🟡 Advanced Python · Lesson 22

Iterators and Generators

Iterators और Generators

What are Generators and Iterators?

Generators and Iterators means generators produce values one at a time using yield. They are memory efficient for large data.

In real programs, this topic helps in processing large files. Learn the idea first, then type the program yourself and compare the output.

💡 At a Glance

Point	Details
Course Area	Advanced Python Professional concepts used to make code reusable, clean and project-ready.
Main Use	processing large files
Example File	`generators-iterators.py`
Practice Focus	Run, change values, and explain the output line by line.

Why should you learn this?

It is useful for processing large files.
It connects with saving memory.
It improves your ability to read, write and debug Python programs.

Important Terms

These terms are used directly in this lesson. Understand them before memorising the code.

Term	Meaning
iterator	iterator is an important term in this topic.
yield	Keyword that returns a value and pauses a generator.
next()	Function used to get the next value from an iterator.
lazy evaluation	lazy evaluation is an important term in this topic.
memory efficient	Uses less memory by producing values one by one.

Syntax / Basic Pattern

The simple pattern is: prepare data, apply the concept, then show the result.

Basic Pattern

def count_up_to(limit):
    number = 1
    while number <= limit:
        yield number
        number += 1
for value in count_up_to(3):
    print(value)

Complete Example Program

Python – generators-iterators.py

def count_up_to(limit):
    number = 1
    while number <= limit:
        yield number
        number += 1

for value in count_up_to(3):
    print(value)

Expected Output

1 2 3

Program Explanation

def count_up_to(limit): creates a reusable function.
number = 1 stores a value in number.
while number <= limit: repeats the following indented statements.
yield number performs the next step of the program logic.
number += 1 stores a value in number +.
for value in count_up_to(3): repeats the following indented statements.
print(value) displays information or calculated result on the screen.

Where will you use it?

Processing large files.
Saving memory.
Generating values one by one.

Common Mistakes

Making code complex when a simple function or class is enough.
Not handling possible errors or edge cases.
Mixing project dependencies instead of using a virtual environment.

Practice Tasks

Type the program in generators-iterators.py and run it.
Change input values or sample data and observe the new output.
Create one example related to processing large files.
Write 5 lines explaining the logic in your own words.

Summary

Generators and Iterators is not a theory-only topic. You should be able to explain the meaning, write the example, run it successfully, and use it in a small practical program.

Generators और Iterators क्या है?

Generators और Iterators ka matlab hai: Generators produce values one at a time using yield. They are memory efficient for large data. Simple words me, ye topic practical Python programs likhne me direct use hota hai.

Is topic ko sirf definition ke liye nahi, balki processing large files jaise real examples ke liye practice karein.

यह क्यों सीखना जरूरी है?

Ye processing large files me kaam aata hai.
Ye saving memory se bhi connected hai.
Isse aap code ka output aur errors better samajh paate hain.

Important Terms

Term	Meaning
iterator	iterator is an important term in this topic.
yield	Keyword that returns a value and pauses a generator.
next()	Function used to get the next value from an iterator.
lazy evaluation	lazy evaluation is an important term in this topic.
memory efficient	Uses less memory by producing values one by one.

Syntax / Basic Pattern

Basic idea: pehle data तैयार करें, phir Python logic apply करें, aur finally result display करें.

Basic Pattern

def count_up_to(limit):
    number = 1
    while number <= limit:
        yield number
        number += 1
for value in count_up_to(3):
    print(value)

Complete Example Program

Python – generators-iterators.py

def count_up_to(limit):
    number = 1
    while number <= limit:
        yield number
        number += 1

for value in count_up_to(3):
    print(value)

Expected Output

1 2 3

Program Explanation

def count_up_to(limit): creates a reusable function.
number = 1 stores a value in number.
while number <= limit: repeats the following indented statements.
yield number performs the next step of the program logic.
number += 1 stores a value in number +.
for value in count_up_to(3): repeats the following indented statements.
print(value) displays information or calculated result on the screen.

Practical Uses

Processing large files.
Saving memory.
Generating values one by one.

Common Mistakes

Making code complex when a simple function or class is enough.
Not handling possible errors or edge cases.
Mixing project dependencies instead of using a virtual environment.

Practice Tasks

Program ko generators-iterators.py file me type karke run karein.
Values change karke output compare karein.
processing large files par ek छोटा example banayen.
Logic ko apne words me 5 lines me likhein.

सारांश

Generators and Iterators ko tab complete maanenge jab aap iska meaning, example, output aur practical use clearly explain kar saken.

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