#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,
0:03 you're inevitably going to hit a point
0:05 where you write some code and it's just slower
0:08 than you want it to be.
0:09 This happens all the time,
0:11 when you're doing scientific computation,
0:13 you're calling services,
0:14 maybe you're talking to a database.
0:16 It really happens a lot on the web 'cause,
0:18 for popular websites, performance is critical.
0:21 We're going to spend the next couple of days focusing
0:24 on how to get Python to tell us exactly
0:29 where it's spending its time.
0:31 Making things faster, that's a different problem.
0:33 How do we optimize our code, use the right data structures,
0:36 and so on? That's what you might do after this,
0:39 but this will tell you where things are slow,
0:41 where you need to focus your effort.
0:43 This whole concept is called profiling
0:45 and you'll see a lot of it is built right into Python.
0:47 And there's some great external tools, as well.