Magic methods and slots
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 covered in the previous section. There are two ways in which this can be done:
- [New in PyO3 0.15, recommended 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. - [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]
.)
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
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
Objects that compare equal must have the same hash value.
Disabling Python's default hash
By default, all `#[pyclass]` types have a default hash implementation from Python. Types which should not be hashable can override this by setting `__hash__` to `None`. This is the same mechanism as for a pure-Python class. This is done like so:#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct NotHashable { } #[pymethods] impl NotHashable { #[classattr] const __hash__: Option<PyObject> = None; } }
-
__richcmp__(<self>, object, pyo3::basic::CompareOp) -> object
Overloads Python comparison operations (
==
,!=
,<
,<=
,>
, and>=
). TheCompareOp
argument indicates the comparison operation being performed.Return type
The return type will normally be `PyResult`, but any Python object can be returned. If the `object` is not of the type specified in the signature, the generated code will automatically `return NotImplemented`. -
__getattr__(<self>, object) -> object
-
__getattribute__(<self>, object) -> object
Differences between `__getattr__` and `__getattribute__`
As in Python, `__getattr__` is only called if the attribute is not found by normal attribute lookup. `__getattribute__`, on the other hand, is called for *every* attribute access. If it wants to access existing attributes on `self`, it needs to be very careful not to introduce infinite recursion, and use `baseclass.__getattribute__()`. -
__setattr__(<self>, value: object) -> ()
-
__delattr__(<self>, object) -> ()
Overrides attribute access.
-
__bool__(<self>) -> bool
Determines the "truthyness" of an object.
-
__call__(<self>, ...) -> object
- here, any argument list can be defined as for normalpymethods
Iterable objects
Iterators can be defined using these methods:
__iter__(<self>) -> object
__next__(<self>) -> Option<object> or IterNextOutput
(see details)
Returning None
from __next__
indicates that that there are no further items.
Example:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct MyIterator { iter: Box<dyn Iterator<Item = PyObject> + Send>, } #[pymethods] impl 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, the iterable
only needs to implement __iter__()
while the iterator must implement both
__iter__()
and __next__()
. For example:
#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct Iter { inner: std::vec::IntoIter<usize>, } #[pymethods] impl 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>, } #[pymethods] impl 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.
Awaitable objects
__await__(<self>) -> object
__aiter__(<self>) -> object
__anext__(<self>) -> Option<object> or IterANextOutput
Mapping & Sequence types
-
__len__(<self>) -> usize
Implements the built-in function
len()
for the sequence. -
__contains__(<self>, object) -> 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.Disabling Python's default contains
By default, all
#[pyclass]
types with an__iter__
method support a default implementation of thein
operator. Types which do not want this can override this by setting__contains__
toNone
. This is the same mechanism as for a pure-Python class. This is done like so:#![allow(unused)] fn main() { use pyo3::prelude::*; #[pyclass] struct NoContains { } #[pymethods] impl NoContains { #[classattr] const __contains__: Option<PyObject> = None; } }
-
__getitem__(<self>, object) -> object
Implements retrieval of the
self[a]
element.Note: Negative integer indexes are not handled specially.
-
__setitem__(<self>, object, object) -> ()
Implements assignment to the
self[a]
element. Should only be implemented if elements can be replaced. -
__delitem__(<self>, object) -> ()
Implements deletion of the
self[a]
element. Should only be implemented if elements can be deleted.
-
fn __concat__(&self, other: impl FromPyObject) -> PyResult<impl ToPyObject>
Concatenates two sequences. Used by the
+
operator, after trying the numeric addition via the__add__
and__radd__
methods. -
fn __repeat__(&self, count: isize) -> PyResult<impl ToPyObject>
Repeats the sequence
count
times. Used by the*
operator, after trying the numeric multiplication via the__mul__
and__rmul__
methods. -
fn __inplace_concat__(&self, other: impl FromPyObject) -> PyResult<impl ToPyObject>
Concatenates two sequences. Used by the
+=
operator, after trying the numeric addition via the__iadd__
method. -
fn __inplace_repeat__(&self, count: isize) -> PyResult<impl ToPyObject>
Concatenates two sequences. Used by the
*=
operator, after trying the numeric multiplication via the__imul__
method.
Descriptors
__get__(<self>, object, object) -> object
__set__(<self>, object, object) -> ()
__delete__(<self>, object) -> ()
Numeric types
Binary arithmetic operations (+
, -
, *
, @
, /
, //
, %
, divmod()
,
pow()
and **
, <<
, >>
, &
, ^
, and |
) and their reflected versions:
(If the object
is not of the type specified in the signature, the generated code
will automatically return NotImplemented
.)
__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
In-place assignment operations (+=
, -=
, *=
, @=
, /=
, //=
, %=
,
**=
, <<=
, >>=
, &=
, ^=
, |=
):
__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) -> ()
Unary operations (-
, +
, abs()
and ~
):
__pos__(<self>) -> object
__neg__(<self>) -> object
__abs__(<self>) -> object
__invert__(<self>) -> object
Coercions:
__index__(<self>) -> object (int)
__int__(<self>) -> object (int)
__float__(<self>) -> object (float)
Buffer objects
__getbuffer__(<self>, *mut ffi::Py_buffer, flags) -> ()
__releasebuffer__(<self>, *mut ffi::Py_buffer)
(no return value, not evenPyResult
)
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 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.
__traverse__(<self>, pyo3::class::gc::PyVisit) -> Result<(), pyo3::class::gc::PyTraverseError>
__clear__(<self>) -> ()
Example:
#![allow(unused)] fn main() { use pyo3::prelude::*; use pyo3::PyTraverseError; use pyo3::gc::PyVisit; #[pyclass] struct ClassWithGCSupport { obj: Option<PyObject>, } #[pymethods] impl 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; } } }
#[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.
Due to complexity in the implementation and usage, these traits are 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.
fn __str__(&self) -> PyResult<impl ToPyObject<ObjectType=PyString>>
fn __repr__(&self) -> PyResult<impl ToPyObject<ObjectType=PyString>>
fn __hash__(&self) -> PyResult<impl PrimInt>
fn __richcmp__(&self, other: impl FromPyObject, op: CompareOp) -> PyResult<impl ToPyObject>
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<()>
fn __bool__(&self) -> PyResult<bool>
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.
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.
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, modulo: impl FromPyObject) -> PyResult<()>
on Python 3.8^fn __ipow__(&'p mut self, other: impl FromPyObject) -> PyResult<()>
on Python 3.7 see https://bugs.python.org/issue36379fn __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:
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>
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.
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>>>
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.
For details, look at the #[pymethods]
regarding iterator methods.
Garbage Collector Integration
Implement the PyGCProtocol
trait for your struct.
For details, look at the #[pymethods]
regarding GC methods.