Python support for the Linux "perf" profiler
********************************************

auteur:
   Pablo Galindo

The Linux perf profiler is a very powerful tool that allows you to
profile and obtain information about the performance of your
application. "perf" also has a very vibrant ecosystem of tools that
aid with the analysis of the data that it produces.

The main problem with using the "perf" profiler with Python
applications is that "perf" only gets information about native
symbols, that is, the names of functions and procedures written in C.
This means that the names and file names of Python functions in your
code will not appear in the output of "perf".

Since Python 3.12, the interpreter can run in a special mode that
allows Python functions to appear in the output of the "perf"
profiler. When this mode is enabled, the interpreter will interpose a
small piece of code compiled on the fly before the execution of every
Python function and it will teach "perf" the relationship between this
piece of code and the associated Python function using perf map files.

Note:

  Support for the "perf" profiler is currently only available for
  Linux on select architectures. Check the output of the "configure"
  build step or check the output of "python -m sysconfig | grep
  HAVE_PERF_TRAMPOLINE" to see if your system is supported.

For example, consider the following script:

   def foo(n):
       result = 0
       for _ in range(n):
           result += 1
       return result

   def bar(n):
       foo(n)

   def baz(n):
       bar(n)

   if __name__ == "__main__":
       baz(1000000)

We can run "perf" to sample CPU stack traces at 9999 hertz:

   $ perf record -F 9999 -g -o perf.data python my_script.py

Then we can use "perf report" to analyze the data:

   $ perf report --stdio -n -g

   # Children      Self       Samples  Command     Shared Object       Symbol
   # ........  ........  ............  ..........  ..................  ..........................................
   #
       91.08%     0.00%             0  python.exe  python.exe          [.] _start
               |
               ---_start
               |
                   --90.71%--__libc_start_main
                           Py_BytesMain
                           |
                           |--56.88%--pymain_run_python.constprop.0
                           |          |
                           |          |--56.13%--_PyRun_AnyFileObject
                           |          |          _PyRun_SimpleFileObject
                           |          |          |
                           |          |          |--55.02%--run_mod
                           |          |          |          |
                           |          |          |           --54.65%--PyEval_EvalCode
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     |
                           |          |          |                     |--51.67%--_PyEval_EvalFrameDefault
                           |          |          |                     |          |
                           |          |          |                     |          |--11.52%--_PyLong_Add
                           |          |          |                     |          |          |
                           |          |          |                     |          |          |--2.97%--_PyObject_Malloc
   ...

As you can see, the Python functions are not shown in the output, only
"_PyEval_EvalFrameDefault" (the function that evaluates the Python
bytecode) shows up. Unfortunately that's not very useful because all
Python functions use the same C function to evaluate bytecode so we
cannot know which Python function corresponds to which bytecode-
evaluating function.

Instead, if we run the same experiment with "perf" support enabled we
get:

   $ perf report --stdio -n -g

   # Children      Self       Samples  Command     Shared Object       Symbol
   # ........  ........  ............  ..........  ..................  .....................................................................
   #
       90.58%     0.36%             1  python.exe  python.exe          [.] _start
               |
               ---_start
               |
                   --89.86%--__libc_start_main
                           Py_BytesMain
                           |
                           |--55.43%--pymain_run_python.constprop.0
                           |          |
                           |          |--54.71%--_PyRun_AnyFileObject
                           |          |          _PyRun_SimpleFileObject
                           |          |          |
                           |          |          |--53.62%--run_mod
                           |          |          |          |
                           |          |          |           --53.26%--PyEval_EvalCode
                           |          |          |                     py::<module>:/src/script.py
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     py::baz:/src/script.py
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     py::bar:/src/script.py
                           |          |          |                     _PyEval_EvalFrameDefault
                           |          |          |                     PyObject_Vectorcall
                           |          |          |                     _PyEval_Vector
                           |          |          |                     py::foo:/src/script.py
                           |          |          |                     |
                           |          |          |                     |--51.81%--_PyEval_EvalFrameDefault
                           |          |          |                     |          |
                           |          |          |                     |          |--13.77%--_PyLong_Add
                           |          |          |                     |          |          |
                           |          |          |                     |          |          |--3.26%--_PyObject_Malloc


How to enable "perf" profiling support
======================================

"perf" profiling support can be enabled either from the start using
the environment variable "PYTHONPERFSUPPORT" or the "-X perf" option,
or dynamically using "sys.activate_stack_trampoline()" and
"sys.deactivate_stack_trampoline()".

The "sys" functions take precedence over the "-X" option, the "-X"
option takes precedence over the environment variable.

Example, using the environment variable:

   $ PYTHONPERFSUPPORT=1 python script.py
   $ perf report -g -i perf.data

Example, using the "-X" option:

   $ python -X perf script.py
   $ perf report -g -i perf.data

Example, using the "sys" APIs in file "example.py":

   import sys

   sys.activate_stack_trampoline("perf")
   do_profiled_stuff()
   sys.deactivate_stack_trampoline()

   non_profiled_stuff()

...then:

   $ python ./example.py
   $ perf report -g -i perf.data


How to obtain the best results
==============================

For best results, Python should be compiled with "CFLAGS="-fno-omit-
frame-pointer -mno-omit-leaf-frame-pointer"" as this allows profilers
to unwind using only the frame pointer and not on DWARF debug
information. This is because as the code that is interposed to allow
"perf" support is dynamically generated it doesn't have any DWARF
debugging information available.

You can check if your system has been compiled with this flag by
running:

   $ python -m sysconfig | grep 'no-omit-frame-pointer'

If you don't see any output it means that your interpreter has not
been compiled with frame pointers and therefore it may not be able to
show Python functions in the output of "perf".
