PEP 670 – Convert macros to functions in the Python C API
- PEP
- 670
- Title
- Convert macros to functions in the Python C API
- Author
- Erlend Egeberg Aasland <erlend.aasland at protonmail.com>, Victor Stinner <vstinner at python.org>
- Status
- Draft
- Type
- Standards Track
- Created
- 19-Oct-2021
- Python-Version
- 3.11
Contents
- Abstract
- Rationale
- Macro Pitfalls
- Performance and inlining
- Specification
- Backwards Compatibility
- Rejected Ideas
- Examples of Macro Pitfalls
- Examples of hard to read macros
- Macros converted to functions since Python 3.8
- Benchmark comparing macros and static inline functions
- Post History
- References
- Version History
- Copyright
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 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()
inPyBool_FromLong()
:gcc -Og
: inlinedgcc -O0
: not inlined, callPy_INCREF()
function
- Call
_PyErr_Occurred()
in_Py_CheckFunctionResult()
:gcc -Og
: inlinedgcc -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:
“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),
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: “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. 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).
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. 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.
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 toPyObject_New()
PyObject_NEW_VAR()
: alias toPyObjectVar_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 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 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 mailing list threads:
References
- bpo-45490: [C API] PEP 670: Convert macros to functions in the Python C API (October 2021).
- What to do with unsafe macros (March 2021).
- bpo-43502: [C-API] Convert obvious unsafe macros to static inline functions (March 2021).
Version History
- Version 2:
- Stricter policy on not changing argument types and return type.
- Better explain why pointer arguments require a cast to not emit new compiler warnings.
- Macros which can be used as l-values are no longer modified by the PEP.
- Macros having multiple return types are no longer modified by the PEP.
- Limited C API version 3.11 no longer casts pointer arguments.
- No longer remove return values of macros “which should not have a return value”.
- Add “Macros converted to functions since Python 3.8” section.
- Add “Benchmark comparing macros and static inline functions” section.
- 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.
Source: https://github.com/python/peps/blob/main/pep-0670.rst
Last modified: 2022-02-22 12:42:29 GMT