Python Generators Introduction

A Generator in Python is a special type of function that yields values one at a time, instead of returning them all at once.

Generators are memory-efficient and used for working with large datasets, streams, or infinite sequences.

Why Generators?

Feature	Why it matters
Lazy evaluation	Values are produced on demand, not all at once
Memory efficient	Doesn’t store entire data in memory
Improves performance	Faster for large datasets / loops
Infinite sequences	Possible to generate endless values

Regular Function vs Generator

Normal Function

def numbers():
    return [1,2,3]

Generator Function

def numbers():
    yield 1
    yield 2
    yield 3

The keyword yield makes it a generator.

How to Use a Generator

def numbers():
    yield 1
    yield 2
    yield 3

gen = numbers()
print(next(gen))  # 1
print(next(gen))  # 2
print(next(gen))  # 3

Generator with Loop

def countdown(n):
    while n > 0:
        yield n
        n -= 1

for num in countdown(5):
    print(num)

Difference Between return and yield

Keyword	Behavior
return	Exits function and sends a single value
yield	Pauses function, saves state, returns value, resumes on next call

Generator Expression

List comprehension

squares = [x*x for x in range(5)]

Generator expression

squares = (x*x for x in range(5))
print(squares)         # <generator object>
print(next(squares))   # 0, then 1, 4, 9...

Practical Examples

Generate Even Numbers

def even_numbers(limit):
    for n in range(limit+1):
        if n % 2 == 0:
            yield n

for i in even_numbers(10):
    print(i)

Read Large Files Line by Line (Memory Friendly)

def read_file(filepath):
    with open(filepath) as f:
        for line in f:
            yield line

for line in read_file("large_data.txt"):
    print(line)

Infinite Generator (Be careful!)

def infinite_counter():
    num = 1
    while True:
        yield num
        num += 1

gen = infinite_counter()
print(next(gen))
print(next(gen))

Fibonacci Series Generator

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

for num in fibonacci(10):
    print(num)

Generator to Filter Data

def filter_positive(numbers):
    for num in numbers:
        if num > 0:
            yield num

nums = [-4, 3, 5, -1, 9]
for n in filter_positive(nums):
    print(n)

Python Decorators

Decorator Definition

A decorator in Python is a function that modifies the behavior of another function, without changing its code.

Think of a decorator as adding a layer of functionality before and/or after the original function runs.

Why Use Decorators?

Purpose	Example Use Case
Add functionality without editing original code	Logging, Authorization
Reuse common logic	Validation
Track performance	Execution time calculator
Restrict access	Admin/user roles

Basic Decorator Structure

def decorator_function(original_function):
    def wrapper_function():
        # Code before
        original_function()
        # Code after
    return wrapper_function

Applying a Decorator

@decorator_function
def display():
    print("Display function executed")

The @decorator_function applies extra behavior to the display() function.

Basic Example

def my_decorator(func):
    def wrapper():
        print("Before function runs")
        func()
        print("After function runs")
    return wrapper

@my_decorator
def greet():
    print("Hello!")

greet()

Output:

Before function runs
Hello!
After function runs

Decorator With Arguments

def decorator(func):
    def wrapper(*args, **kwargs):
        print("Arguments:", args, kwargs)
        return func(*args, **kwargs)
    return wrapper

@decorator
def add(a, b):
    print("Sum =", a + b)

add(5, 3)

Decorator Returning a Value

def decorator(func):
    def wrapper(*args):
        result = func(*args)
        print("Function returned:", result)
        return result
    return wrapper

@decorator
def multiply(x, y):
    return x * y

multiply(4, 5)

Real-World Example – Logging

def logger(func):
    def wrapper(*args, **kwargs):
        print(f"Running function: {func.__name__}")
        return func(*args, **kwargs)
    return wrapper

@logger
def show():
    print("Inside show function")

show()

Example – Execution Time Calculator

import time

def timer(func):
    def wrapper(*args, **kwargs):
        start = time.time()
        result = func(*args, **kwargs)
        end = time.time()
        print(f"Execution Time: {end-start:.5f} seconds")
        return result
    return wrapper

@timer
def slow_function():
    time.sleep(2)

slow_function()

Authentication / Access Control

def require_admin(func):
    def wrapper(user):
        if user != "admin":
            print("Access Denied!")
        else:
            return func(user)
    return wrapper

@require_admin
def delete_data(user):
    print("Data deleted successfully!")

delete_data("guest")
delete_data("admin")

Decorators with Parameters (Advanced)

Sometimes we need the decorator to accept its own argument:

def repeat(num):
    def decorator(func):
        def wrapper():
            for _ in range(num):
                func()
        return wrapper
    return decorator

@repeat(3)
def hello():
    print("Hello")

hello()

Output

Hello
Hello
Hello

Nesting Multiple Decorators

def bold(func):
    def wrapper():
        print("<b>", end="")
        func()
        print("</b>")
    return wrapper

def italic(func):
    def wrapper():
        print("<i>", end="")
        func()
        print("</i>")
    return wrapper

@bold
@italic
def text():
    print("Decorated Text", end="")

text()

Python OS Module

Introduction

The os module in Python provides functions to interact with the operating system. It allows you to work with files, folders, system paths, and environment variables and execute system commands.

Why Use the `os` Module?

Task you want to do	`os` Module Feature
Get current directory	os.getcwd()
Change directory	os.chdir()
Create/Remove folders	os.mkdir() / os.rmdir()
List files and folders	os.listdir()
Work with environment variables	os.environ
Join file paths safely	os.path.join()
Delete a file	os.remove()
Run system commands	os.system()

Importing OS Module

import os

Directory Operations

Get the current working directory

import os
print(os.getcwd())

Change working directory

os.chdir("C:/Users")

List all files and folders

print(os.listdir())

Create and Delete Directories

Create a new folder

os.mkdir("myfolder")

Remove a folder (only if empty)

os.rmdir("myfolder")

Create multiple nested directories

os.makedirs("main/subfolder/new")

Remove nested directories

os.removedirs("main/subfolder/new")

File Handling

Delete a file

os.remove("sample.txt")

Rename a file

os.rename("oldname.txt", "newname.txt")

Path Operations (os.path)

Function	Description
`os.path.join()`	Safely join folder and file names
`os.path.exists()`	Check if path/file exists
`os.path.isdir()`	Check if the path is file
`os.path.isfile()`	Check if the path is a file
`os.path.getsize()`	Get file size in bytes

Example

# This will join the folder path and file name.
path = os.path.join("folder", "file.txt")

# This will return True if path exists.
print(os.path.exists(path))

# get size of file 
print(os.path.getsize(path))

Environment Variables

View environment variables

print(os.environ)

Fetch a specific variable

print(os.environ.get("PATH"))

Run System Commands

Open Command Prompt / Terminal command

# get list of file and folder in windos current directory.
os.system("dir")     # Windows

# get list of file and folder in linux current directory.
os.system("ls")      # Mac/Linux

Examples of Python OS Module

Create a Folder Only If It Doesn’t Exist

import os

folder = "project_data"

if not os.path.exists(folder):
    os.mkdir(folder)
    print("Folder created")
else:
    print("Folder already exists")

List Files Only (Exclude folders)

import os

for item in os.listdir():
    if os.path.isfile(item):
        print("File:", item)

List Folders Only (Exclude files)

import os

for item in os.listdir():
    if os.path.isdir(item):
        print("Folder:", item)

Recursively List Files from All Subdirectories

import os

path = "C:/Users"
for root, dirs, files in os.walk(path):
    print("Current Path:", root)
    print("Folders:", dirs)
    print("Files:", files)
    print("----------")

Count Number of Files and Folders

import os

files = 0
folders = 0

for item in os.listdir():
    if os.path.isfile(item):
        files += 1
    elif os.path.isdir(item):
        folders += 1

print("Files:", files)
print("Folders:", folders)

Copy File to Another Folder (Using os)

os doesn’t have copy directly, so use system command

import os
os.system("copy source.txt destination\\")   # Windows
os.system("cp source.txt destination/")      # Linux/Mac

Get File Size in KB / MB

import os

file = "example.txt"
size = os.path.getsize(file)  # in bytes

print(size / 1024, "KB")
print(size / (1024*1024), "MB")

Check File Permissions

import os

filepath = "example.txt"

print("Readable:", os.access(filepath, os.R_OK))
print("Writable:", os.access(filepath, os.W_OK))
print("Executable:", os.access(filepath, os.X_OK))

Execute Multiple Commands at Once

import os

os.system("dir && echo Hello World")  # Windows
# os.system("ls; echo Hello World")   # Linux/Mac

Change File Permission (Linux/Mac)

import os

os.chmod("script.sh", 0o755)  # Owner read/write/execute, others read/execute

Python Read/Write CSV

What is a CSV File?

CSV stands for Comma-Separated Values and is commonly used for tabular data like spreadsheets.

Python has a built-in csv module for handling CSV files.

import csv

Write to CSV File

Write Rows Manually

import csv

with open("students.csv", "w", newline="") as file:
    writer = csv.writer(file)
    
    writer.writerow(["Name", "Age", "City"])  # Header
    writer.writerow(["Deepesh", 30, "Delhi"])
    writer.writerow(["Riya", 25, "Mumbai"])

Write Multiple Rows (Loop / List)

import csv

data = [
    ["Name", "Age", "City"],
    ["Aman", 28, "Pune"],
    ["Neha", 24, "Chennai"],
    ["Kunal", 29, "Bangalore"]
]

with open("data.csv", "w", newline="") as file:
    writer = csv.writer(file)
    writer.writerows(data)   # write all rows at once

Read CSV File

Read and Print Entire File

import csv

with open("students.csv", "r") as file:
    reader = csv.reader(file)
    
    for row in reader:
        print(row)

Read CSV as Dictionary

💡 Best when the first row contains headers.

import csv

with open("students.csv", "r") as file:
    reader = csv.DictReader(file)
    
    for row in reader:
        print(row["Name"], row["City"])

Write CSV Using Dictionary

import csv

data = [
    {"Name": "Raj", "Age": 27, "City": "Delhi"},
    {"Name": "Simran", "Age": 23, "City": "Kolkata"}
]

with open("students_dict.csv", "w", newline="") as file:
    fieldnames = ["Name", "Age", "City"]
    writer = csv.DictWriter(file, fieldnames=fieldnames)

    writer.writeheader()
    writer.writerows(data)

Append to a CSV File

import csv

with open("students.csv", "a", newline="") as file:
    writer = csv.writer(file)
    writer.writerow(["Kiran", 22, "Hyderabad"])

Handling Custom Delimiters

Example: Semi-colon ; separated file

import csv

with open("data_semicolon.csv", "r") as file:
    reader = csv.reader(file, delimiter=";")
    for row in reader:
        print(row)

Real Example: CSV Filtering

Print only rows where Age > 25

import csv

with open("students.csv", "r") as file:
    reader = csv.DictReader(file)
    
    for row in reader:
        if int(row["Age"]) > 25:
            print(row)

Summary

Task	Method
Write row	`writer.writerow()`
Write multiple rows	`writer.writerows()`
Read CSV	`csv.reader()`
Read as dict	`csv.DictReader()`
Write dict	`csv.DictWriter()`
Append data	`"a"` mode
Change delimiter	`delimiter=";"`

Python Read/Write JSON

JSON in Python

JSON (JavaScript Object Notation) is used for storing and exchanging data, commonly in APIs and configuration files.

Python has a built-in module:

import json

Write (Save) JSON to a File

Example Dictionary/Data

data = {
    "name": "Deepesh",
    "age": 30,
    "skills": ["Python", "Selenium", "Automation"]
}

Save to JSON file

import json

with open("data.json", "w") as file:
    json.dump(data, file, indent=4)

indent=4 makes the JSON formatted & readable.

Read (Load) JSON from a File

import json

with open("data.json", "r") as file:
    content = json.load(file)
    print(content)

Output

{'name': 'Deepesh', 'age': 30, 'skills': ['Python', 'Selenium', 'Automation']}

Now content is a Python dictionary, and you can access elements like:

print(content["name"])
print(content["skills"][1])

Convert Python Data ↔ JSON String

Convert Python → JSON string

import json

person = {"city": "Delhi", "pin": 110001}
json_string = json.dumps(person)
print(json_string)

Convert JSON string → Python

import json

json_str = '{"status": "success", "code": 200}'
data = json.loads(json_str)
print(data)

Update JSON File

import json

# Read existing content
with open("data.json", "r") as file:
    data = json.load(file)

# Modify data
data["age"] = 31
data["skills"].append("API Testing")

# Write back to file
with open("data.json", "w") as file:
    json.dump(data, file, indent=4)

Work with Lists in JSON

Example JSON file (`employees.json`)

[
    {"id": 1, "name": "Ankit"},
    {"id": 2, "name": "Riya"}
]

Add a new record

import json

with open("employees.json", "r") as file:
    employees = json.load(file)

employees.append({"id": 3, "name": "Aman"})

with open("employees.json", "w") as file:
    json.dump(employees, file, indent=4)

Summary

Task	Function
Write Python → JSON file	json.dump()
Read JSON file → Python	json.load()
Python → JSON string	json.dumps()
JSON string → Python	json.loads()

Python String MCQ Quiz (Random 10 from 50)

Python Loops MCQ Quiz (Random 10 from 50)

Python IF Conditions MCQ Quiz (Random 10 from 50)

Python Datatypes MCQ Quiz (Random 10 Questions)

Python Variables MCQ Quiz (Random 10 of 50 Questions)

Python Generators Introduction

Why Generators?

Regular Function vs Generator

Normal Function

Generator Function

How to Use a Generator

Generator with Loop

Difference Between return and yield

Generator Expression

List comprehension

Generator expression

Practical Examples

Generate Even Numbers

Read Large Files Line by Line (Memory Friendly)

Infinite Generator (Be careful!)

Fibonacci Series Generator

Generator to Filter Data

Decorator Definition

Why Use Decorators?

Basic Decorator Structure

Applying a Decorator

Basic Example

Decorator With Arguments

Decorator Returning a Value

Real-World Example – Logging

Example – Execution Time Calculator

Authentication / Access Control

Decorators with Parameters (Advanced)

Nesting Multiple Decorators

Introduction

Why Use the os Module?

Importing OS Module

Directory Operations

Get the current working directory

Change working directory

List all files and folders

Create and Delete Directories

Create a new folder

Remove a folder (only if empty)

Create multiple nested directories

Remove nested directories

File Handling

Delete a file

Rename a file

Path Operations (os.path)

Example

Environment Variables

View environment variables

Fetch a specific variable

Run System Commands

Open Command Prompt / Terminal command

Examples of Python OS Module

Create a Folder Only If It Doesn’t Exist

List Files Only (Exclude folders)

List Folders Only (Exclude files)

Recursively List Files from All Subdirectories

Count Number of Files and Folders

Copy File to Another Folder (Using os)

Get File Size in KB / MB

Check File Permissions

Execute Multiple Commands at Once

Change File Permission (Linux/Mac)

What is a CSV File?

Write to CSV File

Write Rows Manually

Write Multiple Rows (Loop / List)

Read CSV File

Read and Print Entire File

Read CSV as Dictionary

Write CSV Using Dictionary

Append to a CSV File

Handling Custom Delimiters

Real Example: CSV Filtering

Print only rows where Age > 25

Summary

Why Use the `os` Module?

Example JSON file (`employees.json`)