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We all know that python is slower than compiled languages like C. But what can you do about it? Jake VanderPlas, director of research in the physical sciences for the university of Washington's eScience institute, digs into python's internals to explain how it works and what program design choices you can make to use python efficiently.
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Why Python is Slow: Looking Under the Hood
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The Fine Print: The following comments are owned by whoever posted them. We are not responsible for them in any way.
You may be sure that when a man begins to call himself a "realist," he
is preparing to do something he is secretly ashamed of doing.
-- Sydney Harris
(Score: 2) by Angry Jesus on Tuesday May 13 2014, @02:24AM
Python gets a lot of serious use though. As I recall, Dropbox is almost 100% python (so much so that they are developing their own JIT [dropbox.com]). Youtube is also mostly python (with ffmpeg for the video processing).
(Score: 4, Informative) by physicsmajor on Tuesday May 13 2014, @03:11AM
For good reason.
The same reasons, in fact, why you don't waste time optimizing an inefficient string processing routine which, when you profile, gets used 0.01% of your runtime. To turn that around: if Python lets your team hack out 80% of your application in 5% of the time, thanks to these features, that is an obvious massive win.
In my experience (warning: Python dev, I'm biased but also not sugarcoating) this is true. Python results in clearer, easier to maintain code. When I need serious performance there's always Cython or the various methods to hook into lower level libraries, but the remaining >= 80% of the time using Python was a clear and objective win for efficiency and maintainability.
(Score: 2) by kaszz on Tuesday May 13 2014, @04:01AM
Dito for Perl. What I really like is the powerful and easy pattern matching capability. One can mix huge binaries with bit operations and laissez faires operands that stretch arithmetic to string matching without boundaries.
As always if you code to shoot yourself in the foot. The code will deliver your misery.
(Score: 2) by Nerdfest on Tuesday May 13 2014, @10:56AM
Clear, easy to maintain Python code? So, you're the guy.
(Score: 2) by Nerdfest on Tuesday May 13 2014, @10:58AM
Damn, meant perl code. Doh.
(Score: 2) by LaminatorX on Tuesday May 13 2014, @04:21AM
The raw number crunching is slow, but the things I write in Python are network or disk access bound, not CPU bound. I can imagine a sufficiently large data set where that would shift, but in practice it's never happened.