What are the advantages of using generators compared to regular functions?

Main advantages of generators over regular functions that return lists or other complete collections:

• Memory efficiency: Generators compute and return items on demand (lazy evaluation), rather than generating the entire sequence at once. This is critical when working with large data volumes or infinite sequences.

• Performance: Since items are generated one by one, processing can begin with the first items without waiting for the entire sequence to be generated.

• Ease of implementation and code readability: For simple iterators, generators are often implemented using the yield keyword inside a function body, which is more concise and understandable than writing a class with __iter__ and __next__ methods.

Example:

# Regular function
def create_list():
    my_list = []
    for i in range(1000000):
        my_list.append(i * 2)
    return my_list

# Generator
def create_generator():
    for i in range(1000000):
        yield i * 2

# For large datasets, the generator will use significantly less memory
# list_data = create_list()  # Can consume a lot of memory
# generator_data = create_generator() # Items are generated on demand during iteration