Python

Subashini Mannuraja

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Jun 8, 2026

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Python is a high-level, interpreted, object-oriented programming language developed by Guido van Rossum in 1991.

print(“Hello, World!”)

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Modules, Comments and Pip:

Modules in Python:

A module is a file containing Python code that can be reused.

Types of Modules in Python:

Python modules are mainly classified into 3 types:

1. Built-in Modules (Predefined Modules)

These modules come already installed with Python.

You don’t need to install them separately.

Examples

• math
• random
• datetime
• os
• sys

User-Defined Modules

Modules created by programmers according to their needs.

Step 1: Create a file named calculator.py

Step 2: Use the module

External Modules or Third-Party Modules

Modules developed by other programmers and installed using pip.

Examples

• numpy
• pandas
• matplotlib
• tensorflow
• requests

COMMENTS

Comments are notes written for programmers.

TYPES OF COMMENTS

1] Single Line Comment (#)

2] Multi Line Comment ( ‘’’ ‘’’)

PIP(Preferred Installer Program)

PIP is Python’s package manager.

Think of it as:

Play Store for Python

Just as Play Store installs apps,

PIP installs Python packages.

Variables, Data Types, Keywords & Operators

Variables store data values.

name = “Subashini”
age = 21

print(name)
print(age)

Identifiers are names used for variables, functions, classes, etc.

Valid Identifiers:

student_name = “Suba”
_age = 21
marks1 = 95

Invalid Identifiers:

1name = “Suba”
class = “Python”

Data Types in Python

Integer:

An Integer is a data type used to store whole numbers without any decimal point.

x = 10
print(type(x))

Float:

A Float is a data type used to store decimal numbers (floating-point numbers).

y = 10.5
print(type(y))

String:

A String is a sequence of characters enclosed within single quotes (' ') or double quotes (" ").

name = “Python”
print(type(name))

Boolean:

A Boolean is a data type that can store only two values: True or False.

flag = True
print(type(flag))

List:

A list is an ordered, mutable collection.

lst = [1,2,3]

Tuple:

An ordered and immutable collection.

t = (1,2,3)

Set:

An unordered collection of unique elements.

s = {1,2,3}

Dictionary:

Stores data as key-value pairs.

d = {“name”:”Suba”}

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FLOW CONTROL:

Flow control determines the order in which statements are executed in a program.

print(“Statement 1”)
print(“Statement 2”)
print(“Statement 3”)

The statements execute one after another.

Sometimes we need to make decisions based on conditions. That’s where flow control comes in.

If Statement:

The if statement is used to execute a block of code only when a condition is True.

Syntax:

if condition:
statement

If-Else Statement:

The if-else statement executes one block when the condition is True and another block when it is False.

if condition:
statement1
else:
statement2

Elif Statement

elif means "else if".

It is used when multiple conditions need to be checked.

if condition1:
statement
elif condition2:
statement
else:
statement

Nested If Statement:

An if statement inside another if statement is called a Nested If.

if condition1:
# Outer if block

if condition2:
# Inner if block
statements

LOOPS:

A loop is used to execute a block of code repeatedly.

Why Loops?

Without loop:

print(“Hello”)
print(“Hello”)
print(“Hello”)
print(“Hello”)
print(“Hello”)

With loop:
for i in range(5):
print(“Hello”)

While Loop

A while loop executes as long as the condition remains True.

Syntax:

while condition:
statement

Example:

i = 1

while i <= 5:
print(i)
i += 1

For Loop:

A for loop is used to iterate through a sequence such as a list, tuple, string, or range.

for i in [10,20,30]:
print(i)

For Loop Using range():

The range() function generates a sequence of numbers.

for i in range(1,6):
print(i)

Types of range():

range(stop)

Output: 0 1 2 3 4

range(start, stop)

range(1,5)

Output: 1 2 3 4

range(start, stop, step)

range(1,10,2)

Output: 1 3 5 7 9

Nested For Loop:

A for loop inside another for loop is called a Nested For Loop.

for i in range(3):
for j in range(2):
print(i, j)

Output:

0 0
0 1
1 0
1 1
2 0
2 1

STRINGS:

A string is a sequence of characters enclosed within single quotes or double quotes.

name = “Python”

Creating Strings in Python:

Using Single Quotes, Double Quotes, Triple Quotes.

String Indexing and Slicing:

Indexing:

Each character has a position.

P Y T H O N
0 1 2 3 4 5

Example:

name = “PYTHON”

print(name[0])

Output: P

Negative Indexing:

P Y T H O N
-6 -5 -4 -3 -2 -1

print(name[-1])

Output: N

Slicing

Used to extract a portion of a string.

name = “PYTHON”

print(name[0:3])

Output: PYT

Deleting the String:

Deleting means removing the entire string variable from memory.

Example:

name = “Python”

del name

After deletion:

print(name)

Output: NameError

String Formatting:

String formatting is the process of inserting values into a string.

Method 1: Using f-string (Most Common)

name = “Subashini”
age = 21

print(f”My name is {name} and I am {age} years old.”)

Output:

My name is Subashini and I am 21 years old.

Method 2: Using format()

name = “Subashini”

print(“My name is {}”.format(name))

Method 3: Using % Operator

name = “Subashini”

print(“My name is %s” % name)

FUNCTIONS:

A function is a block of code that performs a specific task and can be reused whenever needed.

Why Functions?

Without functions:

print(“Welcome”)
print(“Welcome”)
print(“Welcome”)

With functions:

def greet():
print(“Welcome”)

greet()
greet()
greet()

Creating a Function & Function Calling:

Syntax:

def function_name():
statements

function_name()

Example:

def greet():
print(“Hello”)

greet()

Output: Hello

Function with Parameters:

def add(a, b):
print(a+b)

add(10, 20)

# a,b → Parameters

# 10,20 → Arguments

Output:

30

Return Statement:

The return statement sends a value back to the place where the function was called.

Syntax:

def function_name():
return value

Difference Between print() and return:

print() - Cannot store the result.

return - Can store and reuse the result.

Scope of Variables

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Scope determines where a variable can be accessed.

Local Variable:

Created inside a function.

def display():
x = 10
print(x)

display()

Global Variable:

Created outside a function.

x = 10

def display():
print(x)

display()

FILE HANDLING:

Introduction to File Input/Output

File handling allows us to store and retrieve data permanently.

Why File Handling?

Without file:

Program Ends
↓
Data Lost

With file:

Program Ends
↓
Data Saved

Types of Files

Text Files:

Store human-readable data.

Eg: notes.txt
students.txt
data.csv

Binary Files:

Store data in machine-readable format.

Eg: image.jpg
audio.mp3
video.mp4

Opening and Closing Files

Opening a File:

Syntax: file = open(“filename”,”mode”)

Eg: file = open(“data.txt”,”r”)

Closing a File:

Syntax: file.close()

Eg: file = open(“data.txt”,”r”)
file.close()

Reading and Writing Text Files

Writing:

file = open(“data.txt”,”w”)

file.write(“Hello Python”)

file.close()

Reading:

file = open(“data.txt”,”r”)

print(file.read())

file.close()

Read Methods

read()

Reads entire file.

file.read()

readline()

Reads one line.

file.readline()

readlines()

Reads all lines into a list.

file.readlines()

Working with Binary Files:

Binary files store data as bytes rather than text.

Examples: Images
Videos
Audio Files
PDF Files

Writing Binary Data:

file = open(“image.jpg”,”wb”)

Reading Binary Data:

file = open(“image.jpg”,”rb”)

Exception Handling in File Operations

Problem:

If file doesn’t exist:

file = open(“abc.txt”,”r”)

Output: FileNotFoundError

Solution:

try:
file = open(“abc.txt”,”r”)
print(file.read())

except FileNotFoundError:
print(“File not found”)

Output: File not found

EXCEPTION HANDLING:

Exception handling is a mechanism used to handle runtime errors without terminating the program.

Example: print(10/0)

Output: ZeroDivisionError

With Exception Handling:

try:
print(10/0)

except:
print(“Error occurred”)

Output:

Error occurred.

Exception Handling Mechanism:

Syntax:

try:
risky code

except:
error handling code

Flow:

Try Block
↓
Exception?
↓ ↓
No Yes
↓ ↓
Run Except Block

Handling Multiple Exceptions:

Different exceptions can be handled separately.

Example:

try:
num = int(input())
print(10/num)

except ValueError:
print(“Invalid Input”)

except ZeroDivisionError:
print(“Cannot divide by zero”)

Custom Exceptions:

User-defined exceptions created using classes.

Syntax: class MyException(Exception):
pass

Error Handling Strategies

1. Try-Except

try:
risky code
except:
handling code

Try-Except-Else

else runs when no exception occurs.

try:
x = 10/2
except:
print(“Error”)
else:
print(“Success”)

Try-Except-Finally

finally always executes.

try:
file = open(“data.txt”)

except:
print(“Error”)

finally:
print(“Closing file”)

FUNCTIONAL PROGRAMMING:

Functional Programming is a programming style where functions are treated as the main building blocks of a program.

Instead of repeatedly writing loops, we use functions to process data.

Benefits

• Cleaner code
• Less code
• Easier maintenance
• Better readability

map():

map() applies a function to every element of an iterable (list, tuple, etc.).

Syntax: map(function, iterable)

Example:

Without map():

nums = [1,2,3,4]

result = []

for i in nums:
result.append(i*2)

print(result)

With map():

nums = [1,2,3,4]

result = list(map(lambda x:x*2, nums))

print(result)

Output:

[2,4,6,8]

Eg: Teacher adds 5 grace marks to every student’s mark.

80 → 85
70 → 75
60 → 65

Map modifies every item.

filter():

Filter selects elements that satisfy a condition.

Syntax:

filter(function, iterable)

Example:

nums = [1,2,3,4,5,6]

result = list(filter(lambda x:x%2==0, nums))

print(result)

Output:

[2,4,6]

Eg: Selecting only students who passed.

Marks:
90
45
80
30

Result:
90
80

reduce():

Reduce combines all elements into a single value.

Syntax:

from functools import reduce

Example:

from functools import reduce

nums = [1,2,3,4]

result = reduce(lambda x,y:x+y, nums)

print(result)

Output: 10

Eg: Adding total marks of all subjects.

80 + 90 + 70 + 60 = 300

Lambda Functions:

A Lambda Function is an anonymous function (function without a name).

Syntax: lambda arguments : expression

Example: square = lambda x:x*x

print(square(5))

Output: 25

Equivalent Normal Function:

def square(x):
return x*x

Why Lambda?

Used for short operations.

Especially with:

• map()
• filter()
• reduce()

WORKING WITH FILES AND DIRECTORIES:

File Handling: File handling is used to store data permanently.

Without files:

Program Ends
↓
Data Lost

With files:

Program Ends
↓
Data Saved

Binary Files: Binary files store information as bytes.

Eg: image.jpg
video.mp4
audio.mp3
document.pdf

Reading Binary Files:

file = open(“image.jpg”,”rb”)

data = file.read()

file.close()

Writing Binary Files:

file = open(“copy.jpg”,”wb”)

file.write(data)

file.close()

Directory Manipulation:

Directory manipulation means working with folders.

Python uses the os module.

Create Folder:

import os

os.mkdir(“Projects”)

Delete Folder:

os.rmdir(“Projects”)

Rename Folder:

os.rename(“Old”,”New”)

Current Working Directory:

os.getcwd()

Real-Life Example:

Same as creating, deleting, and renaming folders in Windows.

CSV Files:

CSV stands for Comma Separated Values

Eg: Name,Age
Subashini,21
Priya,20

Reading CSV:

import csv

with open(“students.csv”,”r”) as file:
reader = csv.reader(file)

for row in reader:
print(row)

Writing CSV:

import csv

with open(“students.csv”,”w”) as file:
writer = csv.writer(file)

writer.writerow([“Name”,”Age”])

JSON Files:

JSON stands for JavaScript Object Notation

Used for data exchange between applications.

Example JSON:

{
“name”:”Subashini”,
“age”:21
}

Reading JSON:

import json

with open(“data.json”,”r”) as file:
data = json.load(file)

print(data)

Eg: When a website sends user information to a server, JSON is commonly used.

REGULAR EXPRESSIONS (REGEX)

Regex (Regular Expression) is a sequence of characters used to search, match, validate, or replace text patterns.

Python uses the re module.

import re

Why Regex?

Suppose you need to validate:

• Email addresses
• Phone numbers
• Passwords

Regex makes it easy.

Introduction to Regex:

import re

text = “Python”

result = re.search(“Py”, text)

print(result)

Output: Match Found

Pattern Matching using re Module:

search()

Finds first occurrence.

re.search(“cat”,”The cat is sleeping”)

findall()

Returns all matches.

re.findall(“cat”,”cat dog cat”)

Output:

[‘cat’,’cat’]

match()

Checks from the beginning of the string.

re.match(“Hello”,”Hello World”)

sub()

Replaces text.

re.sub(“cat”,”dog”,”cat is sleeping”)

Output:

dog is sleeping

Common Regex Patterns

Digits:

\d

Matches:

0–9

Example:

re.findall(r”\d”,”A1B2C3")

Output:

[‘1’, ‘2’, ‘3’]

Alphabets:

[a-z]

Matches lowercase letters.

Uppercase Letters:

[A-Z]

Matches uppercase letters.

Any Character

.

Matches any single character.

One or More Occurrences

+

Example:

a+

Matches:

a
aa
aaa

Beginning of String:

^

Example:

^Hello

String must start with Hello.

End of String:

$

Example:

World$

String must end with World.