How do Python dictionaries compare in performance?

How do Python dictionaries compare in performance to lists?

Python dictionaries are generally faster for lookups compared to lists, especially for large datasets, due to their hash table implementation.

What about memory usage? Are dictionaries more memory-intensive?

Yes, dictionaries typically use more memory than lists because they store key-value pairs and require additional overhead for hashing.

Can you provide an example of when to use a dictionary over a list?

Use a dictionary when you need to associate unique keys with values, like storing user profiles where each user ID is a key.

Are there any performance benchmarks available for this comparison?

Yes, there are benchmarks available that show dictionaries outperform lists in average-case time complexity for lookups, insertions, and deletions.