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python-cheatsheet
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Profiling

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Jure Šorn 2 years ago
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  1. 3
      README.md
  2. 11
      index.html
  3. 1
      pdf/remove_links.py

3
README.md
View File

@ -2604,9 +2604,7 @@ Line # Hits Time Per Hit % Time Line Contents
2 def main():
3 1 955.0 955.0 43.7 a = [*range(10000)]
4 1 1231.0 1231.0 56.3 b = {*range(10000)}
```
```text
$ python3 -m memory_profiler test.py
Line # Mem usage Increment Line Contents
=======================================================
@ -2627,6 +2625,7 @@ drawer = cg.output.GraphvizOutput(output_file=filename)
with cg.PyCallGraph(drawer):
<code_to_be_profiled>
```
* **The "latest and greatest" profiler that can also monitor GPU usage is called [Scalene](https://github.com/plasma-umass/scalene).**
NumPy

11
index.html
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@ -54,7 +54,7 @@
<body>
<header>
<aside>December 26, 2022</aside>
<aside>December 27, 2022</aside>
<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
</header>
@ -2133,8 +2133,8 @@ Line # Hits Time Per Hit % Time Line Contents
2 def main():
3 1 955.0 955.0 43.7 a = [*range(10000)]
4 1 1231.0 1231.0 56.3 b = {*range(10000)}
</code></pre>
<pre><code class="text language-text">$ python3 -m memory_profiler test.py
$ python3 -m memory_profiler test.py
Line # Mem usage Increment Line Contents
=======================================================
1 37.668 MiB 37.668 MiB @profile
@ -2152,6 +2152,9 @@ drawer = cg.output.GraphvizOutput(output_file=filename)
</code></pre></div></div>
<ul>
<li><strong>The "latest and greatest" profiler that can also monitor GPU usage is called <a href="https://github.com/plasma-umass/scalene">Scalene</a>.</strong></li>
</ul>
<div><h2 id="numpy"><a href="#numpy" name="numpy">#</a>NumPy</h2><p><strong>Array manipulation mini-language. It can run up to one hundred times faster than the equivalent Python code. An even faster alternative that runs on a GPU is called CuPy.</strong></p><pre><code class="python language-python hljs"><span class="hljs-comment"># $ pip3 install numpy</span>
<span class="hljs-keyword">import</span> numpy <span class="hljs-keyword">as</span> np
</code></pre></div>
@ -2916,7 +2919,7 @@ $ pyinstaller script.py --add-data '&lt;path&gt;:.' <span class="hljs-comment">
<footer>
<aside>December 26, 2022</aside>
<aside>December 27, 2022</aside>
<a href="https://gto76.github.io" rel="author">Jure Šorn</a>
</footer>

1
pdf/remove_links.py
View File

@ -22,6 +22,7 @@ MATCHES = {
'<strong>Bools will be stored and returned as ints and dates as <a href="#encode">ISO formatted strings</a>.</strong>': '<strong>Bools will be stored and returned as ints and dates as ISO formatted strings (p. 9).</strong>',
'<strong>An object with the same interface called ProcessPoolExecutor provides true parallelism by running a separate interpreter in each process. All arguments must be <a href="#pickle">pickable</a>.</strong>': '<strong>An object with the same interface called ProcessPoolExecutor provides true parallelism by running a separate interpreter in each process. All arguments must be pickable (p. 25).</strong>',
'<strong>Asyncio module also provides its own <a href="#queue">Queue</a>, <a href="#semaphoreeventbarrier">Event</a>, <a href="#lock">Lock</a> and <a href="#semaphoreeventbarrier">Semaphore</a> classes.</strong>': '<strong>Asyncio module also provides its own Queue, Event, Lock and Semaphore classes (p. 30).</strong>',
'<strong>The "latest and greatest" profiler that can also monitor GPU usage is called <a href="https://github.com/plasma-umass/scalene">Scalene</a>.</strong>': '<strong>The "latest and greatest" profiler that can also monitor GPU usage is called Scalene.</strong>',
}

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