyEnum::Variant { i: 42 }).unwrap();
    let cls = py.get_type::<MyEnum>();
    pyo3::py_run!(py, x cls, r#"
        assert isinstance(x, cls)
        assert not isinstance(x, cls.Variant)
    "#)
})

The constructor of each generated class can be customized using the #[pyo3(constructor = (...))] attribute. This uses the same syntax as the #[pyo3(signature = (...))] attribute on function and methods and supports the same options. To apply this attribute simply place it on top of a variant in a #[pyclass] complex enum as shown below:

use pyo3::prelude::*;
#[pyclass]
enum Shape {
    #[pyo3(constructor = (radius=1.0))]
    Circle { radius: f64 },
    #[pyo3(constructor = (*, width, height))]
    Rectangle { width: f64, height: f64 },
    #[pyo3(constructor = (side_count, radius=1.0))]
    RegularPolygon { side_count: u32, radius: f64 },
    Nothing { },
}

#[cfg(Py_3_10)]
Python::with_gil(|py| {
    let cls = py.get_type::<Shape>();
    pyo3::py_run!(py, cls, r#"
        circle = cls.Circle()
        assert isinstance(circle, cls)
        assert isinstance(circle, cls.Circle)
        assert circle.radius == 1.0

        square = cls.Rectangle(width = 1, height = 1)
        assert isinstance(square, cls)
        assert isinstance(square, cls.Rectangle)
        assert square.width == 1
        assert square.height == 1

        hexagon = cls.RegularPolygon(6)
        assert isinstance(hexagon, cls)
        assert isinstance(hexagon, cls.RegularPolygon)
        assert hexagon.side_count == 6
        assert hexagon.radius == 1
    "#)
})

Implementation details

The #[pyclass] macros rely on a lot of conditional code generation: each #[pyclass] can optionally have a #[pymethods] block.

To support this flexibility the #[pyclass] macro expands to a blob of boilerplate code which sets up the structure for "dtolnay specialization". This implementation pattern enables the Rust compiler to use #[pymethods] implementations when they are present, and fall back to default (empty) definitions when they are not.

This simple technique works for the case when there is zero or one implementations. To support multiple #[pymethods] for a #[pyclass] (in the multiple-pymethods feature), a registry mechanism provided by the inventory crate is used instead. This collects impls at library load time, but isn't supported on all platforms. See inventory: how it works for more details.

The #[pyclass] macro expands to roughly the code seen below. The PyClassImplCollector is the type used internally by PyO3 for dtolnay specialization:

#[cfg(not(feature = "multiple-pymethods"))] {
use pyo3::prelude::*;
// Note: the implementation differs slightly with the `multiple-pymethods` feature enabled.
#[allow(dead_code)]
struct MyClass {
    #[allow(dead_code)]
    num: i32,
}

impl pyo3::types::DerefToPyAny for MyClass {}

unsafe impl pyo3::type_object::PyTypeInfo for MyClass {
    const NAME: &'static str = "MyClass";
    const MODULE: ::std::option::Option<&'static str> = ::std::option::Option::None;
    #[inline]
    fn type_object_raw(py: pyo3::Python<'_>) -> *mut pyo3::ffi::PyTypeObject {
        <Self as pyo3::impl_::pyclass::PyClassImpl>::lazy_type_object()
            .get_or_init(py)
            .as_type_ptr()
    }
}

impl pyo3::PyClass for MyClass {
    type Frozen = pyo3::pyclass::boolean_struct::False;
}

impl<'a, 'py> pyo3::impl_::extract_argument::PyFunctionArgument<'a, 'py> for &'a MyClass
{
    type Holder = ::std::option::Option<pyo3::PyRef<'py, MyClass>>;

    #[inline]
    fn extract(obj: &'a pyo3::Bound<'py, PyAny>, holder: &'a mut Self::Holder) -> pyo3::PyResult<Self> {
        pyo3::impl_::extract_argument::extract_pyclass_ref(obj, holder)
    }
}

impl<'a, 'py> pyo3::impl_::extract_argument::PyFunctionArgument<'a, 'py> for &'a mut MyClass
{
    type Holder = ::std::option::Option<pyo3::PyRefMut<'py, MyClass>>;

    #[inline]
    fn extract(obj: &'a pyo3::Bound<'py, PyAny>, holder: &'a mut Self::Holder) -> pyo3::PyResult<Self> {
        pyo3::impl_::extract_argument::extract_pyclass_ref_mut(obj, holder)
    }
}

#[allow(deprecated)]
impl pyo3::IntoPy<PyObject> for MyClass {
    fn into_py(self, py: pyo3::Python<'_>) -> pyo3::PyObject {
        pyo3::IntoPy::into_py(pyo3::Py::new(py, self).unwrap(), py)
    }
}

impl pyo3::impl_::pyclass::PyClassImpl for MyClass {
    const IS_BASETYPE: bool = false;
    const IS_SUBCLASS: bool = false;
    const IS_MAPPING: bool = false;
    const IS_SEQUENCE: bool = false;
    type BaseType = PyAny;
    type ThreadChecker = pyo3::impl_::pyclass::SendablePyClass<MyClass>;
    type PyClassMutability = <<pyo3::PyAny as pyo3::impl_::pyclass::PyClassBaseType>::PyClassMutability as pyo3::impl_::pycell::PyClassMutability>::MutableChild;
    type Dict = pyo3::impl_::pyclass::PyClassDummySlot;
    type WeakRef = pyo3::impl_::pyclass::PyClassDummySlot;
    type BaseNativeType = pyo3::PyAny;

    fn items_iter() -> pyo3::impl_::pyclass::PyClassItemsIter {
        use pyo3::impl_::pyclass::*;
        let collector = PyClassImplCollector::<MyClass>::new();
        static INTRINSIC_ITEMS: PyClassItems = PyClassItems { slots: &[], methods: &[] };
        PyClassItemsIter::new(&INTRINSIC_ITEMS, collector.py_methods())
    }

    fn lazy_type_object() -> &'static pyo3::impl_::pyclass::LazyTypeObject<MyClass> {
        use pyo3::impl_::pyclass::LazyTypeObject;
        static TYPE_OBJECT: LazyTypeObject<MyClass> = LazyTypeObject::new();
        &TYPE_OBJECT
    }

    fn doc(py: Python<'_>) -> pyo3::PyResult<&'static ::std::ffi::CStr> {
        use pyo3::impl_::pyclass::*;
        static DOC: pyo3::sync::GILOnceCell<::std::borrow::Cow<'static, ::std::ffi::CStr>> = pyo3::sync::GILOnceCell::new();
        DOC.get_or_try_init(py, || {
            let collector = PyClassImplCollector::<Self>::new();
            build_pyclass_doc(<MyClass as pyo3::PyTypeInfo>::NAME, pyo3::ffi::c_str!(""), collector.new_text_signature())
        }).map(::std::ops::Deref::deref)
    }
}

Python::with_gil(|py| {
    let cls = py.get_type::<MyClass>();
    pyo3::py_run!(py, cls, "assert cls.__name__ == 'MyClass'")
});
}

PyO3 user guide