Home > python > Ned Batchelder – Big-O: How Code Slows as Data Grows – PyCon 2018

Ned Batchelder – Big-O: How Code Slows as Data Grows – PyCon 2018

Speaker: Ned Batchelder

Big-O is a computer science technique for analyzing how code performs as data gets larger. It’s a very handy tool for the working programmer, but it’s often shrouded in off-putting mathematics.

In this talk, I’ll teach you what you need to know about Big-O, and how to use it to keep your programs running well. Big-O helps you choose the data structures and algorithms that will let your code work efficiently even on large data sets.

You can understand Big-O even if you aren’t a theoretical computer science math nerd. Big-O isn’t as mystical as it appears. It’s wrapped in mathematical trappings, but doesn’t have to be more than a common-sense assessment of how your code will behave.

Slides can be found at: https://speakerdeck.com/pycon2018 and https://github.com/PyCon/2018-slides

Source:
https://realpython.com/must-watch-pycon-talks/#10-refactoring-python-why-and-how-to-restructure-your-code

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