Class customizations
Python's object model defines several protocols for different object behavior, such as the sequence, mapping, and number protocols. You may be familiar with implementing these protocols in Python classes by "magic" methods, such as __str__
or __repr__
. Because of the double-underscores surrounding their name, these are also known as "dunder" methods.
In the Python C-API which PyO3 is implemented upon, many of these magic methods have to be placed into special "slots" on the class type object. as already covered in the previous section. There are two ways in which this can be done:
- [Experimental for PyO3 0.15, may change slightly in PyO3 0.16] In
#[pymethods]
, if the name of the method is a recognised magic method, PyO3 will place it in the type object automatically. - [Stable, but expected to be deprecated in PyO3 0.16] In special traits combined with the
#[pyproto]
attribute.
(There are also many magic methods which don't have a special slot, such as __dir__
. These methods can be implemented as normal in #[pymethods]
.)
This chapter of the guide has a section on each of these solutions in turn:
Magic methods in #[pymethods]
In PyO3 0.15, if a function name in #[pymethods]
is a recognised magic method, it will be automatically placed into the correct slot in the Python type object. The function name is taken from the usual rules for naming #[pymethods]
: the #[pyo3(name = "...")]
attribute is used if present, otherwise the Rust function name is used.
The magic methods handled by PyO3 are very similar to the standard Python ones on this page - in particular they are the the subset which have slots as defined here. Some of the slots do not have a magic method in Python, which leads to a few additional magic methods defined only in PyO3:
- Magic methods for garbage collection
- Magic methods for the buffer protocol
- Magic methods for the sequence protocol
When PyO3 handles a magic method, a couple of changes apply compared to other #[pymethods]
:
- The
#[pyo3(text_signature = "...")]
attribute is not allowed - The signature is restricted to match the magic method
The following sections list of all magic methods PyO3 currently handles. The given signatures should be interpreted as follows:
- All methods take a receiver as first argument, shown as
<self>
. It can be&self
,&mut self
or aPyCell
reference likeself_: PyRef<Self>
andself_: PyRefMut<Self>
, as described here. - An optional
Python<'py>
argument is always allowed as the first argument. - Return values can be optionally wrapped in
PyResult
. object
means that any type is allowed that can be extracted from a Python object (if argument) or converted to a Python object (if return value).- Other types must match what's given, e.g.
pyo3::basic::CompareOp
for__richcmp__
's second argument. - For the comparison and arithmetic methods, extraction errors are not
propagated as exceptions, but lead to a return of
NotImplemented
. - For some magic methods, the return values are not restricted by PyO3, but
checked by the Python interpreter. For example,
__str__
needs to return a string object. This is indicated byobject (Python type)
.
Basic object customization
-
__str__(<self>) -> object (str)
-
__repr__(<self>) -> object (str)
-
__hash__(<self>) -> isize
-
__richcmp__(<self>, object, pyo3::basic::CompareOp) -> object
-
__getattr__(<self>, object) -> object
-
__setattr__(<self>, object, object) -> ()
-
__delattr__(<self>, object) -> ()
-
__bool__(<self>) -> bool
-
__call__(<self>, ...) -> object
- here, any argument list can be defined as for normalpymethods
Example: Callable objects
Custom classes can be callable if they have a #[pymethod]
named __call__
.
The following pyclass is a basic decorator - its constructor takes a Python object as argument and calls that object when called.
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::types::{PyDict, PyTuple}; #[pyclass(name = "counter")] struct PyCounter { count: u64, wraps: Py<PyAny>, } #[pymethods] impl PyCounter { #[new] fn __new__(wraps: Py<PyAny>) -> Self { PyCounter { count: 0, wraps } } fn __call__( &mut self, py: Python, args: &PyTuple, kwargs: Option<&PyDict>, ) -> PyResult<Py<PyAny>> { self.count += 1; let name = self.wraps.getattr(py, "__name__").unwrap(); println!("{} has been called {} time(s).", name, self.count); self.wraps.call(py, args, kwargs) } } }
Python code:
@counter
def say_hello():
print("hello")
say_hello()
say_hello()
say_hello()
say_hello()
Output:
say_hello has been called 1 time(s).
hello
say_hello has been called 2 time(s).
hello
say_hello has been called 3 time(s).
hello
say_hello has been called 4 time(s).
hello
Iterable objects
__iter__(<self>) -> object
__next__(<self>) -> Option<object> or IterNextOutput
(see details)
Awaitable objects
__await__(<self>) -> object
__aiter__(<self>) -> object
__anext__(<self>) -> Option<object> or IterANextOutput
Sequence types
TODO; see #1884
Mapping types
__len__(<self>) -> usize
__contains__(<self>, object) -> bool
__getitem__(<self>, object) -> object
__setitem__(<self>, object, object) -> ()
__delitem__(<self>, object) -> ()
Descriptors
__get__(<self>, object, object) -> object
__set__(<self>, object, object) -> ()
__delete__(<self>, object) -> ()
Numeric types
__pos__(<self>) -> object
__neg__(<self>) -> object
__abs__(<self>) -> object
__invert__(<self>) -> object
__index__(<self>) -> object (int)
__int__(<self>) -> object (int)
__float__(<self>) -> object (float)
__iadd__(<self>, object) -> ()
__isub__(<self>, object) -> ()
__imul__(<self>, object) -> ()
__imatmul__(<self>, object) -> ()
__itruediv__(<self>, object) -> ()
__ifloordiv__(<self>, object) -> ()
__imod__(<self>, object) -> ()
__ipow__(<self>, object, object) -> ()
__ilshift__(<self>, object) -> ()
__irshift__(<self>, object) -> ()
__iand__(<self>, object) -> ()
__ixor__(<self>, object) -> ()
__ior__(<self>, object) -> ()
__add__(<self>, object) -> object
__radd__(<self>, object) -> object
__sub__(<self>, object) -> object
__rsub__(<self>, object) -> object
__mul__(<self>, object) -> object
__rmul__(<self>, object) -> object
__matmul__(<self>, object) -> object
__rmatmul__(<self>, object) -> object
__floordiv__(<self>, object) -> object
__rfloordiv__(<self>, object) -> object
__truediv__(<self>, object) -> object
__rtruediv__(<self>, object) -> object
__divmod__(<self>, object) -> object
__rdivmod__(<self>, object) -> object
__mod__(<self>, object) -> object
__rmod__(<self>, object) -> object
__lshift__(<self>, object) -> object
__rlshift__(<self>, object) -> object
__rshift__(<self>, object) -> object
__rrshift__(<self>, object) -> object
__and__(<self>, object) -> object
__rand__(<self>, object) -> object
__xor__(<self>, object) -> object
__rxor__(<self>, object) -> object
__or__(<self>, object) -> object
__ror__(<self>, object) -> object
__pow__(<self>, object, object) -> object
__rpow__(<self>, object, object) -> object
Buffer objects
TODO; see #1884
Garbage Collector Integration
TODO; see #1884
#[pyproto]
traits
PyO3 can use the #[pyproto]
attribute in combination with special traits to implement the magic methods which need slots. The special traits are listed below. See also the documentation for the pyo3::class
module.
Before PyO3 0.15 this was the only supported solution for implementing magic methods. Due to complexity in the implementation and usage, these traits are expected to be deprecated in PyO3 0.16 in favour of the #[pymethods]
solution.
All #[pyproto]
methods can return T
instead of PyResult<T>
if the method implementation is infallible. In addition, if the return type is ()
, it can be omitted altogether.
Basic object customization
The PyObjectProtocol
trait provides several basic customizations.
Attribute access
To customize object attribute access, define the following methods:
fn __getattr__(&self, name: impl FromPyObject) -> PyResult<impl IntoPy<PyObject>>
fn __setattr__(&mut self, name: impl FromPyObject, value: impl FromPyObject) -> PyResult<()>
fn __delattr__(&mut self, name: impl FromPyObject) -> PyResult<()>
Each method corresponds to Python's self.attr
, self.attr = value
and del self.attr
code.
String Conversions
-
fn __repr__(&self) -> PyResult<impl ToPyObject<ObjectType=PyString>>
-
fn __str__(&self) -> PyResult<impl ToPyObject<ObjectType=PyString>>
Possible return types for
__str__
and__repr__
arePyResult<String>
orPyResult<PyString>
.
Comparison operators
-
fn __richcmp__(&self, other: impl FromPyObject, op: CompareOp) -> PyResult<impl ToPyObject>
Overloads Python comparison operations (
==
,!=
,<
,<=
,>
, and>=
). Theop
argument indicates the comparison operation being performed. The return type will normally bePyResult<bool>
, but any Python object can be returned. Ifother
is not of the type specified in the signature, the generated code will automaticallyreturn NotImplemented
. -
fn __hash__(&self) -> PyResult<impl PrimInt>
Objects that compare equal must have the same hash value. The return type must be
PyResult<T>
whereT
is one of Rust's primitive integer types.
Other methods
-
fn __bool__(&self) -> PyResult<bool>
Determines the "truthyness" of the object.
Emulating numeric types
The PyNumberProtocol
trait can be implemented to emulate numeric types.
fn __add__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __sub__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __mul__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __matmul__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __truediv__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __floordiv__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __mod__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __divmod__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __pow__(lhs: impl FromPyObject, rhs: impl FromPyObject, modulo: Option<impl FromPyObject>) -> PyResult<impl ToPyObject>
fn __lshift__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rshift__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __and__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __or__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __xor__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
These methods are called to implement the binary arithmetic operations
(+
, -
, *
, @
, /
, //
, %
, divmod()
, pow()
and **
, <<
, >>
, &
, ^
, and |
).
If rhs
is not of the type specified in the signature, the generated code
will automatically return NotImplemented
. This is not the case for lhs
which must match signature or else raise a TypeError.
The reflected operations are also available:
fn __radd__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rsub__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rmul__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rmatmul__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rtruediv__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rfloordiv__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rmod__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rdivmod__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rpow__(lhs: impl FromPyObject, rhs: impl FromPyObject, modulo: Option<impl FromPyObject>) -> PyResult<impl ToPyObject>
fn __rlshift__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rrshift__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rand__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __ror__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
fn __rxor__(lhs: impl FromPyObject, rhs: impl FromPyObject) -> PyResult<impl ToPyObject>
The code generated for these methods expect that all arguments match the signature, or raise a TypeError.
This trait also has support the augmented arithmetic assignments (+=
, -=
,
*=
, @=
, /=
, //=
, %=
, **=
, <<=
, >>=
, &=
, ^=
, |=
):
fn __iadd__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __isub__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __imul__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __imatmul__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __itruediv__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __ifloordiv__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __imod__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __ipow__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __ilshift__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __irshift__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __iand__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __ior__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
fn __ixor__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
The following methods implement the unary arithmetic operations (-
, +
, abs()
and ~
):
fn __neg__(&'p self) -> PyResult<impl ToPyObject>
fn __pos__(&'p self) -> PyResult<impl ToPyObject>
fn __abs__(&'p self) -> PyResult<impl ToPyObject>
fn __invert__(&'p self) -> PyResult<impl ToPyObject>
Support for coercions:
fn __int__(&'p self) -> PyResult<impl ToPyObject>
fn __float__(&'p self) -> PyResult<impl ToPyObject>
Other:
fn __index__(&'p self) -> PyResult<impl ToPyObject>
Emulating sequential containers (such as lists or tuples)
The PySequenceProtocol
trait can be implemented to emulate
sequential container types.
For a sequence, the keys are the integers k for which 0 <= k < N, where N is the length of the sequence.
-
fn __len__(&self) -> PyResult<usize>
Implements the built-in function
len()
for the sequence. -
fn __getitem__(&self, idx: isize) -> PyResult<impl ToPyObject>
Implements evaluation of the
self[idx]
element. If theidx
value is outside the set of indexes for the sequence,IndexError
should be raised.Note: Negative integer indexes are handled as follows: if
__len__()
is defined, it is called and the sequence length is used to compute a positive index, which is passed to__getitem__()
. If__len__()
is not defined, the index is passed as is to the function. -
fn __setitem__(&mut self, idx: isize, value: impl FromPyObject) -> PyResult<()>
Implements assignment to the
self[idx]
element. Same note as for__getitem__()
. Should only be implemented if sequence elements can be replaced. -
fn __delitem__(&mut self, idx: isize) -> PyResult<()>
Implements deletion of the
self[idx]
element. Same note as for__getitem__()
. Should only be implemented if sequence elements can be deleted. -
fn __contains__(&self, item: impl FromPyObject) -> PyResult<bool>
Implements membership test operators. Should return true if
item
is inself
, false otherwise. For objects that don’t define__contains__()
, the membership test simply traverses the sequence until it finds a match. -
fn __concat__(&self, other: impl FromPyObject) -> PyResult<impl ToPyObject>
Concatenates two sequences. Used by the
+
operator, after trying the numeric addition via thePyNumberProtocol
trait method. -
fn __repeat__(&self, count: isize) -> PyResult<impl ToPyObject>
Repeats the sequence
count
times. Used by the*
operator, after trying the numeric multiplication via thePyNumberProtocol
trait method. -
fn __inplace_concat__(&mut self, other: impl FromPyObject) -> PyResult<Self>
Concatenates two sequences in place. Returns the modified first operand. Used by the
+=
operator, after trying the numeric in place addition via thePyNumberProtocol
trait method. -
fn __inplace_repeat__(&mut self, count: isize) -> PyResult<Self>
Repeats the sequence
count
times in place. Returns the modified first operand. Used by the*=
operator, after trying the numeric in place multiplication via thePyNumberProtocol
trait method.
Emulating mapping containers (such as dictionaries)
The PyMappingProtocol
trait allows to emulate
mapping container types.
For a mapping, the keys may be Python objects of arbitrary type.
-
fn __len__(&self) -> PyResult<usize>
Implements the built-in function
len()
for the mapping. -
fn __getitem__(&self, key: impl FromPyObject) -> PyResult<impl ToPyObject>
Implements evaluation of the
self[key]
element. Ifkey
is of an inappropriate type,TypeError
may be raised; ifkey
is missing (not in the container),KeyError
should be raised. -
fn __setitem__(&mut self, key: impl FromPyObject, value: impl FromPyObject) -> PyResult<()>
Implements assignment to the
self[key]
element or insertion of a newkey
mapping tovalue
. Should only be implemented if the mapping support changes to the values for keys, or if new keys can be added. The same exceptions should be raised for improper key values as for the__getitem__()
method. -
fn __delitem__(&mut self, key: impl FromPyObject) -> PyResult<()>
Implements deletion of the
self[key]
element. Should only be implemented if the mapping supports removal of keys. The same exceptions should be raised for improper key values as for the__getitem__()
method.
Garbage Collector Integration
If your type owns references to other Python objects, you will need to
integrate with Python's garbage collector so that the GC is aware of
those references.
To do this, implement the PyGCProtocol
trait for your struct.
It includes two methods __traverse__
and __clear__
.
These correspond to the slots tp_traverse
and tp_clear
in the Python C API.
__traverse__
must call visit.call()
for each reference to another Python object.
__clear__
must clear out any mutable references to other Python objects
(thus breaking reference cycles). Immutable references do not have to be cleared,
as every cycle must contain at least one mutable reference.
Example:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::PyTraverseError; use pyo3::gc::{PyGCProtocol, PyVisit}; #[pyclass] struct ClassWithGCSupport { obj: Option<PyObject>, } #[pyproto] impl PyGCProtocol for ClassWithGCSupport { fn __traverse__(&self, visit: PyVisit) -> Result<(), PyTraverseError> { if let Some(obj) = &self.obj { visit.call(obj)? } Ok(()) } fn __clear__(&mut self) { // Clear reference, this decrements ref counter. self.obj = None; } } }
Special protocol trait implementations have to be annotated with the #[pyproto]
attribute.
It is also possible to enable GC for custom classes using the gc
parameter of the pyclass
attribute.
i.e. #[pyclass(gc)]
. In that case instances of custom class participate in Python garbage
collection, and it is possible to track them with gc
module methods. When using the gc
parameter,
it is required to implement the PyGCProtocol
trait, failure to do so will result in an error
at compile time:
#[pyclass(gc)]
struct GCTracked {} // Fails because it does not implement PyGCProtocol
Iterator Types
Iterators can be defined using the
PyIterProtocol
trait.
It includes two methods __iter__
and __next__
:
fn __iter__(slf: PyRefMut<Self>) -> PyResult<impl IntoPy<PyObject>>
fn __next__(slf: PyRefMut<Self>) -> PyResult<Option<impl IntoPy<PyObject>>>
Returning None
from __next__
indicates that that there are no further items.
These two methods can be take either PyRef<Self>
or PyRefMut<Self>
as their
first argument, so that mutable borrow can be avoided if needed.
Example:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::PyIterProtocol; #[pyclass] struct MyIterator { iter: Box<dyn Iterator<Item = PyObject> + Send>, } #[pyproto] impl PyIterProtocol for MyIterator { fn __iter__(slf: PyRef<Self>) -> PyRef<Self> { slf } fn __next__(mut slf: PyRefMut<Self>) -> Option<PyObject> { slf.iter.next() } } }
In many cases you'll have a distinction between the type being iterated over (i.e. the iterable) and the iterator it
provides. In this case, you should implement PyIterProtocol
for both the iterable and the iterator, but the iterable
only needs to support __iter__()
while the iterator must support both __iter__()
and __next__()
. The default
implementations in PyIterProtocol
will ensure that the objects behave correctly in Python. For example:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::PyIterProtocol; #[pyclass] struct Iter { inner: std::vec::IntoIter<usize>, } #[pyproto] impl PyIterProtocol for Iter { fn __iter__(slf: PyRef<Self>) -> PyRef<Self> { slf } fn __next__(mut slf: PyRefMut<Self>) -> Option<usize> { slf.inner.next() } } #[pyclass] struct Container { iter: Vec<usize>, } #[pyproto] impl PyIterProtocol for Container { fn __iter__(slf: PyRef<Self>) -> PyResult<Py<Iter>> { let iter = Iter { inner: slf.iter.clone().into_iter(), }; Py::new(slf.py(), iter) } } Python::with_gil(|py| { let container = Container { iter: vec![1, 2, 3, 4] }; let inst = pyo3::PyCell::new(py, container).unwrap(); pyo3::py_run!(py, inst, "assert list(inst) == [1, 2, 3, 4]"); pyo3::py_run!(py, inst, "assert list(iter(iter(inst))) == [1, 2, 3, 4]"); }); }
For more details on Python's iteration protocols, check out the "Iterator Types" section of the library documentation.
Returning a value from iteration
This guide has so far shown how to use Option<T>
to implement yielding values during iteration.
In Python a generator can also return a value. To express this in Rust, PyO3 provides the
IterNextOutput
enum to
both Yield
values and Return
a final value - see its docs for further details and an example.