8 Python Generators

1. What is a Generator?

A generator is a special type of function that gives values one by one instead of all at once.

In simple words:
👉 A normal function returns everything at once
👉 A generator remembers its place
👉 It gives the next value only when asked

2. Why Use Generators?

Generators are useful because:

• They save memory

• They are fast for big data

• They work one step at a time

3. Generator vs Normal Function

Normal Function

👉 Returns all values together.

Generator Function

👉 Returns values one by one.

4. Creating a Simple Generator

We use the keyword yield to create a generator.

Example

Output:

5. Generator with Loop

Example

6. How yield Works

• yield pauses the function

• Saves the value

• Continues from same place next time

7. Generator Example: Even Numbers

Example

8. Generator Expression (Short Form)

 

Example

9. Generator vs List (Memory Example)

List

👉 Uses more memory.

Generator

👉 Uses very little memory.

10. Generator Stops Automatically

When values are finished, generator stops.

Example

11. Common Beginner Mistakes

❌ Using return Instead of yield

❌ Generator stops at return.

❌ Calling Generator Again

👉 Generator runs only once.

12. Real-Life Example (Read Data Slowly)

Example

13. Simple Practice Examples

Example 1: Countdown Generator

Example 2: Squares Generator

Example 3: Odd Numbers

14. Summary (Python Generators)

✔ Use yield
✔ Returns values one by one
✔ Saves memory
✔ Faster for big data
✔ Generator runs only once

📘 Perfect for Beginner eBook

This chapter is ideal for:

• Python beginner books

• School & college students

• Self-learners

If you want next, I can write:

• Iterator vs Generator

• Modules

• Exception Handling

• File Handling

• Mini Python Projects

Just tell me 😊