🔹 Introduction

Python generators provide a powerful way to work with iterators and lazy evaluation. They allow you to create functions that yield values one at a time, instead of returning everything at once.
This can save memory and improve performance, especially when working with large datasets.

🎯 Objective

In this guide, you’ll learn how to:

• Create a generator using the yield keyword
• Use a generator in a for loop
• Understand how generators help with memory efficiency

💻 Example Code

def number_generator(n):
    """A simple generator that yields numbers from 1 to n."""
    for i in range(1, n + 1):
        yield i

# Using the generator
print("Generated numbers:")
for number in number_generator(5):
    print(number)
    

📘 Explanation

Let’s break down the program:

• number_generator(n): A generator function that uses yield to produce numbers one at a time from 1 to n.
• yield: Pauses the function and returns a value. On next call, continues from where it left off.
• for number in number_generator(5): Iterates through each yielded value until the generator is exhausted.

🚀 How to Run the Program

You can run this script in any Python 3 environment:

• Save the code in a file named generator_example.py
• Open a terminal or command prompt
• Run the command: python generator_example.py
• You should see the numbers 1 through 5 printed, one per line