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<li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> — Pure Python profiler</a><ul>
<li><a class="reference internal" href="#migration">Migration</a></li>
<li><a class="reference internal" href="#profile-and-profiling-tracing-module-reference"><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> and <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code> module reference</a></li>
<li><a class="reference internal" href="#differences-from-profiling-tracing">Differences from <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a></li>
<li><a class="reference internal" href="#what-is-deterministic-profiling">What is deterministic profiling?</a></li>
<li><a class="reference internal" href="#limitations">Limitations</a></li>
<li><a class="reference internal" href="#calibration">Calibration</a></li>
<li><a class="reference internal" href="#using-a-custom-timer">Using a custom timer</a></li>
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<section id="module-profile">
<span id="profile-pure-python-profiler"></span><span id="profile"></span><h1><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> — Pure Python profiler<a class="headerlink" href="#module-profile" title="Link to this heading">¶</a></h1>
<p><strong>Source code:</strong> <a class="extlink-source reference external" href="https://github.com/python/cpython/tree/3.15/Lib/profile.py">Lib/profile.py</a></p>
<hr class="docutils" />
<div class="deprecated-removed">
<p><span class="versionmodified deprecated">Deprecated since version 3.15, will be removed in version 3.17.</span></p>
</div>
<p>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module is deprecated and will be removed in Python 3.17.
Use <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> instead.</p>
<p>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module provides a pure Python implementation of a
deterministic profiler. While useful for understanding profiler internals or
extending profiler behavior through subclassing, its pure Python implementation
introduces significant overhead compared to the C-based <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>
module.</p>
<p>For most profiling tasks, use:</p>
<ul class="simple">
<li><p><a class="reference internal" href="profiling.sampling.html#module-profiling.sampling" title="profiling.sampling: Statistical sampling profiler for Python processes."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.sampling</span></code></a> for production debugging with zero overhead</p></li>
<li><p><a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> for development and testing</p></li>
</ul>
<section id="migration">
<h2>Migration<a class="headerlink" href="#migration" title="Link to this heading">¶</a></h2>
<p>Migrating from <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> to <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> is straightforward.
The APIs are compatible:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="c1"># Old (deprecated)</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">profile</span>
<span class="n">profile</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="s1">'my_function()'</span><span class="p">)</span>
<span class="c1"># New (recommended)</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">profiling.tracing</span>
<span class="n">profiling</span><span class="o">.</span><span class="n">tracing</span><span class="o">.</span><span class="n">run</span><span class="p">(</span><span class="s1">'my_function()'</span><span class="p">)</span>
</pre></div>
</div>
<p>For most code, replacing <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">profile</span></code> with <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">profiling.tracing</span></code>
(and using <code class="docutils literal notranslate"><span class="pre">profiling.tracing</span></code> instead of <code class="docutils literal notranslate"><span class="pre">profile</span></code> throughout) provides
a straightforward migration path.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The <code class="docutils literal notranslate"><span class="pre">cProfile</span></code> module remains available as a backward-compatible alias
to <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>. Existing code using <code class="docutils literal notranslate"><span class="pre">import</span> <span class="pre">cProfile</span></code> will
continue to work without modification.</p>
</div>
</section>
<section id="profile-and-profiling-tracing-module-reference">
<h2><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> and <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code> module reference<a class="headerlink" href="#profile-and-profiling-tracing-module-reference" title="Link to this heading">¶</a></h2>
<p>Both the <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> and <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> modules provide the
following functions:</p>
<dl class="py function">
<dt class="sig sig-object py" id="profile.run">
<span class="sig-prename descclassname"><span class="pre">profile.</span></span><span class="sig-name descname"><span class="pre">run</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">command</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.run" title="Link to this definition">¶</a></dt>
<dd><p>This function takes a single argument that can be passed to the <a class="reference internal" href="functions.html#exec" title="exec"><code class="xref py py-func docutils literal notranslate"><span class="pre">exec()</span></code></a>
function, and an optional file name. In all cases this routine executes:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="n">exec</span><span class="p">(</span><span class="n">command</span><span class="p">,</span> <span class="n">__main__</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">,</span> <span class="n">__main__</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">)</span>
</pre></div>
</div>
<p>and gathers profiling statistics from the execution. If no file name is
present, then this function automatically creates a <a class="reference internal" href="pstats.html#pstats.Stats" title="pstats.Stats"><code class="xref py py-class docutils literal notranslate"><span class="pre">Stats</span></code></a>
instance and prints a simple profiling report. If the sort value is specified,
it is passed to this <code class="xref py py-class docutils literal notranslate"><span class="pre">Stats</span></code> instance to control how the
results are sorted.</p>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="profile.runctx">
<span class="sig-prename descclassname"><span class="pre">profile.</span></span><span class="sig-name descname"><span class="pre">runctx</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">command</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">globals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">locals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.runctx" title="Link to this definition">¶</a></dt>
<dd><p>This function is similar to <a class="reference internal" href="#profile.run" title="profile.run"><code class="xref py py-func docutils literal notranslate"><span class="pre">run()</span></code></a>, with added arguments to supply the
globals and locals mappings for the <em>command</em> string. This routine
executes:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="n">exec</span><span class="p">(</span><span class="n">command</span><span class="p">,</span> <span class="nb">globals</span><span class="p">,</span> <span class="nb">locals</span><span class="p">)</span>
</pre></div>
</div>
<p>and gathers profiling statistics as in the <a class="reference internal" href="#profile.run" title="profile.run"><code class="xref py py-func docutils literal notranslate"><span class="pre">run()</span></code></a> function above.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="profile.Profile">
<em class="property"><span class="k"><span class="pre">class</span></span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">profile.</span></span><span class="sig-name descname"><span class="pre">Profile</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">timer</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">timeunit</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0.0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subcalls</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">builtins</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile" title="Link to this definition">¶</a></dt>
<dd><p>This class is normally only used if more precise control over profiling is
needed than what the <a class="reference internal" href="profiling.tracing.html#profiling.tracing.run" title="profiling.tracing.run"><code class="xref py py-func docutils literal notranslate"><span class="pre">profiling.tracing.run()</span></code></a> function provides.</p>
<p>A custom timer can be supplied for measuring how long code takes to run via
the <em>timer</em> argument. This must be a function that returns a single number
representing the current time. If the number is an integer, the <em>timeunit</em>
specifies a multiplier that specifies the duration of each unit of time. For
example, if the timer returns times measured in thousands of seconds, the
time unit would be <code class="docutils literal notranslate"><span class="pre">.001</span></code>.</p>
<p>Directly using the <code class="xref py py-class docutils literal notranslate"><span class="pre">Profile</span></code> class allows formatting profile results
without writing the profile data to a file:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">profiling.tracing</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">pstats</span>
<span class="kn">import</span><span class="w"> </span><span class="nn">io</span>
<span class="kn">from</span><span class="w"> </span><span class="nn">pstats</span><span class="w"> </span><span class="kn">import</span> <span class="n">SortKey</span>
<span class="n">pr</span> <span class="o">=</span> <span class="n">profiling</span><span class="o">.</span><span class="n">tracing</span><span class="o">.</span><span class="n">Profile</span><span class="p">()</span>
<span class="n">pr</span><span class="o">.</span><span class="n">enable</span><span class="p">()</span>
<span class="c1"># ... do something ...</span>
<span class="n">pr</span><span class="o">.</span><span class="n">disable</span><span class="p">()</span>
<span class="n">s</span> <span class="o">=</span> <span class="n">io</span><span class="o">.</span><span class="n">StringIO</span><span class="p">()</span>
<span class="n">sortby</span> <span class="o">=</span> <span class="n">SortKey</span><span class="o">.</span><span class="n">CUMULATIVE</span>
<span class="n">ps</span> <span class="o">=</span> <span class="n">pstats</span><span class="o">.</span><span class="n">Stats</span><span class="p">(</span><span class="n">pr</span><span class="p">,</span> <span class="n">stream</span><span class="o">=</span><span class="n">s</span><span class="p">)</span><span class="o">.</span><span class="n">sort_stats</span><span class="p">(</span><span class="n">sortby</span><span class="p">)</span>
<span class="n">ps</span><span class="o">.</span><span class="n">print_stats</span><span class="p">()</span>
<span class="nb">print</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">getvalue</span><span class="p">())</span>
</pre></div>
</div>
<p>The <code class="xref py py-class docutils literal notranslate"><span class="pre">Profile</span></code> class can also be used as a context manager (supported
only in <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>, not in the deprecated <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code>
module; see <a class="reference internal" href="stdtypes.html#typecontextmanager"><span class="std std-ref">Context Manager Types</span></a>):</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">profiling.tracing</span>
<span class="k">with</span> <span class="n">profiling</span><span class="o">.</span><span class="n">tracing</span><span class="o">.</span><span class="n">Profile</span><span class="p">()</span> <span class="k">as</span> <span class="n">pr</span><span class="p">:</span>
<span class="c1"># ... do something ...</span>
<span class="n">pr</span><span class="o">.</span><span class="n">print_stats</span><span class="p">()</span>
</pre></div>
</div>
<div class="versionchanged">
<p><span class="versionmodified changed">Changed in version 3.8: </span>Added context manager support.</p>
</div>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.enable">
<span class="sig-name descname"><span class="pre">enable</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.enable" title="Link to this definition">¶</a></dt>
<dd><p>Start collecting profiling data. Only in <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.disable">
<span class="sig-name descname"><span class="pre">disable</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.disable" title="Link to this definition">¶</a></dt>
<dd><p>Stop collecting profiling data. Only in <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.create_stats">
<span class="sig-name descname"><span class="pre">create_stats</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.create_stats" title="Link to this definition">¶</a></dt>
<dd><p>Stop collecting profiling data and record the results internally
as the current profile.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.print_stats">
<span class="sig-name descname"><span class="pre">print_stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sort</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">-1</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.print_stats" title="Link to this definition">¶</a></dt>
<dd><p>Create a <a class="reference internal" href="pstats.html#pstats.Stats" title="pstats.Stats"><code class="xref py py-class docutils literal notranslate"><span class="pre">Stats</span></code></a> object based on the current
profile and print the results to stdout.</p>
<p>The <em>sort</em> parameter specifies the sorting order of the displayed
statistics. It accepts a single key or a tuple of keys to enable
multi-level sorting, as in <a class="reference internal" href="pstats.html#pstats.Stats.sort_stats" title="pstats.Stats.sort_stats"><code class="xref py py-meth docutils literal notranslate"><span class="pre">pstats.Stats.sort_stats()</span></code></a>.</p>
<div class="versionadded">
<p><span class="versionmodified added">Added in version 3.13: </span><code class="xref py py-meth docutils literal notranslate"><span class="pre">print_stats()</span></code> now accepts a tuple of keys.</p>
</div>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.dump_stats">
<span class="sig-name descname"><span class="pre">dump_stats</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.dump_stats" title="Link to this definition">¶</a></dt>
<dd><p>Write the results of the current profile to <em>filename</em>.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.run">
<span class="sig-name descname"><span class="pre">run</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmd</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.run" title="Link to this definition">¶</a></dt>
<dd><p>Profile the cmd via <a class="reference internal" href="functions.html#exec" title="exec"><code class="xref py py-func docutils literal notranslate"><span class="pre">exec()</span></code></a>.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.runctx">
<span class="sig-name descname"><span class="pre">runctx</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">cmd</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">globals</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">locals</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.runctx" title="Link to this definition">¶</a></dt>
<dd><p>Profile the cmd via <a class="reference internal" href="functions.html#exec" title="exec"><code class="xref py py-func docutils literal notranslate"><span class="pre">exec()</span></code></a> with the specified global and
local environment.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="profile.Profile.runcall">
<span class="sig-name descname"><span class="pre">runcall</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="positional-only-separator o"><abbr title="Positional-only parameter separator (PEP 570)"><span class="pre">/</span></abbr></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#profile.Profile.runcall" title="Link to this definition">¶</a></dt>
<dd><p>Profile <code class="docutils literal notranslate"><span class="pre">func(*args,</span> <span class="pre">**kwargs)</span></code></p>
</dd></dl>
</dd></dl>
<p>Note that profiling will only work if the called command/function actually
returns. If the interpreter is terminated (e.g. via a <a class="reference internal" href="sys.html#sys.exit" title="sys.exit"><code class="xref py py-func docutils literal notranslate"><span class="pre">sys.exit()</span></code></a> call
during the called command/function execution) no profiling results will be
printed.</p>
</section>
<section id="differences-from-profiling-tracing">
<h2>Differences from <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code><a class="headerlink" href="#differences-from-profiling-tracing" title="Link to this heading">¶</a></h2>
<p>The <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module differs from <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> in several
ways:</p>
<p><strong>Higher overhead.</strong> The pure Python implementation is significantly slower
than the C implementation, making it unsuitable for profiling long-running
programs or performance-sensitive code.</p>
<p><strong>Calibration support.</strong> The <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module supports calibration to
compensate for profiling overhead. This is not needed in <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>
because the C implementation has negligible overhead.</p>
<p><strong>Custom timers.</strong> Both modules support custom timers, but <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code>
accepts timer functions that return tuples (like <a class="reference internal" href="os.html#os.times" title="os.times"><code class="xref py py-func docutils literal notranslate"><span class="pre">os.times()</span></code></a>), while
<a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a> requires a function returning a single number.</p>
<p><strong>Subclassing.</strong> The pure Python implementation is easier to subclass and
extend for custom profiling behavior.</p>
</section>
<section id="what-is-deterministic-profiling">
<span id="deterministic-profiling"></span><h2>What is deterministic profiling?<a class="headerlink" href="#what-is-deterministic-profiling" title="Link to this heading">¶</a></h2>
<p><em class="dfn">Deterministic profiling</em> is meant to reflect the fact that all <em>function
call</em>, <em>function return</em>, and <em>exception</em> events are monitored, and precise
timings are made for the intervals between these events (during which time the
user’s code is executing). In contrast, <em class="dfn">statistical profiling</em> (which is
provided by the <a class="reference internal" href="profiling.sampling.html#module-profiling.sampling" title="profiling.sampling: Statistical sampling profiler for Python processes."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.sampling</span></code></a> module) periodically samples the
effective instruction pointer, and deduces where time is being spent. The
latter technique traditionally involves less overhead (as the code does not
need to be instrumented), but provides only relative indications of where time
is being spent.</p>
<p>In Python, since there is an interpreter active during execution, the presence
of instrumented code is not required in order to do deterministic profiling.
Python automatically provides a <em class="dfn">hook</em> (optional callback) for each event.
In addition, the interpreted nature of Python tends to add so much overhead to
execution, that deterministic profiling tends to only add small processing
overhead in typical applications. The result is that deterministic profiling is
not that expensive, yet provides extensive run time statistics about the
execution of a Python program.</p>
<p>Call count statistics can be used to identify bugs in code (surprising counts),
and to identify possible inline-expansion points (high call counts). Internal
time statistics can be used to identify “hot loops” that should be carefully
optimized. Cumulative time statistics should be used to identify high level
errors in the selection of algorithms. Note that the unusual handling of
cumulative times in this profiler allows statistics for recursive
implementations of algorithms to be directly compared to iterative
implementations.</p>
</section>
<section id="limitations">
<span id="profile-limitations"></span><h2>Limitations<a class="headerlink" href="#limitations" title="Link to this heading">¶</a></h2>
<p>One limitation has to do with accuracy of timing information. There is a
fundamental problem with deterministic profilers involving accuracy. The most
obvious restriction is that the underlying “clock” is only ticking at a rate
(typically) of about .001 seconds. Hence no measurements will be more accurate
than the underlying clock. If enough measurements are taken, then the “error”
will tend to average out. Unfortunately, removing this first error induces a
second source of error.</p>
<p>The second problem is that it “takes a while” from when an event is dispatched
until the profiler’s call to get the time actually <em>gets</em> the state of the
clock. Similarly, there is a certain lag when exiting the profiler event
handler from the time that the clock’s value was obtained (and then squirreled
away), until the user’s code is once again executing. As a result, functions
that are called many times, or call many functions, will typically accumulate
this error. The error that accumulates in this fashion is typically less than
the accuracy of the clock (less than one clock tick), but it <em>can</em> accumulate
and become very significant.</p>
<p>The problem is more important with the deprecated <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module than
with the lower-overhead <a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a>. For this reason,
<code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> provides a means of calibrating itself for a given platform so
that this error can be probabilistically (on the average) removed. After the
profiler is calibrated, it will be more accurate (in a least square sense), but
it will sometimes produce negative numbers (when call counts are exceptionally
low, and the gods of probability work against you :-). ) Do <em>not</em> be alarmed
by negative numbers in the profile. They should <em>only</em> appear if you have
calibrated your profiler, and the results are actually better than without
calibration.</p>
</section>
<section id="calibration">
<span id="profile-calibration"></span><h2>Calibration<a class="headerlink" href="#calibration" title="Link to this heading">¶</a></h2>
<p>The profiler of the <code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> module subtracts a constant from each event
handling time to compensate for the overhead of calling the time function, and
socking away the results. By default, the constant is 0. The following
procedure can be used to obtain a better constant for a given platform (see
<a class="reference internal" href="#profile-limitations"><span class="std std-ref">Limitations</span></a>).</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">profile</span>
<span class="n">pr</span> <span class="o">=</span> <span class="n">profile</span><span class="o">.</span><span class="n">Profile</span><span class="p">()</span>
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">5</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="n">pr</span><span class="o">.</span><span class="n">calibrate</span><span class="p">(</span><span class="mi">10000</span><span class="p">))</span>
</pre></div>
</div>
<p>The method executes the number of Python calls given by the argument, directly
and again under the profiler, measuring the time for both. It then computes the
hidden overhead per profiler event, and returns that as a float. For example,
on a 1.8Ghz Intel Core i5 running macOS, and using Python’s time.process_time() as
the timer, the magical number is about 4.04e-6.</p>
<p>The object of this exercise is to get a fairly consistent result. If your
computer is <em>very</em> fast, or your timer function has poor resolution, you might
have to pass 100000, or even 1000000, to get consistent results.</p>
<p>When you have a consistent answer, there are three ways you can use it:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="kn">import</span><span class="w"> </span><span class="nn">profile</span>
<span class="c1"># 1. Apply computed bias to all Profile instances created hereafter.</span>
<span class="n">profile</span><span class="o">.</span><span class="n">Profile</span><span class="o">.</span><span class="n">bias</span> <span class="o">=</span> <span class="n">your_computed_bias</span>
<span class="c1"># 2. Apply computed bias to a specific Profile instance.</span>
<span class="n">pr</span> <span class="o">=</span> <span class="n">profile</span><span class="o">.</span><span class="n">Profile</span><span class="p">()</span>
<span class="n">pr</span><span class="o">.</span><span class="n">bias</span> <span class="o">=</span> <span class="n">your_computed_bias</span>
<span class="c1"># 3. Specify computed bias in instance constructor.</span>
<span class="n">pr</span> <span class="o">=</span> <span class="n">profile</span><span class="o">.</span><span class="n">Profile</span><span class="p">(</span><span class="n">bias</span><span class="o">=</span><span class="n">your_computed_bias</span><span class="p">)</span>
</pre></div>
</div>
<p>If you have a choice, you are better off choosing a smaller constant, and then
your results will “less often” show up as negative in profile statistics.</p>
</section>
<section id="using-a-custom-timer">
<span id="profile-timers"></span><h2>Using a custom timer<a class="headerlink" href="#using-a-custom-timer" title="Link to this heading">¶</a></h2>
<p>If you want to change how current time is determined (for example, to force use
of wall-clock time or elapsed process time), pass the timing function you want
to the <a class="reference internal" href="#profile.Profile" title="profile.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">Profile</span></code></a> class constructor:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="n">pr</span> <span class="o">=</span> <span class="n">profile</span><span class="o">.</span><span class="n">Profile</span><span class="p">(</span><span class="n">your_time_func</span><span class="p">)</span>
</pre></div>
</div>
<p>The resulting profiler will then call <code class="docutils literal notranslate"><span class="pre">your_time_func</span></code>. Depending on whether
you are using <a class="reference internal" href="#profile.Profile" title="profile.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">profile.Profile</span></code></a> or <a class="reference internal" href="profiling.tracing.html#profiling.tracing.Profile" title="profiling.tracing.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">profiling.tracing.Profile</span></code></a>,
<code class="docutils literal notranslate"><span class="pre">your_time_func</span></code>’s return value will be interpreted differently:</p>
<dl>
<dt><a class="reference internal" href="#profile.Profile" title="profile.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">profile.Profile</span></code></a></dt><dd><p><code class="docutils literal notranslate"><span class="pre">your_time_func</span></code> should return a single number, or a list of numbers whose
sum is the current time (like what <a class="reference internal" href="os.html#os.times" title="os.times"><code class="xref py py-func docutils literal notranslate"><span class="pre">os.times()</span></code></a> returns). If the
function returns a single time number, or the list of returned numbers has
length 2, then you will get an especially fast version of the dispatch
routine.</p>
<p>Be warned that you should calibrate the profiler class for the timer function
that you choose (see <a class="reference internal" href="#profile-calibration"><span class="std std-ref">Calibration</span></a>). For most machines, a timer
that returns a lone integer value will provide the best results in terms of
low overhead during profiling. (<a class="reference internal" href="os.html#os.times" title="os.times"><code class="xref py py-func docutils literal notranslate"><span class="pre">os.times()</span></code></a> is <em>pretty</em> bad, as it
returns a tuple of floating-point values). If you want to substitute a
better timer in the cleanest fashion, derive a class and hardwire a
replacement dispatch method that best handles your timer call, along with the
appropriate calibration constant.</p>
</dd>
<dt><a class="reference internal" href="profiling.tracing.html#profiling.tracing.Profile" title="profiling.tracing.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">profiling.tracing.Profile</span></code></a></dt><dd><p><code class="docutils literal notranslate"><span class="pre">your_time_func</span></code> should return a single number. If it returns integers,
you can also invoke the class constructor with a second argument specifying
the real duration of one unit of time. For example, if
<code class="docutils literal notranslate"><span class="pre">your_integer_time_func</span></code> returns times measured in thousands of seconds,
you would construct the <a class="reference internal" href="#profile.Profile" title="profile.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">Profile</span></code></a> instance as follows:</p>
<div class="highlight-python3 notranslate"><div class="highlight"><pre><span></span><span class="n">pr</span> <span class="o">=</span> <span class="n">profiling</span><span class="o">.</span><span class="n">tracing</span><span class="o">.</span><span class="n">Profile</span><span class="p">(</span><span class="n">your_integer_time_func</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">)</span>
</pre></div>
</div>
<p>As the <a class="reference internal" href="profiling.tracing.html#profiling.tracing.Profile" title="profiling.tracing.Profile"><code class="xref py py-class docutils literal notranslate"><span class="pre">profiling.tracing.Profile</span></code></a> class cannot be calibrated, custom
timer functions should be used with care and should be as fast as possible.
For the best results with a custom timer, it might be necessary to hard-code
it in the C source of the internal <code class="xref py py-mod docutils literal notranslate"><span class="pre">_lsprof</span></code> module.</p>
</dd>
</dl>
<p>Python 3.3 adds several new functions in <a class="reference internal" href="time.html#module-time" title="time: Time access and conversions."><code class="xref py py-mod docutils literal notranslate"><span class="pre">time</span></code></a> that can be used to make
precise measurements of process or wall-clock time. For example, see
<a class="reference internal" href="time.html#time.perf_counter" title="time.perf_counter"><code class="xref py py-func docutils literal notranslate"><span class="pre">time.perf_counter()</span></code></a>.</p>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="profiling.html#module-profiling" title="profiling: Python profiling tools for performance analysis."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling</span></code></a></dt><dd><p>Overview of Python profiling tools.</p>
</dd>
<dt><a class="reference internal" href="profiling.tracing.html#module-profiling.tracing" title="profiling.tracing: Deterministic tracing profiler for Python programs."><code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a></dt><dd><p>Recommended replacement for this module.</p>
</dd>
<dt><a class="reference internal" href="pstats.html#module-pstats" title="pstats: Statistics object for analyzing profiler output."><code class="xref py py-mod docutils literal notranslate"><span class="pre">pstats</span></code></a></dt><dd><p>Statistical analysis and formatting for profile data.</p>
</dd>
</dl>
</div>
</section>
</section>
<div class="clearer"></div>
</div>
</div>
</div>
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<h3><a href="../contents.html">Table of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#"><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> — Pure Python profiler</a><ul>
<li><a class="reference internal" href="#migration">Migration</a></li>
<li><a class="reference internal" href="#profile-and-profiling-tracing-module-reference"><code class="xref py py-mod docutils literal notranslate"><span class="pre">profile</span></code> and <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code> module reference</a></li>
<li><a class="reference internal" href="#differences-from-profiling-tracing">Differences from <code class="xref py py-mod docutils literal notranslate"><span class="pre">profiling.tracing</span></code></a></li>
<li><a class="reference internal" href="#what-is-deterministic-profiling">What is deterministic profiling?</a></li>
<li><a class="reference internal" href="#limitations">Limitations</a></li>
<li><a class="reference internal" href="#calibration">Calibration</a></li>
<li><a class="reference internal" href="#using-a-custom-timer">Using a custom timer</a></li>
</ul>
</li>
</ul>
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