Monitor performance issues & errors in your code

Faster Python Programs: Measure, Don't Guess

Episode #66, published Thu, Jul 7, 2016, recorded Mon, Jul 4, 2016

Python is a wonderful programming language that is often underestimated because it's so clear and simple. Oftentimes people mistake this simplicity for being too simple for real-programs. After all, you didn't even struggle to get your program to link against an incompatible static library or battle a DLL version mismatch in your Python app today did you?

Usually we find this simple and clear programming language to be powerful and fast. But what happens when it's not fast enough? Do you have to stop and rewrite it in C, C#, or Java?

Well before you do something drastic, Mike Mueller is here to teach us the techniques and steps to determine why our Python programs might be slow and give us some tips to make them faster.

Links from the show:

PyCon Talk by Mike: youtube.com/watch?v=JDSGVvMwNM8
SnakeViz Project: jiffyclub.github.io/snakeviz
line_profiler: pypi.io/project/line_profiler
Pympler mem profiler: pypi.io/project/Pympler
memory_profiler: pypi.io/project/memory_profiler
Python Academy (Mike's company): python-academy.com
xonsh: xonsh.org
Article: Amazon found every 100ms of latency cost them 1% in sales:
highscalability.com/latency-everywhere-and-it-costs-you-sales-how-crush-it

Stitcher and Talk Python Podcast: A Farewell Letter:
blog.michaelckennedy.net
The Course Everyone New to Python Desperately Needs to Take:
datadependence.com/2016/07/write-pythonic-code-like-a-seasoned-developer


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