Effective PyCharm Transcripts
Chapter: Performance and profiling
Lecture: Your turn: Profiling
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0:02
Just like visual debugging is important for understanding how your code works, if you try to understand its performance
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visual tools here also are really, really important, let's go and play with the visual tools for understanding performance in PyCharm.
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Over here on github under 9-performance we already have a little application here, performance app
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so this is similar to the one you just saw in the demo, it's related to this chapter so we're going to come down here
0:30
and we're going to use the tools to understand the app's existing performance and then improve it in a few key areas
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so we're going to go and open up this project, now if you create a virtual environment or you just do it on your main system,
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be aware you need Requests installed for it to work because one of its features is it goes out and makes a call to a web service,
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so notice here, we'll use the profile program this only gets set up once you create a run configuration
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so right click on programs, they run and then you can profile it. So first thing we're going to do is answer a couple of questions,
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what are the three slowest methods and why, and then what is making them slow and then you go through, there's a few to do's in the code
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that says here's a section that could be improved, theoretically, it's got a time.sleep type thing and say
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well what if we use NumPy, maybe that makes it 20 times faster, so make that number 20 times smaller
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or what if we add an index, make it a 100 times smaller, so you can follow a couple of these steps here,
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keep running the performance tools to see what the changes and effects are and we'll make this program faster.