Whenever you have to choose a list creation method, try multiple implementations and consider what’s easiest to read and understand in your specific scenario. If performance is important, then you can use profiling tools to give you actionable data instead of relying on hunches or guesses about what works the best.
In this course, you learned how to:
- Simplify loops and
map()calls with declarative list comprehensions
- Supercharge your comprehensions with conditional logic
- Create set and dictionary comprehensions
- Determine when code clarity or performance dictates an alternative approach
Remember that while Python list comprehensions get a lot of attention, your intuition and ability to use data when it counts will help you write clean code that serves the task at hand. This, ultimately, is the key to making your code Pythonic!
Congratulations, you made it to the end of the course! What’s your #1 takeaway or favorite thing you learned? How are you going to put your newfound skills to use? Leave a comment in the discussion section and let us know.
Alan ODannel on April 7, 2021
Nice course, informative and flowed at a good pace. I had an understanding on Comprehensions, this course introduced concepts that I was not aware of. Thank you.