python-peps/pep-0670.rst

PEP: 670
Title: Convert macros to functions in the Python C API
Author: Erlend Egeberg Aasland <erlend.aasland@protonmail.com>,
        Victor Stinner <vstinner@python.org>
Status: Draft
Type: Standards Track
Content-Type: text/x-rst
Created: 19-Oct-2021
Python-Version: 3.11


Abstract
========

Convert macros to static inline functions or regular functions to avoid
macro pitfalls.

Convert macros and static inline functions to regular functions to make
them usable by Python extensions which cannot use macros or static
inline functions, like extensions written in a programming languages
other than C or C++.

Function arguments of pointer types are still cast and return types are
not changed to prevent emitting new compiler warnings.

Macros which can be used as l-value in an assignment are not converted
to functions to avoid introducing incompatible changes.


Rationale
=========

The use of macros may have unintended adverse effects that are hard to
avoid, even for experienced C developers. Some issues have been known
for years, while others have been discovered recently in Python.
Working around macro pitfalls makes the macro coder harder to read and
to maintain.

Converting macros to functions has multiple advantages:

* By design, functions don't have macro pitfalls.
* Arguments type and return type are well defined.
* Debuggers and profilers can retrieve the name of inlined functions.
* Debuggers can put breakpoints on inlined functions.
* Variables have a well defined scope.
* Code is usually easier to read and to maintain than similar macro
  code.  Functions don't need the following workarounds for macro
  pitfalls:

  * Add parentheses around arguments.
  * Use line continuation characters if the function is written on
    multiple lines.
  * Add commas to execute multiple expressions.
  * Use ``do { ... } while (0)`` to write multiple statements.

Converting macros and static inline functions to regular functions makes
these regular functions accessible to projects which use Python but
cannot use macros and static inline functions.


Macro Pitfalls
==============

The `GCC documentation
<https://gcc.gnu.org/onlinedocs/cpp/Macro-Pitfalls.html>`_ lists several
common macro pitfalls:

- Misnesting
- Operator precedence problems
- Swallowing the semicolon
- Duplication of side effects
- Self-referential macros
- Argument prescan
- Newlines in arguments


Performance and inlining
========================

Static inline functions is a feature added to the C99 standard. Modern C
compilers have efficient heuristics to decide if a function should be
inlined or not.

When a C compiler decides to not inline, there is likely a good reason.
For example, inlining would reuse a register which requires to
save/restore the register value on the stack and so increases the stack
memory usage, or be less efficient.


Debug build
-----------

Benchmarks must not be run on a Python debug build, only on release
build. Moreover, using LTO and PGO optimizations is recommended for best
performances and reliable benchmarks. PGO helps the compiler to decide
if function should be inlined or not.

``./configure --with-pydebug`` uses the ``-Og`` compiler option if it's
supported by the compiler (GCC and LLVM Clang support it): optimize
debugging experience. Otherwise, the ``-O0`` compiler option is used:
disable most optimizations.

With GCC 11, ``gcc -Og`` can inline static inline functions, whereas
``gcc -O0`` does not inline static inline functions. Examples:

* Call ``Py_INCREF()`` in ``PyBool_FromLong()``:

  * ``gcc -Og``: inlined
  * ``gcc -O0``: not inlined, call ``Py_INCREF()`` function

* Call ``_PyErr_Occurred()`` in ``_Py_CheckFunctionResult()``:

  * ``gcc -Og``: inlined
  * ``gcc -O0``: not inlined, call ``_PyErr_Occurred()`` function

On Windows, when Python is built in debug mode by Visual Studio, static
inline functions are not inlined.


Force inlining
--------------

The ``Py_ALWAYS_INLINE`` macro can be used to force inlining. This macro
uses ``__attribute__((always_inline))`` with GCC and Clang, and
``__forceinline`` with MSC.

Previous attempts to use ``Py_ALWAYS_INLINE`` didn't show any benefit, and were
abandoned. See for example: `bpo-45094 <https://bugs.python.org/issue45094>`_:
"Consider using ``__forceinline`` and ``__attribute__((always_inline))`` on
static inline functions (``Py_INCREF``, ``Py_TYPE``) for debug build".

When the ``Py_INCREF()`` macro was converted to a static inline
functions in 2018 (`commit
<https://github.com/python/cpython/commit/2aaf0c12041bcaadd7f2cc5a54450eefd7a6ff12>`__),
it was decided not to force inlining. The machine code was analyzed with
multiple C compilers and compiler options: ``Py_INCREF()`` was always
inlined without having to force inlining. The only case where it was not
inlined was the debug build. See discussion in the `bpo-35059
<https://bugs.python.org/issue35059>`_: "Convert ``Py_INCREF()`` and
``PyObject_INIT()`` to inlined functions".


Disable inlining
----------------

On the other side, the ``Py_NO_INLINE`` macro can be used to disable
inlining.  It can be used to reduce the stack memory usage, or to prevent
inlining on LTO+PGO builds, which are generally more aggressive to inline
code: see `bpo-33720 <https://bugs.python.org/issue33720>`_. The
``Py_NO_INLINE`` macro uses ``__attribute__ ((noinline))`` with GCC and
Clang, and ``__declspec(noinline)`` with MSC.


Specification
=============

Convert macros to static inline functions
-----------------------------------------

Most macros should be converted to static inline functions to prevent
`macro pitfalls`_.

The following macros should not be converted:

* Empty macros. Example: ``#define Py_HAVE_CONDVAR``.
* Macros only defining a number, even if a constant with a well defined
  type can better. Example: ``#define METH_VARARGS 0x0001``.
* Compatibility layer for different C compilers, C language extensions,
  or recent C features.
  Example: ``#define Py_ALWAYS_INLINE __attribute__((always_inline))``.
* Macros that need C preprocessor features, like stringification and
  concatenation. Example: ``Py_STRINGIFY()``.
* Macros which can be used as l-value in an assignment. This change is
  an incompatible change and is out of the scope of this PEP.
  Example: ``PyBytes_AS_STRING()``.
* Macros having different return types depending on the code path.


Convert static inline functions to regular functions
----------------------------------------------------

The performance impact of converting static inline functions to regular
functions should be measured with benchmarks. If there is a significant
slowdown, there should be a good reason to do the conversion. One reason
can be hiding implementation details.

To avoid any risk of performance slowdown on Python built without LTO,
it is possible to keep a private static inline function in the internal
C API and use it in Python, but expose a regular function in the public
C API.

Using static inline functions in the internal C API is fine: the
internal C API exposes implementation details by design and should not be
used outside Python.

Cast pointer arguments
----------------------

Existing cast
'''''''''''''

Currently, most macros accepting pointers cast pointer arguments to
their expected types. For example, in Python 3.6, the ``Py_TYPE()``
macro casts its argument to ``PyObject*``::

    #define Py_TYPE(ob) (((PyObject*)(ob))->ob_type)

The ``Py_TYPE()`` macro accepts the ``PyObject*`` type, but also any
pointer types, such as ``PyLongObject*`` and ``PyDictObject*``.

Add a new macro to keep the cast
''''''''''''''''''''''''''''''''

When a macro is converted to a function and the macro casts at least one
of its arguments, a new macro is added to keep the cast. The new macro
and the function have the same name. Example with the ``Py_TYPE()``
macro converted to a static inline function::

    static inline PyTypeObject* Py_TYPE(PyObject *ob) {
        return ob->ob_type;
    }
    #define Py_TYPE(ob) Py_TYPE((PyObject*)(ob))

The cast is kept for all pointer types, not only ``PyObject*``.

Removing a cast to ``void*`` would emit a new warning if the function is
called with a variable of ``const void*`` type. For example, the
``PyUnicode_WRITE()`` macro casts its *data* argument to ``void*``, and
so accepts ``const void*`` type, even if it writes into *data*.

Avoid the cast in the limited C API version 3.11
''''''''''''''''''''''''''''''''''''''''''''''''

The cast is removed from the limited C API version 3.11 and newer: the
caller must pass the expected type, or perform the cast. An example with
the ``Py_TYPE()`` function::

    static inline PyTypeObject* Py_TYPE(PyObject *ob) {
        return ob->ob_type;
    }
    #if !defined(Py_LIMITED_API) || Py_LIMITED_API+0 < 0x030b0000
    #  define Py_TYPE(ob) Py_TYPE((PyObject*)(ob))
    #endif


Return type is not changed
--------------------------

When a macro is converted to a function, its return type must not change
to prevent emitting new compiler warnings.

For example, Python 3.7 changed ``PyUnicode_AsUTF8()`` return type from
``char*`` to ``const char*`` (`commit
<https://github.com/python/cpython/commit/2a404b63d48d73bbaa007d89efb7a01048475acd>`__).
The change emitted new compiler warnings when building C extensions
expecting ``char*``. This PEP doesn't change the return type to prevent
this issue.


Backwards Compatibility
=======================

The PEP is designed to avoid C API incompatible changes.

Only C extensions explicitly targeting the limited C API version 3.11
must now pass the expected types to functions: pointer arguments are no
longer cast to the expected types.

Function arguments of pointer types are still cast and return types are
not changed to prevent emitting new compiler warnings.

Macros which can be used as l-value in an assignment are not modified by
this PEP to avoid incompatible changes.


Rejected Ideas
==============

Keep macros, but fix some macro issues
--------------------------------------

Macros are always "inlined" with any C compiler.

The duplication of side effects can be worked around in the caller of
the macro.

People using macros should be considered "consenting adults". People who
feel unsafe with macros should simply not use them.

These ideas are rejected because macros _are_ error prone, and it is too easy
to miss a macro pitfall when writing and reviewing macro code. Moreover, macros
are harder to read and maintain than functions.


Examples of Macro Pitfalls
==========================

Duplication of side effects
---------------------------

Macros::

    #define PySet_Check(ob) \
        (Py_IS_TYPE(ob, &PySet_Type) \
         || PyType_IsSubtype(Py_TYPE(ob), &PySet_Type))

    #define Py_IS_NAN(X) ((X) != (X))

If the *op* or the *X* argument has a side effect, the side effect is
duplicated: it executed twice by ``PySet_Check()`` and ``Py_IS_NAN()``.

For example, the ``pos++`` argument in the
``PyUnicode_WRITE(kind, data, pos++, ch)`` code has a side effect.
This code is safe because the ``PyUnicode_WRITE()`` macro only uses its
3rd argument once and so does not duplicate ``pos++`` side effect.

Misnesting
----------

Example of the `bpo-43181: Python macros don't shield arguments
<https://bugs.python.org/issue43181>`_. The ``PyObject_TypeCheck()``
macro before it has been fixed::

    #define PyObject_TypeCheck(ob, tp) \
        (Py_IS_TYPE(ob, tp) || PyType_IsSubtype(Py_TYPE(ob), (tp)))

C++ usage example::

    PyObject_TypeCheck(ob, U(f<a,b>(c)))

The preprocessor first expands it::

    (Py_IS_TYPE(ob, f<a,b>(c)) || ...)

C++ ``"<"`` and ``">"`` characters are not treated as brackets by the
preprocessor, so the ``Py_IS_TYPE()`` macro is invoked with 3 arguments:

* ``ob``
* ``f<a``
* ``b>(c)``

The compilation fails with an error on ``Py_IS_TYPE()`` which only takes
2 arguments.

The bug is that the *op* and *tp* arguments of ``PyObject_TypeCheck()``
must be put between parentheses: replace ``Py_IS_TYPE(ob, tp)`` with
``Py_IS_TYPE((ob), (tp))``. In regular C code, these parentheses are
redundant, can be seen as a bug, and so are often forgotten when writing
macros.

To avoid Macro Pitfalls, the ``PyObject_TypeCheck()`` macro has been
converted to a static inline function:
`commit <https://github.com/python/cpython/commit/4bb2a1ebc569eee6f1b46ecef1965a26ae8cb76d>`__.


Examples of hard to read macros
===============================

PyObject_INIT()
---------------

Example showing the usage of commas in a macro which has a return value.

Python 3.7 macro::

    #define PyObject_INIT(op, typeobj) \
        ( Py_TYPE(op) = (typeobj), _Py_NewReference((PyObject *)(op)), (op) )

Python 3.8 function (simplified code)::

    static inline PyObject*
    _PyObject_INIT(PyObject *op, PyTypeObject *typeobj)
    {
        Py_TYPE(op) = typeobj;
        _Py_NewReference(op);
        return op;
    }

    #define PyObject_INIT(op, typeobj) \
        _PyObject_INIT(_PyObject_CAST(op), (typeobj))

* The function doesn't need the line continuation character ``"\"``.
* It has an explicit ``"return op;"`` rather than the surprising
  ``", (op)"`` syntax at the end of the macro.
* It uses short statements on multiple lines, rather than being written
  as a single long line.
* Inside the function, the *op* argument has the well defined type
  ``PyObject*`` and so doesn't need casts like ``(PyObject *)(op)``.
* Arguments don't need to be put inside parentheses: use ``typeobj``,
  rather than ``(typeobj)``.

_Py_NewReference()
------------------

Example showing the usage of an ``#ifdef`` inside a macro.

Python 3.7 macro (simplified code)::

    #ifdef COUNT_ALLOCS
    #  define _Py_INC_TPALLOCS(OP) inc_count(Py_TYPE(OP))
    #  define _Py_COUNT_ALLOCS_COMMA  ,
    #else
    #  define _Py_INC_TPALLOCS(OP)
    #  define _Py_COUNT_ALLOCS_COMMA
    #endif /* COUNT_ALLOCS */

    #define _Py_NewReference(op) (                   \
        _Py_INC_TPALLOCS(op) _Py_COUNT_ALLOCS_COMMA  \
        Py_REFCNT(op) = 1)

Python 3.8 function (simplified code)::

    static inline void _Py_NewReference(PyObject *op)
    {
        _Py_INC_TPALLOCS(op);
        Py_REFCNT(op) = 1;
    }


PyUnicode_READ_CHAR()
---------------------

This macro reuses arguments, and possibly calls ``PyUnicode_KIND`` multiple
times::

    #define PyUnicode_READ_CHAR(unicode, index) \
    (assert(PyUnicode_Check(unicode)),          \
     assert(PyUnicode_IS_READY(unicode)),       \
     (Py_UCS4)                                  \
        (PyUnicode_KIND((unicode)) == PyUnicode_1BYTE_KIND ? \
            ((const Py_UCS1 *)(PyUnicode_DATA((unicode))))[(index)] : \
            (PyUnicode_KIND((unicode)) == PyUnicode_2BYTE_KIND ? \
                ((const Py_UCS2 *)(PyUnicode_DATA((unicode))))[(index)] : \
                ((const Py_UCS4 *)(PyUnicode_DATA((unicode))))[(index)] \
            ) \
        ))

Possible implementation as a static inlined function::

    static inline Py_UCS4
    PyUnicode_READ_CHAR(PyObject *unicode, Py_ssize_t index)
    {
        assert(PyUnicode_Check(unicode));
        assert(PyUnicode_IS_READY(unicode));

        switch (PyUnicode_KIND(unicode)) {
        case PyUnicode_1BYTE_KIND:
            return (Py_UCS4)((const Py_UCS1 *)(PyUnicode_DATA(unicode)))[index];
        case PyUnicode_2BYTE_KIND:
            return (Py_UCS4)((const Py_UCS2 *)(PyUnicode_DATA(unicode)))[index];
        case PyUnicode_4BYTE_KIND:
        default:
            return (Py_UCS4)((const Py_UCS4 *)(PyUnicode_DATA(unicode)))[index];
        }
    }


Macros converted to functions since Python 3.8
==============================================

List of macros already converted to functions between Python 3.8 and
Python 3.11 showing that these conversions didn't not impact the Python
performance and didn't break the backward compatibility, even if some
converted macros are very commonly used by C extensions like
``Py_INCREF()``.

Macros converted to static inline functions
-------------------------------------------

Python 3.8:

* ``Py_DECREF()``
* ``Py_INCREF()``
* ``Py_XDECREF()``
* ``Py_XINCREF()``
* ``PyObject_INIT()``
* ``PyObject_INIT_VAR()``
* ``_PyObject_GC_UNTRACK()``
* ``_Py_Dealloc()``

Macros converted to regular functions
-------------------------------------

Python 3.9:

* ``PyIndex_Check()``
* ``PyObject_CheckBuffer()``
* ``PyObject_GET_WEAKREFS_LISTPTR()``
* ``PyObject_IS_GC()``
* ``PyObject_NEW()``: alias to ``PyObject_New()``
* ``PyObject_NEW_VAR()``: alias to ``PyObjectVar_New()``

To avoid any risk of performance slowdown on Python built without LTO,
private static inline functions have been added to the internal C API:

* ``_PyIndex_Check()``
* ``_PyObject_IS_GC()``
* ``_PyType_HasFeature()``
* ``_PyType_IS_GC()``


Static inline functions converted to regular functions
-------------------------------------------------------

Python 3.11:

* ``PyObject_CallOneArg()``
* ``PyObject_Vectorcall()``
* ``PyVectorcall_Function()``
* ``_PyObject_FastCall()``

To avoid any risk of performance slowdown on Python built without LTO, a
private static inline function has been added to the internal C API:

* ``_PyVectorcall_FunctionInline()``


Incompatible changes
--------------------

While other converted macros didn't break the backward compatibility,
there is an exception.

The 3 macros ``Py_REFCNT()``, ``Py_TYPE()`` and ``Py_SIZE()`` have been
converted to static inline functions in Python 3.10 and 3.11 to disallow
using them as l-value in assignment. It is an incompatible change made
on purpose: see `bpo-39573 <https://bugs.python.org/issue39573>`_ for
the rationale.

This PEP does not convert macros which can be used as l-value to avoid
introducing incompatible changes.


Benchmark comparing macros and static inline functions
======================================================

Benchmark run on Fedora 35 (Linux) with GCC 11 on a laptop with 8
logical CPUs (4 physical CPU cores).

The `PR 29728 <https://github.com/python/cpython/pull/29728>`_ replaces
existing the following static inline functions with macros:

* ``PyObject_TypeCheck()``
* ``PyType_Check()``, ``PyType_CheckExact()``
* ``PyType_HasFeature()``
* ``PyVectorcall_NARGS()``
* ``Py_DECREF()``, ``Py_XDECREF()``
* ``Py_INCREF()``, ``Py_XINCREF()``
* ``Py_IS_TYPE()``
* ``Py_NewRef()``
* ``Py_REFCNT()``, ``Py_TYPE()``, ``Py_SIZE()``


When static inline functions are inlined: Release build
-------------------------------------------------------

Benchmark of the ``./python -m test -j5`` command on Python built in
release mode with ``gcc -O3``, LTO and PGO:

* Macros (PR 29728): 361 sec +- 1 sec
* Static inline functions (reference): 361 sec +- 1 sec

There is **no significant performance difference** between macros and
static inline functions when static inline functions **are inlined**.


When static inline functions are not inlined: Debug build and -O0
-----------------------------------------------------------------

Benchmark of the ``./python -m test -j10`` command on Python built in
debug mode with ``gcc -O0`` (explicitly disable compiler optimizations):

* Macros (PR 29728): 345 sec ± 5 sec
* Static inline functions (reference): 360 sec ± 6 sec

Replacing macros with static inline functions makes Python
**1.04x slower** when the compiler **does not inline** static inline
functions.


Post History
============

* python-dev: `PEP 670: Convert macros to functions in the Python C API
  <https://mail.python.org/archives/list/python-dev@python.org/thread/2GN646CGWGTO6ZHHU7JTA5XWDF4ULM77/>`_
  (October 2021)


References
==========

* `bpo-45490 <https://bugs.python.org/issue45490>`_:
  [meta][C API] Avoid C macro pitfalls and usage of static inline
  functions (October 2021).
* `What to do with unsafe macros
  <https://discuss.python.org/t/what-to-do-with-unsafe-macros/7771>`_
  (March 2021).
* `bpo-43502 <https://bugs.python.org/issue43502>`_:
  [C-API] Convert obvious unsafe macros to static inline functions
  (March 2021).


Version History
===============

* Version 2: No longer remove return values; remove argument casting
  from the limited C API.
* Version 1: First public version


Copyright
=========

This document is placed in the public domain or under the
CC0-1.0-Universal license, whichever is more permissive.