#100DaysOfCode in Python Transcripts
Chapter: Days 49-51: Measuring performance
Lecture: Introduction to profiling

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0:00 As you advance further in your Python projects, you're inevitably going to hit a point where you write some code and it's just slower
0:09 than you want it to be. This happens all the time, when you're doing scientific computation, you're calling services,
0:15 maybe you're talking to a database. It really happens a lot on the web 'cause, for popular websites, performance is critical.
0:22 We're going to spend the next couple of days focusing on how to get Python to tell us exactly where it's spending its time.
0:32 Making things faster, that's a different problem. How do we optimize our code, use the right data structures,
0:37 and so on? That's what you might do after this, but this will tell you where things are slow, where you need to focus your effort.
0:44 This whole concept is called profiling and you'll see a lot of it is built right into Python. And there's some great external tools, as well.

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