Python Generators & Iterators

1. What are Iterators and Generators?

Both iterators and generators are used to go through values one by one.

In simple words:
👉 They give one value at a time
👉 They save memory
👉 They are useful for large data

2. What is an Iterator?

An iterator is an object that:

  • Remembers its position

  • Gives next value when asked

Python uses:


  •  

3. Simple Iterator Example (List)

Example


 

Output:


 

4. Iterator Stops Automatically

When values finish, Python gives StopIteration error.

Example


 

5. Iterator with for Loop (Easy Way)

Python handles iterator automatically in for loop.

Example


 

6. Create Your Own Iterator (Basic)

To create your own iterator, you need:


  •  

Example


 

7. What is a Generator?

A generator is a simpler way to create an iterator.

In simple words:
👉 Generator is a function
👉 Uses yield instead of return
👉 Automatically remembers state

8. Simple Generator Example

Example


 

9. Generator vs Normal Function

Normal Function


 

👉 Returns only once.

Generator Function


 

👉 Returns many values, one by one.

10. Generator with Loop

Example


 

11. Generator Expression (Short Form)

Like list comprehension, but uses ().

Example


 

12. Generator vs Iterator (Simple Table)

Iterator Generator
Uses class Uses function
More code Less code
Manual control Automatic
Harder Easier

👉 Beginners prefer generators.

13. Why Use Generators & Iterators?

✔ Save memory
✔ Faster for big data
✔ Clean code
✔ Used in real applications

14. Common Beginner Mistakes

❌ Using return instead of yield


 

❌ Not a generator.

❌ Reusing Generator


 

👉 Generator works only once.

15. Simple Practice Examples

Example 1: Even Numbers Generator


 

Example 2: Countdown Generator


 

Example 3: Iterator from String


 

16. Summary (Generators & Iterators)

✔ Both give values one by one
✔ Iterators use iter() and next()
✔ Generators use yield
✔ Generators are easier
✔ Very useful for large data

📘 Perfect for Beginner & Intermediate eBook

This chapter is ideal for:

  • Python learners

  • Interview preparation

  • Memory-efficient coding

  • Real-world projects

If you want next, I can write:

  • Advanced Generators

  • Iterator vs Generator (Deep)

  • Real Python Projects

  • Python Performance Tips

Just tell me 😊

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