List Comprehensions vs Generators

What's the difference between list comprehensions and generators in Python?

List comprehensions create a list in memory, while generators yield items one at a time, saving memory.

Can you give me an example of both?

Sure! A list comprehension: [x**2 for x in range(5)] creates a list of squares. A generator: (x**2 for x in range(5)) yields squares one by one.

When should I use a generator instead of a list comprehension?

Use generators when dealing with large datasets to save memory, as they generate items on-the-fly.

Are there any performance differences between the two?

Yes, generators are generally more memory-efficient and can be faster for large data, but list comprehensions are faster for smaller datasets.