What are the complexities of different data structures in Python?

What are the complexities of different data structures in Python?

In Python, data structures like lists, sets, and dictionaries have different time complexities for operations. For example, accessing an element in a list is O(1), while searching for an element in a list is O(n). In contrast, dictionaries offer O(1) average time complexity for lookups.

Can you explain why dictionaries are faster for lookups?

Dictionaries in Python use a hash table for storage, which allows for average O(1) time complexity for lookups. This is because the hash function computes an index where the value is stored, making retrieval very efficient.

What about the space complexity of these data structures?

The space complexity varies: lists require O(n) space, dictionaries also require O(n) space due to their underlying hash table, and sets, which are similar to dictionaries, also require O(n) space.

Are there any scenarios where I should avoid using a list?

Yes, if you need frequent insertions or deletions, consider using a linked list or a deque, as lists can be inefficient for these operations due to their O(n) complexity.