[Python-Dev] PEP 590 (Vectorcall) discussion
Discussion on PEP 590 (Vectorcall) has been split over several PRs,
issues and e-mails, so let me post an update.
I am planning to approve PEP 590 with the following changes, if Mark
doesn't object to them:
* https://github.com/python/peps/pull/1064 (Mark the main API as private
to allow changes in Python 3.9)
* https://github.com/python/peps/pull/1066 (Use size_t for "number of
arguments + flag")
The resulting text, for reference:
Title: Vectorcall: a fast calling protocol for CPython
Author: Mark Shannon <mark at hotpy.org>, Jeroen Demeyer <J.Demeyer at UGent.be>
BDFL-Delegate: Petr Viktorin <encukou at gmail.com>
Type: Standards Track
This PEP introduces a new C API to optimize calls of objects.
It introduces a new "vectorcall" protocol and calling convention.
This is based on the "fastcall" convention, which is already used
internally by CPython.
The new features can be used by any user-defined extension class.
Most of the new API is private in CPython 3.8.
The plan is to finalize semantics and make it public in Python 3.9.
**NOTE**: This PEP deals only with the Python/C API,
it does not affect the Python language or standard library.
The choice of a calling convention impacts the performance and
flexibility of code on either side of the call.
Often there is tension between performance and flexibility.
The current ``tp_call`` _ calling convention is sufficiently flexible
to cover all cases, but its performance is poor.
The poor performance is largely a result of having to create
intermediate tuples, and possibly intermediate dicts, during the call.
This is mitigated in CPython by including special-case code to speed up
calls to Python and builtin functions.
Unfortunately, this means that other callables such as classes and third
party extension objects are called using the
slower, more general ``tp_call`` calling convention.
This PEP proposes that the calling convention used internally for Python
and builtin functions is generalized and published
so that all calls can benefit from better performance.
The new proposed calling convention is not fully general, but covers the
large majority of calls.
It is designed to remove the overhead of temporary object creation and
Another source of inefficiency in the ``tp_call`` convention is that it
has one function pointer per class,
rather than per object.
This is inefficient for calls to classes as several intermediate objects
need to be created.
For a class ``cls``, at least one intermediate object is created for
each call in the sequence
``type.__call__``, ``cls.__new__``, ``cls.__init__``.
This PEP proposes an interface for use by extension modules.
Such interfaces cannot effectively be tested, or designed, without
consumers in the loop.
For that reason, we provide private (underscore-prefixed) names.
The API may change (based on consumer feedback) in Python 3.9, where we
it to be finalized, and the underscores removed.
The function pointer type
Calls are made through a function pointer taking the following parameters:
* ``PyObject *callable``: The called object
* ``PyObject *const *args``: A vector of arguments
* ``size_t nargs``: The number of arguments plus the optional flag
``PY_VECTORCALL_ARGUMENTS_OFFSET`` (see below)
* ``PyObject *kwnames``: Either ``NULL`` or a tuple with the names of
the keyword arguments
This is implemented by the function pointer type:
``typedef PyObject *(*vectorcallfunc)(PyObject *callable, PyObject
*const *args, size_t nargs, PyObject *kwnames);``
Changes to the ``PyTypeObject`` struct
The unused slot ``printfunc tp_print`` is replaced with
``tp_vectorcall_offset``. It has the type ``Py_ssize_t``.
A new ``tp_flags`` flag is added, ``_Py_TPFLAGS_HAVE_VECTORCALL``,
which must be set for any class that uses the vectorcall protocol.
If ``_Py_TPFLAGS_HAVE_VECTORCALL`` is set, then ``tp_vectorcall_offset``
must be a positive integer.
It is the offset into the object of the vectorcall function pointer of
This pointer may be ``NULL``, in which case the behavior is the same as
if ``_Py_TPFLAGS_HAVE_VECTORCALL`` was not set.
The ``tp_print`` slot is reused as the ``tp_vectorcall_offset`` slot to
make it easier for for external projects to backport the vectorcall
protocol to earlier Python versions.
In particular, the Cython project has shown interest in doing that (see
One additional type flag is specified: ``Py_TPFLAGS_METHOD_DESCRIPTOR``.
``Py_TPFLAGS_METHOD_DESCRIPTOR`` should be set if the callable uses the
descriptor protocol to create a bound method-like object.
This is used by the interpreter to avoid creating temporary objects when
(see ``_PyObject_GetMethod`` and the ``LOAD_METHOD``/``CALL_METHOD``
Concretely, if ``Py_TPFLAGS_METHOD_DESCRIPTOR`` is set for
- ``func.__get__(obj, cls)(*args, **kwds)`` (with ``obj`` not None)
must be equivalent to ``func(obj, *args, **kwds)``.
- ``func.__get__(None, cls)(*args, **kwds)`` must be equivalent to
There are no restrictions on the object ``func.__get__(obj, cls)``.
The latter is not required to implement the vectorcall protocol.
The call takes the form ``((vectorcallfunc)(((char *)o)+offset))(o,
args, n, kwnames)`` where
``offset`` is ``Py_TYPE(o)->tp_vectorcall_offset``.
The caller is responsible for creating the ``kwnames`` tuple and
ensuring that there are no duplicates in it.
``n`` is the number of postional arguments plus possibly the
The flag ``PY_VECTORCALL_ARGUMENTS_OFFSET`` should be added to ``n``
if the callee is allowed to temporarily change ``args[-1]``.
In other words, this can be used if ``args`` points to argument 1 in the
The callee must restore the value of ``args[-1]`` before returning.
Whenever they can do so cheaply (without allocation), callers are
encouraged to use ``PY_VECTORCALL_ARGUMENTS_OFFSET``.
Doing so will allow callables such as bound methods to make their onward
The bytecode interpreter already allocates space on the stack for the
so it can use this trick at no additional cost.
See _ for an example of how ``PY_VECTORCALL_ARGUMENTS_OFFSET`` is
used by a callee to avoid allocation.
For getting the actual number of arguments from the parameter ``n``,
the macro ``PyVectorcall_NARGS(n)`` must be used.
This allows for future changes or extensions.
New C API and changes to CPython
The following functions or macros are added to the C API:
- ``PyObject *_PyObject_Vectorcall(PyObject *obj, PyObject *const *args,
size_t nargs, PyObject *keywords)``:
Calls ``obj`` with the given arguments.
Note that ``nargs`` may include the flag
The actual number of positional arguments is given by
The argument ``keywords`` is a tuple of keyword names or ``NULL``.
An empty tuple has the same effect as passing ``NULL``.
This uses either the vectorcall protocol or ``tp_call`` internally;
if neither is supported, an exception is raised.
- ``PyObject *PyVectorcall_Call(PyObject *obj, PyObject *tuple, PyObject
Call the object (which must support vectorcall) with the old
``*args`` and ``**kwargs`` calling convention.
This is mostly meant to put in the ``tp_call`` slot.
- ``Py_ssize_t PyVectorcall_NARGS(size_t nargs)``: Given a vectorcall
return the actual number of arguments.
Currently equivalent to ``nargs & ~PY_VECTORCALL_ARGUMENTS_OFFSET``.
Extension types inherit the type flag ``_Py_TPFLAGS_HAVE_VECTORCALL``
and the value ``tp_vectorcall_offset`` from the base class,
provided that they implement ``tp_call`` the same way as the base class.
Additionally, the flag ``Py_TPFLAGS_METHOD_DESCRIPTOR``
is inherited if ``tp_descr_get`` is implemented the same way as the base
Heap types never inherit the vectorcall protocol because
that would not be safe (heap types can be changed dynamically).
This restriction may be lifted in the future, but that would require
special-casing ``__call__`` in ``type.__setattribute__``.
Finalizing the API
The underscore in the names ``_PyObject_Vectorcall`` and
``_Py_TPFLAGS_HAVE_VECTORCALL`` indicates that this API may change in minor
When finalized (which is planned for Python 3.9), they will be renamed to
``PyObject_Vectorcall`` and ``Py_TPFLAGS_HAVE_VECTORCALL``.
The old underscore-prefixed names will remain available as aliases.
The new API will be documented as normal, but will warn of the above.
Semantics for the other names introduced in this PEP
``PY_VECTORCALL_ARGUMENTS_OFFSET``) are final.
Internal CPython changes
Changes to existing classes
The ``function``, ``builtin_function_or_method``, ``method_descriptor``,
``method``, ``wrapper_descriptor``, ``method-wrapper``
classes will use the vectorcall protocol
(not all of these will be changed in the initial implementation).
For ``builtin_function_or_method`` and ``method_descriptor``
(which use the ``PyMethodDef`` data structure),
one could implement a specific vectorcall wrapper for every existing
Whether or not it is worth doing that remains to be seen.
Using the vectorcall protocol for classes
For a class ``cls``, creating a new instance using ``cls(xxx)``
requires multiple calls.
At least one intermediate object is created for each call in the sequence
``type.__call__``, ``cls.__new__``, ``cls.__init__``.
So it makes a lot of sense to use vectorcall for calling classes.
This really means implementing the vectorcall protocol for ``type``.
Some of the most commonly used classes will use this protocol,
probably ``range``, ``list``, ``str``, and ``type``.
The ``PyMethodDef`` protocol and Argument Clinic
Argument Clinic _ automatically generates wrapper functions around
lower-level callables, providing safe unboxing of primitive types and
other safety checks.
Argument Clinic could be extended to generate wrapper objects conforming
to the new ``vectorcall`` protocol.
This will allow execution to flow from the caller to the Argument Clinic
generated wrapper and
thence to the hand-written code with only a single indirection.
Third-party extension classes using vectorcall
To enable call performance on a par with Python functions and built-in
third-party callables should include a ``vectorcallfunc`` function pointer,
set ``tp_vectorcall_offset`` to the correct value and add the
Any class that does this must implement the ``tp_call`` function and
make sure its behaviour is consistent with the ``vectorcallfunc`` function.
Setting ``tp_call`` to ``PyVectorcall_Call`` is sufficient.
Performance implications of these changes
This PEP should not have much impact on the performance of existing code
(neither in the positive nor the negative sense).
It is mainly meant to allow efficient new code to be written,
not to make existing code faster.
Nevertheless, this PEP optimizes for ``METH_FASTCALL`` functions.
Performance of functions using ``METH_VARARGS`` will become slightly worse.
Nothing from this PEP is added to the stable ABI (PEP 384).
PEP 590 is close to what was proposed in bpo-29259 [#bpo29259]_.
The main difference is that this PEP stores the function pointer
in the instance rather than in the class.
This makes more sense for implementing functions in C,
where every instance corresponds to a different C function.
It also allows optimizing ``type.__call__``, which is not possible with
PEP 576 and PEP 580
Both PEP 576 and PEP 580 are designed to enable 3rd party objects to be
both expressive and performant (on a par with
CPython objects). The purpose of this PEP is provide a uniform way to
call objects in the CPython ecosystem that is
both expressive and as performant as possible.
This PEP is broader in scope than PEP 576 and uses variable rather than
fixed offset function-pointers.
The underlying calling convention is similar. Because PEP 576 only
allows a fixed offset for the function pointer,
it would not allow the improvements to any objects with constraints on
PEP 580 proposes a major change to the ``PyMethodDef`` protocol used to
define builtin functions.
This PEP provides a more general and simpler mechanism in the form of a
new calling convention.
This PEP also extends the ``PyMethodDef`` protocol, but merely to
formalise existing conventions.
Other rejected approaches
A longer, 6 argument, form combining both the vector and optional tuple
and dictionary arguments was considered.
However, it was found that the code to convert between it and the old
``tp_call`` form was overly cumbersome and inefficient.
Also, since only 4 arguments are passed in registers on x64 Windows, the
two extra arguments would have non-neglible costs.
Removing any special cases and making all calls use the ``tp_call`` form
was also considered.
However, unless a much more efficient way was found to create and
destroy tuples, and to a lesser extent dictionaries,
then it would be too slow.
Victor Stinner for developing the original "fastcall" calling convention
internally to CPython.
This PEP codifies and extends his work.
.. [#bpo29259] Add tp_fastcall to PyTypeObject: support FASTCALL calling
convention for all callable objects,
..  tp_call/PyObject_Call calling convention
..  Using PY_VECTORCALL_ARGUMENTS_OFFSET in callee
..  Argument Clinic
A minimal implementation can be found at
This document has been placed in the public domain.