PEP: 590
Title: Vectorcall: a fast calling protocol for CPython
Author: Mark Shannon <mark@hotpy.org>, Jeroen Demeyer <J.Demeyer@UGent.be>
BDFL-Delegate: Petr Viktorin <encukou@gmail.com>
Status: Accepted
Type: Standards Track
Content-Type: text/x-rst
Created: 29-Mar-2019
Python-Version: 3.8
Post-History:
Abstract
========
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.
Motivation
==========
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`` [2]_ 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 multiple indirections.
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 having the
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 expect
it to be finalized, and the underscores removed.
Specification
=============
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 type ``vectorcallfunc``.
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 external projects to backport the vectorcall protocol to earlier Python versions.
In particular, the Cython project has shown interest in doing that (see https://mail.python.org/pipermail/python-dev/2018-June/153927.html).
Descriptor behavior
-------------------
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 calling methods
(see ``_PyObject_GetMethod`` and the ``LOAD_METHOD``/``CALL_METHOD`` opcodes).
Concretely, if ``Py_TPFLAGS_METHOD_DESCRIPTOR`` is set for ``type(func)``, then:
- ``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 ``func(*args, **kwds)``.
There are no restrictions on the object ``func.__get__(obj, cls)``.
The latter is not required to implement the vectorcall protocol.
The call
--------
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 positional arguments plus possibly the ``PY_VECTORCALL_ARGUMENTS_OFFSET`` flag.
PY_VECTORCALL_ARGUMENTS_OFFSET
------------------------------
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 allocated vector.
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 calls cheaply.
The bytecode interpreter already allocates space on the stack for the callable,
so it can use this trick at no additional cost.
See [3]_ 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 ``PY_VECTORCALL_ARGUMENTS_OFFSET``.
The actual number of positional arguments is given by ``PyVectorcall_NARGS(nargs)``.
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 *dict)``:
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 ``nargs`` argument,
return the actual number of arguments.
Currently equivalent to ``nargs & ~PY_VECTORCALL_ARGUMENTS_OFFSET``.
Subclassing
-----------
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 class.
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
Python versions.
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 (``PyVectorcall_NARGS``,
``PyVectorcall_Call``, ``Py_TPFLAGS_METHOD_DESCRIPTOR``,
``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 calling convention.
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 [4]_ 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 functions,
third-party callables should include a ``vectorcallfunc`` function pointer,
set ``tp_vectorcall_offset`` to the correct value and add the ``_Py_TPFLAGS_HAVE_VECTORCALL`` flag.
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.
Stable ABI
==========
Nothing from this PEP is added to the stable ABI (:pep:`384`).
Alternative Suggestions
=======================
bpo-29259
---------
: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 bpo-29259.
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 their layout.
: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-negligible 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.
Acknowledgements
================
Victor Stinner for developing the original "fastcall" calling convention internally to CPython.
This PEP codifies and extends his work.
References
==========
.. [#bpo29259] Add tp_fastcall to PyTypeObject: support FASTCALL calling convention for all callable objects,
https://bugs.python.org/issue29259
.. [2] tp_call/PyObject_Call calling convention
https://docs.python.org/3/c-api/typeobj.html#c.PyTypeObject.tp_call
.. [3] Using PY_VECTORCALL_ARGUMENTS_OFFSET in callee
https://github.com/markshannon/cpython/blob/815cc1a30d85cdf2e3d77d21224db7055a1f07cb/Objects/classobject.c#L53
.. [4] Argument Clinic
https://docs.python.org/3/howto/clinic.html
Reference implementation
========================
A minimal implementation can be found at https://github.com/markshannon/cpython/tree/vectorcall-minimal
Copyright
=========
This document has been placed in the public domain.
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