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:
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 implement Send
. 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 Send
Because Python objects are freely shared between threads by the Python interpreter, there is no guarantee which thread will eventually drop the object. Therefore all types annotated with #[pyclass]
must implement Send
(unless annotated with #[pyclass(unsendable)]
).
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. |
text_signature = "(arg1, arg2, ...)" | Sets the text signature for the Python class' __new__ method. |
unsendable | Required if your struct is not Send . Rather than using unsendable , consider implementing your struct in a threadsafe 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 clases 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)?.to_object(py))
} else {
let sub_sub = sub.add_subclass(SubSubClass { val3: val });
Ok(Py::new(py, sub_sub)?.to_object(py))
}
}
}
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 bothIntoPy<PyObject>
andClone
. - For
set
the field type must implementFromPyObject
.
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 ofMethod arguments
section. - The return type must be
PyResult<T>
orT
for someT
that implementsIntoPy<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 anErr
, 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_py(py);
let square = Shape::RegularPolygon(4, 10.0).into_py(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
"#)
})
WARNING: Py::new
and .into_py
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_py
.
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 impl
s 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)
}
}
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'")
});
}