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 a fieldless enum
(a.k.a. C-like 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 a fieldless enum.
#![allow(unused)] fn main() { #![allow(dead_code)] use pyo3::prelude::*; #[pyclass] struct Integer { inner: i32, } // A "tuple" struct #[pyclass] struct Number(i32); // PyO3 supports custom discriminants in enums #[pyclass] enum HttpResponse { Ok = 200, NotFound = 404, Teapot = 418, // ... } #[pyclass] enum MyEnum { Variant, OtherVariant = 30, // PyO3 supports custom discriminants. } }
The above example generates implementations for PyTypeInfo
and PyClass
for MyClass
and MyEnum
. 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 which 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.
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(unused)] fn main() { 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(unused)] fn main() { 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)) } } } }
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(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct Number(i32); #[pymodule] fn my_module(_py: Python<'_>, m: &PyModule) -> PyResult<()> { m.add_class::<Number>()?; Ok(()) } }
PyCell and interior mutability
You sometimes need to convert your pyclass
into a Python object and access it
from Rust code (e.g., for testing it).
PyCell
is the primary interface for that.
PyCell<T: PyClass>
is always allocated in the Python heap, so Rust doesn't have ownership of it.
In other words, Rust code can only extract a &PyCell<T>
, not a PyCell<T>
.
Thus, to mutate data behind &PyCell
safely, PyO3 employs the
Interior Mutability Pattern
like RefCell
.
Users who are familiar with RefCell
can use PyCell
just like RefCell
.
For users who are not very familiar with RefCell
, 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 must always be valid.
PyCell
, like RefCell
, ensures these borrowing rules by tracking references at runtime.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct MyClass { #[pyo3(get)] num: i32, } Python::with_gil(|py| { let obj = PyCell::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 `&PyCell` to a Python object pyo3::py_run!(py, obj, "assert obj.num == 5"); }); }
&PyCell<T>
is bounded by the same lifetime as a GILGuard
.
To make the object longer lived (for example, to store it in a struct on the
Rust side), you can use Py<T>
, which stores an object longer than the GIL
lifetime, and therefore needs a Python<'_>
token to access.
#![allow(unused)] fn main() { 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(|py| { let cell = obj.as_ref(py); // Py<MyClass>::as_ref returns &PyCell<MyClass> let obj_ref = cell.borrow(); // Get PyRef<T> assert_eq!(obj_ref.num, 1); }); }
Customizing the class
#[pyclass]
can be used with the following parameters:
Parameter | Description |
---|---|
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. |
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 borrowchecker 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. |
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. |
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. |
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. |
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.
For convenience, (T, U)
implements Into<PyClassInitializer<T>>
where U
is the
base class of T
.
But for 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_ref()
as &Self::BaseClass
,
or by self_.into_super()
as PyRef<Self::BaseClass>
.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass(subclass)] struct BaseClass { val1: usize, } #[pymethods] impl BaseClass { #[new] fn new() -> Self { BaseClass { val1: 10 } } pub fn method(&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_ref(); // Get &BaseClass super_.method().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 v = self_.val3; let super_ = self_.into_super(); // Get PyRef<'_, SubClass> SubClass::method2(super_).map(|x| x * v) } } Python::with_gil(|py| { let subsub = pyo3::PyCell::new(py, SubSubClass::new()).unwrap(); pyo3::py_run!(py, subsub, "assert subsub.method3() == 3000") }); }
You can also 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).
However, because of some technical problems, we don't currently provide safe upcasting methods for types that inherit native types. Even in such cases, you can unsafely get a base class by raw pointer conversion.
#![allow(unused)] fn main() { #[cfg(not(Py_LIMITED_API))] { use pyo3::prelude::*; use pyo3::types::PyDict; use pyo3::AsPyPointer; 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(mut self_: PyRefMut<'_, Self>, key: String, value: &PyAny) -> PyResult<()> { self_.counter.entry(key.clone()).or_insert(0); let py = self_.py(); let dict: &PyDict = unsafe { py.from_borrowed_ptr_or_err(self_.as_ptr())? }; dict.set_item(key, value) } } Python::with_gil(|py| { let cnt = pyo3::PyCell::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.
#![allow(unused)] fn main() { 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(unused)] fn main() { #[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: &PyAny, kwargs: Option<&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:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[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
.
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:
#![allow(unused)] fn main() { 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).
#![allow(unused)] fn main() { 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.
#![allow(unused)] fn main() { 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.
#![allow(unused)] fn main() { 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.
#![allow(unused)] fn main() { 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
.
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::types::PyType; #[pyclass] struct MyClass { #[allow(dead_code)] num: i32, } #[pymethods] impl MyClass { #[classmethod] fn cls_method(cls: &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
&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>
.
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>
.
#![allow(unused)] fn main() { 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.
#![allow(unused)] fn main() { 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:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct MyClass {} #[pymethods] impl MyClass { #[classattr] const MY_CONST_ATTRIBUTE: &'static str = "foobar"; } }
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 which 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:
#![allow(unused)] fn main() { 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: &PyTuple, name: &str, py_kwargs: Option<&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
Making class method signatures available to Python
The text_signature = "..."
option for #[pyfunction]
also works for classes and methods:
#![allow(dead_code)] use pyo3::prelude::*; use pyo3::types::PyType; // it works even if the item is not documented: #[pyclass(text_signature = "(c, d, /)")] struct MyClass {} #[pymethods] impl MyClass { // the signature for the constructor is attached // to the struct definition instead. #[new] 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 } #[classmethod] #[pyo3(text_signature = "(cls, e, f)")] fn my_class_method(cls: &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, "(cls, e, f)"); } { 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 classes is not compatible with compilation in
abi3
mode until Python 3.10 or greater.
#[pyclass] enums
Currently PyO3 only supports fieldless enums. 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 ==
:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] 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 enums into int
:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] 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 assert cls.OtherVariant == 10 # You can also compare against int. assert 10 == cls.OtherVariant "#) }) }
PyO3 also provides __repr__
for enums:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] 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__
:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] 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)]
.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass(name = "RenamedEnum")] 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 "#) }) }
You may not use enums as a base class or let enums inherit from other classes.
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass(subclass)] enum BadBase { Var1, } }
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass(subclass)] struct Base; #[pyclass(extends=Base)] enum BadSubclass { Var1, } }
#[pyclass]
enums are currently not interoperable with IntEnum
in Python.
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:
#![allow(unused)] fn main() { #[cfg(not(feature = "multiple-pymethods"))] { use pyo3::prelude::*; // Note: the implementation differs slightly with the `multiple-pymethods` feature enabled. struct MyClass { #[allow(dead_code)] num: i32, } unsafe impl pyo3::type_object::PyTypeInfo for MyClass { type AsRefTarget = pyo3::PyCell<Self>; 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 { use pyo3::type_object::LazyStaticType; static TYPE_OBJECT: LazyStaticType = LazyStaticType::new(); TYPE_OBJECT.get_or_init::<Self>(py) } } 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: &'py pyo3::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: &'py pyo3::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 DOC: &'static str = "Class for demonstration\u{0}"; const IS_BASETYPE: bool = false; const IS_SUBCLASS: bool = false; type Layout = PyCell<MyClass>; type BaseType = PyAny; type ThreadChecker = pyo3::impl_::pyclass::ThreadCheckerStub<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()) } } Python::with_gil(|py| { let cls = py.get_type::<MyClass>(); pyo3::py_run!(py, cls, "assert cls.__name__ == 'MyClass'") }); } }