PEP 590 – Vectorcall: a fast calling protocol for CPython
- Vectorcall: a fast calling protocol for CPython
- Mark Shannon <mark at hotpy.org>, Jeroen Demeyer <J.Demeyer at UGent.be>
- Petr Viktorin <encukou at gmail.com>
- Standards Track
- New C API and changes to CPython
- Finalizing the API
- Internal CPython changes
- Third-party extension classes using vectorcall
- Performance implications of these changes
- Stable ABI
- Alternative Suggestions
- Reference implementation
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.
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 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
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.
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
PyObject *kwnames: Either
NULLor 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
The unused slot
printfunc tp_print is replaced with
tp_vectorcall_offset. It has the type
tp_flags flag is added,
which must be set for any class that uses the vectorcall protocol.
_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
This pointer may be
NULL, in which case the behavior is the same as if
_Py_TPFLAGS_HAVE_VECTORCALL was not set.
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).
One additional type flag is specified:
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
_PyObject_GetMethod and the
Py_TPFLAGS_METHOD_DESCRIPTOR is set for
func.__get__(obj, cls)(*args, **kwds)(with
objnot 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
The latter is not required to implement the vectorcall protocol.
The call takes the form
((vectorcallfunc)(((char *)o)+offset))(o, args, n, kwnames) where
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 should be added to
if the callee is allowed to temporarily change
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
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  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
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
objwith the given arguments. Note that
nargsmay include the flag
PY_VECTORCALL_ARGUMENTS_OFFSET. The actual number of positional arguments is given by
PyVectorcall_NARGS(nargs). The argument
keywordsis 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_callinternally; 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
**kwargscalling convention. This is mostly meant to put in the
Py_ssize_t PyVectorcall_NARGS(size_t nargs): Given a vectorcall
nargsargument, return the actual number of arguments. Currently equivalent to
nargs & ~PY_VECTORCALL_ARGUMENTS_OFFSET.
Extension types inherit the type flag
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
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
Finalizing the API
The underscore in the names
_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
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
classes will use the vectorcall protocol
(not all of these will be changed in the initial implementation).
(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
requires multiple calls.
At least one intermediate object is created for each call in the sequence
So it makes a lot of sense to use vectorcall for calling classes.
This really means implementing the vectorcall protocol for
Some of the most commonly used classes will use this protocol,
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
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,
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
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
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 .
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.
Victor Stinner for developing the original “fastcall” calling convention internally to CPython. This PEP codifies and extends his work.
- Add tp_fastcall to PyTypeObject: support FASTCALL calling convention for all callable objects, https://bugs.python.org/issue29259
- tp_call/PyObject_Call calling convention https://docs.python.org/3/c-api/typeobj.html#c.PyTypeObject.tp_call
- Using PY_VECTORCALL_ARGUMENTS_OFFSET in callee https://github.com/markshannon/cpython/blob/815cc1a30d85cdf2e3d77d21224db7055a1f07cb/Objects/classobject.c#L53
- Argument Clinic https://docs.python.org/3/howto/clinic.html
A minimal implementation can be found at https://github.com/markshannon/cpython/tree/vectorcall-minimal
This document has been placed in the public domain.
Last modified: 2022-02-01 02:49:58 GMT