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Introduction to Sorting Algorithms in Python (Summary)

Liam Pulsifer
Introduction to Sorting Algorithms in Python Liam Pulsifer 01:07
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Sorting is an essential tool in any Pythonista’s toolkit. With knowledge of the different sorting algorithms in Python and how to maximize their potential, you’re ready to implement faster, more efficient apps and programs!

In this course, you learned:

  • How Python’s built-in .sort() works behind the scenes
  • What Big O notation is and how to use it to compare the efficiency of different algorithms
  • How to measure the actual time spent running your code
  • How to implement five different sorting algorithms in Python
  • What the pros and cons are of using different algorithms
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Course Slides (.pdf)

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00:00 During this course, you’ve become a master of sorting algorithms in Python. You’ve learned what sorting is and why it’s such a powerful tool. You’ve learned different features of sorting algorithms, like in-place algorithms versus stable sorts versus different runtime considerations, et cetera, and you’ve learned about the trade-offs that are inherent to those different designs. And finally, of course, you’ve learned how to implement many different common sorting algorithms in Python, and you’ve learned how to balance ease of implementation versus performance in practice, and you’ve learned how to analyze all of those trade-offs that we’ve discussed.

00:38 On this slide, I have an overview of the different algorithms I’ve covered over the course of this series, including their runtimes, their space complexity, whether they’re stable, and whether they’re in-place.

00:48 And this is just for your review, so feel free to download these slides from the link below and you’ll be able to just look over this at your own leisure.

00:57 I hope you had a good time watching this video and I hope you found it valuable. I certainly had a fun time recording it. Thanks so much and good luck in your future Python endeavors.

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