How do different data structures affect performance in Python?

How do different data structures affect performance in Python?

Different data structures in Python, like lists, sets, and dictionaries, have varying performance characteristics. For example, lists allow for fast access but slow insertions, while dictionaries offer average O(1) time complexity for lookups.

Can you explain the time complexity of lists versus dictionaries?

Sure! Lists have O(1) time complexity for accessing elements by index, but O(n) for searching. Dictionaries, on the other hand, provide O(1) average time complexity for lookups, insertions, and deletions due to their hash table implementation.

What about the performance of sets?

Sets in Python also have O(1) average time complexity for lookups, similar to dictionaries. They are particularly useful for membership tests and eliminating duplicates from a collection.

When should I use a list instead of a dictionary?

Use a list when you need ordered data and plan to access elements by their position. Use a dictionary when you need to associate keys with values and require fast lookups.