Generator expressions in Python are a concise and memory-efficient way to create iterators. They are similar to list comprehensions but use parentheses instead of square brackets. This allows for the generation of values on-the-fly, which can be particularly useful when dealing with large datasets or when you want to minimize memory usage.

A generator expression is defined using a syntax that resembles a list comprehension. For example, to create a generator that produces the squares of numbers from 0 to n-1, you can use the following code:

squares = (i**2 for i in range(n))

You can iterate over this generator just like any other iterator. For instance, you can use a loop to print the values or convert it to a list if needed.

One of the main advantages of generator expressions is their memory efficiency. Since they yield items one at a time, they do not require the entire list to be stored in memory, making them ideal for large data processing tasks. Additionally, they can improve the readability of your code by reducing the amount of boilerplate code needed to create an iterator ⁴⁵.