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<li><a class="reference internal" href="#">Python support for the Linux <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler</a><ul>
<li><a class="reference internal" href="#how-to-enable-perf-profiling-support">How to enable <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiling support</a></li>
<li><a class="reference internal" href="#how-to-obtain-the-best-results">How to obtain the best results</a></li>
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<section id="python-support-for-the-linux-perf-profiler">
<span id="perf-profiling"></span><h1>Python support for the Linux <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler<a class="headerlink" href="#python-support-for-the-linux-perf-profiler" title="Link to this heading"></a></h1>
<dl class="field-list simple">
<dt class="field-odd">author<span class="colon">:</span></dt>
<dd class="field-odd"><p>Pablo Galindo</p>
</dd>
</dl>
<p><a class="reference external" href="https://perf.wiki.kernel.org">The Linux perf profiler</a>
is a very powerful tool that allows you to profile and obtain
information about the performance of your application.
<code class="docutils literal notranslate"><span class="pre">perf</span></code> also has a very vibrant ecosystem of tools
that aid with the analysis of the data that it produces.</p>
<p>The main problem with using the <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler with Python applications is that
<code class="docutils literal notranslate"><span class="pre">perf</span></code> 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 <code class="docutils literal notranslate"><span class="pre">perf</span></code>.</p>
<p>Since Python 3.12, the interpreter can run in a special mode that allows Python
functions to appear in the output of the <code class="docutils literal notranslate"><span class="pre">perf</span></code> 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 <code class="docutils literal notranslate"><span class="pre">perf</span></code> the
relationship between this piece of code and the associated Python function using
<a class="reference internal" href="../c-api/perfmaps.html"><span class="doc">perf map files</span></a>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Support for the <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler is currently only available for Linux on
select architectures. Check the output of the <code class="docutils literal notranslate"><span class="pre">configure</span></code> build step or
check the output of <code class="docutils literal notranslate"><span class="pre">python</span> <span class="pre">-m</span> <span class="pre">sysconfig</span> <span class="pre">|</span> <span class="pre">grep</span> <span class="pre">HAVE_PERF_TRAMPOLINE</span></code>
to see if your system is supported.</p>
</div>
<p>For example, consider the following script:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="k">def</span><span class="w"> </span><span class="nf">foo</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">result</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">_</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">result</span> <span class="o">+=</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">result</span>
<span class="k">def</span><span class="w"> </span><span class="nf">bar</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">foo</span><span class="p">(</span><span class="n">n</span><span class="p">)</span>
<span class="k">def</span><span class="w"> </span><span class="nf">baz</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
<span class="n">bar</span><span class="p">(</span><span class="n">n</span><span class="p">)</span>
<span class="k">if</span> <span class="vm">__name__</span> <span class="o">==</span> <span class="s2">&quot;__main__&quot;</span><span class="p">:</span>
<span class="n">baz</span><span class="p">(</span><span class="mi">1000000</span><span class="p">)</span>
</pre></div>
</div>
<p>We can run <code class="docutils literal notranslate"><span class="pre">perf</span></code> to sample CPU stack traces at 9999 hertz:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>my_script.py
</pre></div>
</div>
<p>Then we can use <code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">report</span></code> to analyze the data:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>--stdio<span class="w"> </span>-n<span class="w"> </span>-g
<span class="gp"># </span>Children<span class="w"> </span>Self<span class="w"> </span>Samples<span class="w"> </span>Command<span class="w"> </span>Shared<span class="w"> </span>Object<span class="w"> </span>Symbol
<span class="gp"># </span>........<span class="w"> </span>........<span class="w"> </span>............<span class="w"> </span>..........<span class="w"> </span>..................<span class="w"> </span>..........................................
<span class="gp">#</span>
<span class="go"> 91.08% 0.00% 0 python.exe python.exe [.] _start</span>
<span class="go"> |</span>
<span class="go"> ---_start</span>
<span class="go"> |</span>
<span class="go"> --90.71%--__libc_start_main</span>
<span class="go"> Py_BytesMain</span>
<span class="go"> |</span>
<span class="go"> |--56.88%--pymain_run_python.constprop.0</span>
<span class="go"> | |</span>
<span class="go"> | |--56.13%--_PyRun_AnyFileObject</span>
<span class="go"> | | _PyRun_SimpleFileObject</span>
<span class="go"> | | |</span>
<span class="go"> | | |--55.02%--run_mod</span>
<span class="go"> | | | |</span>
<span class="go"> | | | --54.65%--PyEval_EvalCode</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | |</span>
<span class="go"> | | | |--51.67%--_PyEval_EvalFrameDefault</span>
<span class="go"> | | | | |</span>
<span class="go"> | | | | |--11.52%--_PyLong_Add</span>
<span class="go"> | | | | | |</span>
<span class="go"> | | | | | |--2.97%--_PyObject_Malloc</span>
<span class="go">...</span>
</pre></div>
</div>
<p>As you can see, the Python functions are not shown in the output, only <code class="docutils literal notranslate"><span class="pre">_PyEval_EvalFrameDefault</span></code>
(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.</p>
<p>Instead, if we run the same experiment with <code class="docutils literal notranslate"><span class="pre">perf</span></code> support enabled we get:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>--stdio<span class="w"> </span>-n<span class="w"> </span>-g
<span class="gp"># </span>Children<span class="w"> </span>Self<span class="w"> </span>Samples<span class="w"> </span>Command<span class="w"> </span>Shared<span class="w"> </span>Object<span class="w"> </span>Symbol
<span class="gp"># </span>........<span class="w"> </span>........<span class="w"> </span>............<span class="w"> </span>..........<span class="w"> </span>..................<span class="w"> </span>.....................................................................
<span class="gp">#</span>
<span class="go"> 90.58% 0.36% 1 python.exe python.exe [.] _start</span>
<span class="go"> |</span>
<span class="go"> ---_start</span>
<span class="go"> |</span>
<span class="go"> --89.86%--__libc_start_main</span>
<span class="go"> Py_BytesMain</span>
<span class="go"> |</span>
<span class="go"> |--55.43%--pymain_run_python.constprop.0</span>
<span class="go"> | |</span>
<span class="go"> | |--54.71%--_PyRun_AnyFileObject</span>
<span class="go"> | | _PyRun_SimpleFileObject</span>
<span class="go"> | | |</span>
<span class="go"> | | |--53.62%--run_mod</span>
<span class="go"> | | | |</span>
<span class="go"> | | | --53.26%--PyEval_EvalCode</span>
<span class="go"> | | | py::&lt;module&gt;:/src/script.py</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | py::baz:/src/script.py</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | py::bar:/src/script.py</span>
<span class="go"> | | | _PyEval_EvalFrameDefault</span>
<span class="go"> | | | PyObject_Vectorcall</span>
<span class="go"> | | | _PyEval_Vector</span>
<span class="go"> | | | py::foo:/src/script.py</span>
<span class="go"> | | | |</span>
<span class="go"> | | | |--51.81%--_PyEval_EvalFrameDefault</span>
<span class="go"> | | | | |</span>
<span class="go"> | | | | |--13.77%--_PyLong_Add</span>
<span class="go"> | | | | | |</span>
<span class="go"> | | | | | |--3.26%--_PyObject_Malloc</span>
</pre></div>
</div>
<section id="how-to-enable-perf-profiling-support">
<h2>How to enable <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiling support<a class="headerlink" href="#how-to-enable-perf-profiling-support" title="Link to this heading"></a></h2>
<p><code class="docutils literal notranslate"><span class="pre">perf</span></code> profiling support can be enabled either from the start using
the environment variable <span class="target" id="index-0"></span><a class="reference internal" href="../using/cmdline.html#envvar-PYTHONPERFSUPPORT"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">PYTHONPERFSUPPORT</span></code></a> or the
<a class="reference internal" href="../using/cmdline.html#cmdoption-X"><code class="xref std std-option docutils literal notranslate"><span class="pre">-X</span> <span class="pre">perf</span></code></a> option,
or dynamically using <a class="reference internal" href="../library/sys.html#sys.activate_stack_trampoline" title="sys.activate_stack_trampoline"><code class="xref py py-func docutils literal notranslate"><span class="pre">sys.activate_stack_trampoline()</span></code></a> and
<a class="reference internal" href="../library/sys.html#sys.deactivate_stack_trampoline" title="sys.deactivate_stack_trampoline"><code class="xref py py-func docutils literal notranslate"><span class="pre">sys.deactivate_stack_trampoline()</span></code></a>.</p>
<p>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">sys</span></code> functions take precedence over the <code class="xref std std-option docutils literal notranslate"><span class="pre">-X</span></code> option,
the <code class="xref std std-option docutils literal notranslate"><span class="pre">-X</span></code> option takes precedence over the environment variable.</p>
<p>Example, using the environment variable:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span><span class="nv">PYTHONPERFSUPPORT</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>my_script.py
<span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>-g<span class="w"> </span>-i<span class="w"> </span>perf.data
</pre></div>
</div>
<p>Example, using the <code class="xref std std-option docutils literal notranslate"><span class="pre">-X</span></code> option:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>-X<span class="w"> </span>perf<span class="w"> </span>my_script.py
<span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>-g<span class="w"> </span>-i<span class="w"> </span>perf.data
</pre></div>
</div>
<p>Example, using the <a class="reference internal" href="../library/sys.html#module-sys" title="sys: Access system-specific parameters and functions."><code class="xref py py-mod docutils literal notranslate"><span class="pre">sys</span></code></a> APIs in file <code class="file docutils literal notranslate"><span class="pre">example.py</span></code>:</p>
<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">sys</span>
<span class="n">sys</span><span class="o">.</span><span class="n">activate_stack_trampoline</span><span class="p">(</span><span class="s2">&quot;perf&quot;</span><span class="p">)</span>
<span class="n">do_profiled_stuff</span><span class="p">()</span>
<span class="n">sys</span><span class="o">.</span><span class="n">deactivate_stack_trampoline</span><span class="p">()</span>
<span class="n">non_profiled_stuff</span><span class="p">()</span>
</pre></div>
</div>
<p>…then:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>./example.py
<span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>-g<span class="w"> </span>-i<span class="w"> </span>perf.data
</pre></div>
</div>
</section>
<section id="how-to-obtain-the-best-results">
<h2>How to obtain the best results<a class="headerlink" href="#how-to-obtain-the-best-results" title="Link to this heading"></a></h2>
<p>For best results, Python should be compiled with
<code class="docutils literal notranslate"><span class="pre">CFLAGS=&quot;-fno-omit-frame-pointer</span> <span class="pre">-mno-omit-leaf-frame-pointer&quot;</span></code> 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 <code class="docutils literal notranslate"><span class="pre">perf</span></code>
support is dynamically generated it doesn’t have any DWARF debugging information
available.</p>
<p>You can check if your system has been compiled with this flag by running:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>python<span class="w"> </span>-m<span class="w"> </span>sysconfig<span class="w"> </span><span class="p">|</span><span class="w"> </span>grep<span class="w"> </span><span class="s1">&#39;no-omit-frame-pointer&#39;</span>
</pre></div>
</div>
<p>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 <code class="docutils literal notranslate"><span class="pre">perf</span></code>.</p>
</section>
<section id="how-to-work-without-frame-pointers">
<h2>How to work without frame pointers<a class="headerlink" href="#how-to-work-without-frame-pointers" title="Link to this heading"></a></h2>
<p>If you are working with a Python interpreter that has been compiled without
frame pointers, you can still use the <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler, but the overhead will be
a bit higher because Python needs to generate unwinding information for every
Python function call on the fly. Additionally, <code class="docutils literal notranslate"><span class="pre">perf</span></code> will take more time to
process the data because it will need to use the DWARF debugging information to
unwind the stack and this is a slow process.</p>
<p>To enable this mode, you can use the environment variable
<span class="target" id="index-1"></span><a class="reference internal" href="../using/cmdline.html#envvar-PYTHON_PERF_JIT_SUPPORT"><code class="xref std std-envvar docutils literal notranslate"><span class="pre">PYTHON_PERF_JIT_SUPPORT</span></code></a> or the <a class="reference internal" href="../using/cmdline.html#cmdoption-X"><code class="xref std std-option docutils literal notranslate"><span class="pre">-X</span> <span class="pre">perf_jit</span></code></a> option,
which will enable the JIT mode for the <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Due to a bug in the <code class="docutils literal notranslate"><span class="pre">perf</span></code> tool, only <code class="docutils literal notranslate"><span class="pre">perf</span></code> versions higher than v6.8
will work with the JIT mode. The fix was also backported to the v6.7.2
version of the tool.</p>
<p>Note that when checking the version of the <code class="docutils literal notranslate"><span class="pre">perf</span></code> tool (which can be done
by running <code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">version</span></code>) you must take into account that some distros
add some custom version numbers including a <code class="docutils literal notranslate"><span class="pre">-</span></code> character. This means
that <code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">6.7-3</span></code> is not necessarily <code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">6.7.3</span></code>.</p>
</div>
<p>When using the perf JIT mode, you need an extra step before you can run <code class="docutils literal notranslate"><span class="pre">perf</span>
<span class="pre">report</span></code>. You need to call the <code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">inject</span></code> command to inject the JIT
information into the <code class="docutils literal notranslate"><span class="pre">perf.data</span></code> file.:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>-k<span class="w"> </span><span class="m">1</span><span class="w"> </span>--call-graph<span class="w"> </span>dwarf<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>-Xperf_jit<span class="w"> </span>my_script.py
<span class="gp">$ </span>perf<span class="w"> </span>inject<span class="w"> </span>-i<span class="w"> </span>perf.data<span class="w"> </span>--jit<span class="w"> </span>--output<span class="w"> </span>perf.jit.data
<span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>-g<span class="w"> </span>-i<span class="w"> </span>perf.jit.data
</pre></div>
</div>
<p>or using the environment variable:</p>
<div class="highlight-shell-session notranslate"><div class="highlight"><pre><span></span><span class="gp">$ </span><span class="nv">PYTHON_PERF_JIT_SUPPORT</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>perf<span class="w"> </span>record<span class="w"> </span>-F<span class="w"> </span><span class="m">9999</span><span class="w"> </span>-g<span class="w"> </span>--call-graph<span class="w"> </span>dwarf<span class="w"> </span>-o<span class="w"> </span>perf.data<span class="w"> </span>python<span class="w"> </span>my_script.py
<span class="gp">$ </span>perf<span class="w"> </span>inject<span class="w"> </span>-i<span class="w"> </span>perf.data<span class="w"> </span>--jit<span class="w"> </span>--output<span class="w"> </span>perf.jit.data
<span class="gp">$ </span>perf<span class="w"> </span>report<span class="w"> </span>-g<span class="w"> </span>-i<span class="w"> </span>perf.jit.data
</pre></div>
</div>
<p><code class="docutils literal notranslate"><span class="pre">perf</span> <span class="pre">inject</span> <span class="pre">--jit</span></code> command will read <code class="docutils literal notranslate"><span class="pre">perf.data</span></code>,
automatically pick up the perf dump file that Python creates (in
<code class="docutils literal notranslate"><span class="pre">/tmp/perf-$PID.dump</span></code>), and then create <code class="docutils literal notranslate"><span class="pre">perf.jit.data</span></code> which merges all the
JIT information together. It should also create a lot of <code class="docutils literal notranslate"><span class="pre">jitted-XXXX-N.so</span></code>
files in the current directory which are ELF images for all the JIT trampolines
that were created by Python.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>Notice that when using <code class="docutils literal notranslate"><span class="pre">--call-graph</span> <span class="pre">dwarf</span></code> the <code class="docutils literal notranslate"><span class="pre">perf</span></code> tool will take
snapshots of the stack of the process being profiled and save the
information in the <code class="docutils literal notranslate"><span class="pre">perf.data</span></code> file. By default the size of the stack dump
is 8192 bytes but the user can change the size by passing the size after
comma like <code class="docutils literal notranslate"><span class="pre">--call-graph</span> <span class="pre">dwarf,4096</span></code>. The size of the stack dump is
important because if the size is too small <code class="docutils literal notranslate"><span class="pre">perf</span></code> will not be able to
unwind the stack and the output will be incomplete. On the other hand, if
the size is too big, then <code class="docutils literal notranslate"><span class="pre">perf</span></code> won’t be able to sample the process as
frequently as it would like as the overhead will be higher.</p>
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<ul>
<li><a class="reference internal" href="#">Python support for the Linux <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiler</a><ul>
<li><a class="reference internal" href="#how-to-enable-perf-profiling-support">How to enable <code class="docutils literal notranslate"><span class="pre">perf</span></code> profiling support</a></li>
<li><a class="reference internal" href="#how-to-obtain-the-best-results">How to obtain the best results</a></li>
<li><a class="reference internal" href="#how-to-work-without-frame-pointers">How to work without frame pointers</a></li>
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