Python Inheritance

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Inheritance Definition

Inheritance allows a class (child) to acquire properties and methods of another class (parent).

This promotes:

  • Code reusability
  • Hierarchy / structure
  • Cleaner and scalable programs

Basic Inheritance

class Animal:
    def speak(self):
        print("Animals make sound")

class Dog(Animal):  # Dog inherits from Animal
    pass

d = Dog()
d.speak()

Explanation

  • Animal is the parent/base class.
  • Dog is the child/derived class.
  • Dog gets the speak() method without writing it again.

Single Inheritance

class Parent:
    def show(self):
        print("This is parent class")

class Child(Parent):
    def display(self):
        print("This is child class")

c = Child()
c.show()
c.display()

đź“ť Child gets access to both:
➡ show() (from Parent)
➡ display() (its own)

Multilevel Inheritance

class A:
    def feature1(self):
        print("Feature 1")

class B(A):
    def feature2(self):
        print("Feature 2")

class C(B):
    def feature3(self):
        print("Feature 3")

c = C()
c.feature1()
c.feature2()
c.feature3()

📝 Chain of inheritance: A → B → C
Class C inherits everything.

Multiple Inheritance

class Father:
    def bike(self):
        print("Father's bike")

class Mother:
    def car(self):
        print("Mother's car")

class Child(Father, Mother):
    pass

obj = Child()
obj.bike()
obj.car()

đź“ť Child receives methods of both parents.

Hierarchical Inheritance

class Animal:
    def sound(self):
        print("Animal sound")

class Dog(Animal):
    pass

class Cat(Animal):
    pass

d = Dog()
c = Cat()
d.sound()
c.sound()

📝 One parent → Multiple children.

Using super() to Access Parent Data

class Parent:
    def __init__(self):
        print("Parent constructor")

class Child(Parent):
    def __init__(self):
        super().__init__()
        print("Child constructor")

c = Child()

đź“ť super() is used to call parent methods/constructors.

Python Generators

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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?

FeatureWhy it matters
Lazy evaluationValues are produced on demand, not all at once
Memory efficientDoesn’t store entire data in memory
Improves performanceFaster for large datasets / loops
Infinite sequencesPossible 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

KeywordBehavior
returnExits function and sends a single value
yieldPauses 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

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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?

PurposeExample Use Case
Add functionality without editing original codeLogging, Authorization
Reuse common logicValidation
Track performanceExecution time calculator
Restrict accessAdmin/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

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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 doos Module Feature
Get current directoryos.getcwd()
Change directoryos.chdir()
Create/Remove foldersos.mkdir() / os.rmdir()
List files and foldersos.listdir()
Work with environment variablesos.environ
Join file paths safelyos.path.join()
Delete a fileos.remove()
Run system commandsos.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)

FunctionDescription
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 List MCQs

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Python List MCQ Quiz (Random 10 Questions)

Python String MCQs

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Python String Quiz (Random 10 of 50)

🔄 Refresh the page to get a new set of questions.

⏳ Time Left: 120 seconds

Python Read/Write CSV

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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

đź’ˇ 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

TaskMethod
Write rowwriter.writerow()
Write multiple rowswriter.writerows()
Read CSVcsv.reader()
Read as dictcsv.DictReader()
Write dictcsv.DictWriter()
Append data"a" mode
Change delimiterdelimiter=";"

Python Read/Write JSON

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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

TaskFunction
Write Python → JSON filejson.dump()
Read JSON file → Pythonjson.load()
Python → JSON stringjson.dumps()
JSON string → Pythonjson.loads()

Python Read/Write Excel File

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openpyxl for Excel Handling

Install openpyxl (if not installed)

pip install openpyxl

Create / Write to an Excel File

from openpyxl import Workbook

wb = Workbook()                # Create workbook
ws = wb.active                 # Select active sheet
ws.title = "Students"          # Rename sheet

# Write data
ws['A1'] = "Name"
ws['B1'] = "Marks"
ws['A2'] = "Deepesh"
ws['B2'] = 85

wb.save("students.xlsx")       # Save file
print("File created successfully")

Write Multiple Rows

Using append()

from openpyxl import Workbook

wb = Workbook()
ws = wb.active

data = [
    ["Name", "Marks"],
    ["Ankit", 90],
    ["Riya", 88],
    ["Aman", 76]
]

for row in data:
    ws.append(row)

wb.save("marks.xlsx")
print("Data written successfully")

Read Excel File

Read the whole sheet of data

from openpyxl import load_workbook

wb = load_workbook("marks.xlsx")
ws = wb.active

for row in ws.rows:
    for cell in row:
        print(cell.value, end="  |  ")
    print()

Read Specific Cells

By cell address

from openpyxl import load_workbook

wb = load_workbook("marks.xlsx")
ws = wb.active

print(ws['A1'].value)   # Header
print(ws['B2'].value)   # Marks of 2nd row

Read by Rows / Columns

By Row

for row in ws.iter_rows(min_row=1, max_row=4, values_only=True):
    print(row)

By Column

for col in ws.iter_cols(min_col=1, max_col=2, values_only=True):
    print(col)

Update Existing Excel File

from openpyxl import load_workbook

wb = load_workbook("marks.xlsx")
ws = wb.active

ws['B3'] = 95  # Update marks for row 3
wb.save("marks.xlsx")

print("File updated")

Add a New Sheet

wb = load_workbook("marks.xlsx")
wb.create_sheet(title="Summary")   # Add at end
wb.save("marks.xlsx")

Delete Sheet

wb = load_workbook("marks.xlsx")
del wb["Summary"]
wb.save("marks.xlsx")

Get Sheet Names

print(wb.sheetnames)

Apply Basic Formatting

from openpyxl.styles import Font

ws['A1'].font = Font(bold=True, size=12, color="FF0000")
ws['B1'].font = Font(bold=True, size=12)
wb.save("marks.xlsx")

Calculate Total & Average

from openpyxl import Workbook

wb = Workbook()
ws = wb.active

data = [
    ["Name", "M1", "M2", "M3", "Total", "Average"],
    ["Raj", 85, 90, 88],
    ["Simran", 78, 82, 80],
]

for row in data:
    ws.append(row)

# Add formulas
ws['E2'] = "=B2+C2+D2"
ws['F2'] = "=E2/3"
ws['E3'] = "=B3+C3+D3"
ws['F3'] = "=E3/3"

wb.save("report.xlsx")
print("Report created!")

Summary

TaskMethod
Create fileWorkbook()
Load fileload_workbook()
Write cellws[‘A1’] = value
Append rowws.append()
Readws.rows, iter_rows()
FormattingFont()

Program Examples

Read Excel File

import openpyxl

def read_excel_file(file_path, sheet_name, cell_name):
    # Load the workbook
    workbook = openpyxl.load_workbook(file_path)
    # Select the specified sheet
    sheet = workbook[sheet_name]
    # Read the value from the specified cell
    cell_value = sheet[cell_name].value
    print(f"Value in {cell_name} of sheet '{sheet_name}': {cell_value}")

# read one cell data 
read_excel_file(file_path='users_data.xlsx', sheet_name='Sheet1', cell_name='A2')

Write Excel File

def write_excel_file(file_path, sheet_name, cell_name, data):
    # Load the workbook
    workbook = openpyxl.load_workbook(file_path)
    # Select the specified sheet
    sheet = workbook[sheet_name]
    # Write data to the specified cell
    sheet[cell_name] = data
    
    # Save the workbook
    workbook.save(file_path)
    print(f"Data written to sheet '{sheet_name}' starting at {cell_name}.")



write_excel_file(file_path='users_data.xlsx', sheet_name='Sheet1', cell_name='D2', data='Learning Excel with Python')

Variables Scope In Python

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1. Local Scope Example

Variables declared inside a function are local to that function.

def my_function():
    x = 10   # local variable
    print("Inside function:", x)

my_function()
print("Outside function:", x)  # ❌ Error: x is not defined

2. Global Scope Example

Variable declared outside a function can be accessed anywhere.

x = 50   # global variable

def display():
    print("Inside function:", x)

display()
print("Outside function:", x)

3. Modifying Global Variable Inside a Function

Use the global keyword to change it.

count = 0

def update():
    global count
    count = count + 1
    print("Inside function:", count)

update()
print("Outside function:", count)

4. Enclosing Scope (Nested Functions)

Inner function can access variable from the outer function.

def outer():
    name = "Python"   # enclosing variable

    def inner():
        print("Accessing enclosing variable:", name)
    
    inner()

outer()

5. Modify Enclosing Variable using nonlocal

The nonlocal keyword allows modifying a variable in the outer (enclosing) function.

def outer():
    count = 10
    
    def inner():
        nonlocal count
        count += 5
        print("Inside inner:", count)
    
    inner()
    print("Inside outer:", count)

outer()