How do list comprehensions affect performance in Python?

How do list comprehensions affect performance in Python?

List comprehensions can significantly improve performance in Python by reducing the overhead of function calls and loops.

Can you give me an example comparing list comprehensions to traditional loops?

Sure! For instance, using a list comprehension: squares = [x**2 for x in range(10)] is faster than using a loop.

What are the memory implications of using list comprehensions?

List comprehensions can use more memory if the resulting list is large, but they are generally more memory-efficient than equivalent loops.

Are there any situations where I should avoid using list comprehensions?

Yes, if the logic is too complex or if readability suffers, it's better to use traditional loops.