Python | Algorithms | Data Structures | Cyber ​​Security | Networks

In Python, generators are memory-efficient iterables created with functions using yield instead of return, allowing lazy evaluation for large datasets or infinite sequences. They're ideal for advanced scenarios like streaming data or coroutines.

def fibonacci(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

# Usage: list(fibonacci(10)) -> [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]

🆘 @DataScience4

Please open Telegram to view this post

VIEW IN TELEGRAM

👍5

www.tgoop.com/DataScience4/8509

458 viewsOct 25 at 12:34

In Python, generators are memory-efficient iterables created with functions using yield instead of return, allowing lazy evaluation for large datasets or infinite sequences. They're ideal for advanced scenarios like streaming data or coroutines.

def fibonacci(n):
    a, b = 0, 1
    for _ in range(n):
        yield a
        a, b = b, a + b

# Usage: list(fibonacci(10)) -> [0, 1, 1, 2, 3, 5, 8, 13, 21, 34]