In this video, the author helps you understand the memory layout of lists. Learn how to optimize list insertion, as well as how to sort them, and use lookups to retrieve information.
- [Instructor] Now let me talk briefly…about algorithm complexity.…So far, we've discussed how we can optimize…the implementation of an algorithm,…for instance, by having NumPy or Numba…do complex arithmetics when we compute the Mandelbrot set…instead of doing it in pure Python,…where every individual operation is slower.…But in some cases, there are different algorithms…to obtain the same outcome, and these algorithms…use a different number of operations.…The classic examples are algorithms to sort a list.…
A simple insertion sort, grow a sorted list of elements…by inserting them one by one in the right spot,…requires a number of operations proportional…to n squared, where n is the size of the list.…Whereas smarter algorithms, such as quicksort,…require a number of operations proportional…to n times the logarithm of n.…One says that the algorithm's running time,…O(n squared) and O(n log n), respectively.…
This is a big topic, but one that you should be mindful of,…and research if needed to improve your code.…
- Designing efficient loops
- Exploiting Python collections
- Writing Pythonic code
- Choosing the best libraries for your tasks
- Downloading webpages with requests
- Parsing HTML with Beautiful Soup
- Manipulating images with Pillow
- Making videos and drawing on maps with matplotlib
- Serving webpages with Jinja2 and Flask
- Working with Python classes
- Taking advantage of functional techniques
- Profiling CPU and memory use
- Exploiting parallelism
Skill Level Intermediate
1. Installation and Setup
Jupyter notebooks3m 19s
2. Writing Python Efficiently
3. Exploiting Python Libraries
4. Advanced: Python Object-Oriented and Functional Programming
5. Introduction to Performance Optimization in Python
Next steps1m 2s
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