How can I optimize sorting algorithms in Python?

How can I optimize sorting algorithms in Python?

You can optimize sorting algorithms in Python by choosing the right algorithm for your data size and type. For example, use Timsort (the default in Python) for general purposes, but consider QuickSort or MergeSort for larger datasets.

What are the time complexities of these algorithms?

Timsort has a time complexity of O(n log n) in the average and worst cases. QuickSort also has O(n log n) on average but can degrade to O(n²) in the worst case. MergeSort consistently runs in O(n log n).

Are there any built-in functions in Python for sorting?

Yes, Python provides built-in functions like sorted() and the .sort() method for lists, which use Timsort under the hood.

How can I implement a custom sorting algorithm?

You can implement a custom sorting algorithm by defining a function that follows the sorting logic you want, and then using the sorted() function with the key parameter to specify your custom logic.