Generators provide memory-efficient iteration.
# Generator function
def fibonacci(n):
a, b = 0, 1
for _ in range(n):
yield a
a, b = b, a + b
for num in fibonacci(10):
print(num)
# Generator expression
squares = (x**2 for x in range(1000000))
print(next(squares)) # 0
print(next(squares)) # 1Complete guide to Python decorators covering function decorators, class decorators, decorators with arguments, preserving metadata, and real-world use cases.
Deep dive into Python generators and iterators for memory-efficient data processing, including generator expressions, yield statements, and iterator protocol.
Learn Python decorators including function decorators, class decorators, decorators with arguments, preserving metadata, and practical use cases.