📘 Python Revision Tour – II

2️⃣ Lists in Python

What is a List?

A List is a collection of elements stored in ordered form.

Lists are:

✔ Ordered
✔ Mutable (can be changed)
✔ Allow duplicate values

Example:

marks = [85, 90, 78, 92]

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Accessing List Elements

Each element has an index number.

Index	Value
0	85
1	90
2	78
3	92

Example:

print(marks[0])

Output

85

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Negative Indexing

Python allows accessing elements from the end.

Index	Value
-1	92
-2	78
-3	90

Example

print(marks[-1])

Output

92

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List Operations

1. Adding Elements

Using append()

marks.append(95)

Using insert()

marks.insert(1,88)

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2. Removing Elements

marks.remove(78)

Remove last element

marks.pop()

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3. Updating Elements

marks[2] = 80

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3️⃣ List Functions

Function	Purpose
len()	Number of elements
max()	Largest value
min()	Smallest value
sum()	Total of list

Example:

numbers = [10,20,30]

print(len(numbers))

print(max(numbers))

print(sum(numbers))

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4️⃣ Tuples

What is a Tuple?

A Tuple is a collection similar to list but cannot be modified.

It is immutable.

Example:

t = (10,20,30)

Important points:

✔ Ordered
✔ Allows duplicates
✔ Immutable

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Accessing Tuple Elements

t = (5,10,15)

print(t[1])

Output

10

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Tuple Functions

Function	Purpose
len()	number of elements
max()	maximum value
min()	minimum value

Example

t=(5,7,9)

print(len(t))

print(max(t))

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5️⃣ Dictionaries

Dictionaries

1. Introduction to Dictionary

A Dictionary in Python is a collection of key–value pairs.

Each element has:

key : value

Example:

student = {

    "name": "Rahul",

    "age": 17,

    "marks": 88

}

Here:

Key	Value
name	Rahul
age	17
marks	88

Important Points

✔ Dictionary is mutable (can be changed)
✔ Keys must be unique
✔ Values can be duplicate
✔ Keys must be immutable (string, number, tuple)

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2. Creating Dictionaries

Method 1: Using Curly Braces

emp = {

    "empid":101,

    "name":"Amit",

    "salary":45000

}

Method 2: Using dict()

student = dict(name="Riya", age=16, marks=90)

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3. Accessing Dictionary Elements

Use key name.

print(student["name"])

Output

Riya

Another method:

print(student.get("marks"))

Difference:

Method	Behaviour
[]	Error if key not found
get()	Returns None

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4. Adding Elements to Dictionary

student["city"] = "Mumbai"

Dictionary becomes:

{

'name':'Riya',

'age':16,

'marks':90,

'city':'Mumbai'

}

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5. Updating Dictionary Values

student["marks"] = 95

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6. Deleting Elements

Using del

del student["age"]

Using pop()

student.pop("city")

Remove last item

student.popitem()

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7. Dictionary Functions

len()

Returns number of items.

len(student)

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keys()

Returns all keys.

student.keys()

Output

dict_keys(['name','age','marks'])

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values()

Returns values.

student.values()

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items()

Returns both keys and values.

student.items()

Output

('name','Riya')

('age',16)

('marks',90)

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8. Traversing a Dictionary

Using for loop

student = {"name":"Riya","age":16,"marks":90}

for i in student:

    print(i, student[i])

Output

name Riya

age 16

marks 90

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9. Nested Dictionary

Dictionary inside another dictionary.

Example:

students = {

    "101":{"name":"Amit","marks":85},

    "102":{"name":"Riya","marks":92}

}

Accessing value:

print(students["101"]["name"])

Output

Amit

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10. Applications of Dictionary

Used in:

• Phone directory

• Student database

• Word meaning dictionary

• Login systems

Example Phone Directory

phone = {

"Amit":9876543210,

"Riya":9876541234

}

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6️⃣ Strings in Python

A String is a sequence of characters.

Example:

name = "Python"

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String Operations

Concatenation

a="Hello"

b="World"

print(a+b)

Output

HelloWorld

---

Repetition

print("Hi"*3)

Output

HiHiHi

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String Functions

Function	Purpose
len()	length of string
upper()	convert to uppercase
lower()	convert to lowercase
find()	search substring

Example:

name="Python"

print(len(name))

print(name.upper())

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No 7️⃣ Python Libraries

A library is a collection of pre-written functions.

Example libraries:

Library	Use
math	mathematical operations
random	random numbers
statistics	statistical calculations

---

Example: math Library

import math

print(math.sqrt(25))

Output

5.0

---

Example: random Library

import random

print(random.randint(1,10))

Output

Random number between 1 and 10

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8️⃣ File Handling (Introduction)

File handling allows Python programs to store data permanently.

Example:

file = open("data.txt","w")

file.write("Hello Python")

file.close()

Modes used:

Mode	Meaning
r	read
w	write
a	append

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9️⃣ Sample Programs for Students

Program 1: Find Maximum Number in List

numbers = [10,45,23,67,12]

print("Maximum =",max(numbers))

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Program 2: Count Characters in String

text = input("Enter a string:")

print("Length =",len(text))

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Program 3: Dictionary Example

student = {"name":"Riya","marks":90}

print(student["marks"])

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🔹 1. Functions in Python (Advanced)

📌 Types of Functions

1. Built-in functions → len(), sum()

2. User-defined functions

3. Recursive functions

4. Anonymous (Lambda) functions

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📌 Function Arguments

➤ 1. Required Arguments

def add(a, b):

    return a + b

➤ 2. Default Arguments

def greet(name="Guest"):

    print("Hello", name)

➤ 3. Keyword Arguments

add(b=5, a=3)

➤ 4. Variable Length Arguments

def total(*args):

    return sum(args)

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📌 Return Statement

• Returns value to caller

• Function ends after return

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📌 Recursive Function

    A function calling itself:

def factorial(n):

    if n == 1:

        return 1

    return n * factorial(n-1)

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📌 Lambda Function

• Small anonymous function

    square = lambda x: x*x

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🔹 2. File Handling in Python

📌 Types of Files

• Text file (.txt)

• Binary file (.dat, .bin)

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📌 File Modes

Mode	Description
r	Read
w	Write (overwrite)
a	Append
rb	Read binary
wb	Write binary

---

📌 Opening & Closing Files

    f = open("file.txt", "r")

    f.close()

---

📌 Reading File

f.read()

f.readline()

f.readlines()

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📌 Writing File

    f.write("Hello")

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📌 Append Data

f = open("file.txt", "a")

f.write("New Data")

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📌 Using with Statement (Best Practice)

with open("file.txt", "r") as f:

    data = f.read()

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🔹 3. Working with Binary Files

📌 Using Pickle Module

• Used to store Python objects in binary format

import pickle

f = open("data.dat", "wb")

pickle.dump([1,2,3], f)

f.close()

📌 Reading Binary File

f = open("data.dat", "rb")

data = pickle.load(f)

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🔹 4. Exception Handling

📌 What is Exception?

      Runtime error that disrupts program flow

---

📌 try-except Block

try:

    x = int(input())

except ValueError:

    print("Invalid input")

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📌 Multiple Exceptions

try:

    pass

except (ValueError, ZeroDivisionError):

    pass

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📌 finally Block

• Always executes

finally:

    print("Done")

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📌 else Block

• Executes if no exception occurs

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🔹 5. Modules in Python

📌 What is Module?

    A file containing Python code

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📌 Importing Modules

import math

math.sqrt(25)

from math import sqrt

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📌 Important Modules

• math

• random

• datetime

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📌 Creating User Module

# mymodule.py

def add(a,b):

    return a+b

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🔹 6. List Manipulation (Advanced)

📌 List Comprehension

    squares = [x*x for x in range(5)]

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📌 Nested Lists

    matrix = [[1,2],[3,4]]

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📌 Common Functions

• len(), max(), min(), sum()

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🔹 7. String Manipulation (Advanced)

📌 Important Methods

s.find("a")

s.replace("a","b")

s.split()

s.join()

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📌 String Formatting

name = "Bhav"

print(f"Hello {name}")

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🔹 8. Python Libraries (Intro)

• Library = collection of modules

        Examples:

• matplotlib → graphs

• pandas → data analysis

• tkinter → GUI

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🔹 9. CSV File Handling

📌 Writing CSV

import csv

f = open("data.csv", "w", newline='')

writer = csv.writer(f)

writer.writerow(["Name", "Age"])

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📌 Reading CSV

reader = csv.reader(f)

for row in reader:

    print(row)

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🔹 10. MySQL Connectivity (Important for CBSE)

📌 Steps:

1. Install connector

2. Connect database

3. Execute query

import mysql.connector

con = mysql.connector.connect(

    host="localhost",

    user="root",

    password="1234",

    database="school"

)

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📌 Execute Query

cursor = con.cursor()

cursor.execute("SELECT * FROM student")

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📌 Fetch Data

    data = cursor.fetchall()

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📌 Commit Changes

    con.commit()

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🔹 11. Important Differences

Concept	Difference
List vs Tuple	Mutable vs Immutable
Text vs Binary File	Readable vs Non-readable
Error vs Exception	Compile vs Runtime

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🧠 Important Viva Questions

1. What is recursion?

2. Difference between read() and readline()?

3. What is pickle module?

4. What is exception handling?

5. Difference between append and write?

6. What is CSV file?

7. What is module?

8. What is MySQL connector?

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📌 Conclusion

Python Revision Tour – II strengthens:

• File handling

• Database connectivity

• Error handling

• Advanced programming concepts

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