#100DaysOfCode in Python Transcripts
Chapter: Days 49-51: Measuring performance
Lecture: A quantum warning
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Now, before I turn you loose to go work on the code on your own and do your own profiling, I want to give you a short warning.
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It's not a major warning, but there is an effect you really need to be aware of. There's some parallels here with quantum mechanics;
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in quantum mechanics we have Heisenberg's uncertainty principle where it talks about the more precisely you know
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the position of something, the less precisely you can tell its speed and momentum. So, by measuring one thing really closely
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you have actually weakened your understanding of the other. And profilers are like this as well. You have your code operating one way
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and you measure it really deeply, actually put tons of hooks into it to do this monitoring or porting with cProfile
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and it might actually change the performance of your code. So, when you look at those numbers, like for example we said our program takes
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610 milliseconds to run. Maybe it only takes 400 milliseconds to run, but with profiling it takes 600 and these effects are not evenly distributed.
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It's not like, "Well, the whole program slows down 20%." No. Some of it is barely affected. Some of it's massively affected
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and I would say a general rule is: the more things you do in small pieces, that's affected more.
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The stuff that's kind of pushed into the standard library, it doesn't have it's hooks in there. So, for example that parse row loop
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looping over every row in CSV probably has some affect where as the sort, that's one line measured and then it's handed off to CPython
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and then it's time when it's back. So, there might be a ton of operations in there but they're not measured.
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So, just be aware this Heisenberg uncertainty principle going on with profilers also somewhat applies to debuggers. So, they kind of both apply here
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but in this context we're concerned about profilers and timing and it really can have a big affect. That said, these profilers are massively helpful
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and much better than your intuition on understanding where your code's slow and how you should optimize it.