The document provides an introduction to Python, highlighting its high-level, interpreted nature, versatility across applications like web development and data science, and extensive community support. It discusses Python's history, basic syntax, data types, and includes examples of operations and exercises to enhance learning. The comparison of interpreters and compilers is also covered, emphasizing the advantages and disadvantages of Python's interpreted execution model.

1. Introduction to Python
Faculty : Moushreeta Debroy
Programme : Python
Department : BCA
Semester : 1
Module : 1

2. What is Python?
• Python is a high-level, interpreted, general-purpose programming
language known for its readability and simplicity.
• Python is an easy language to learn because of its simple syntax
• Python can be used for simple tasks such as plotting or for more
complex tasks like machine learning

3. History of Python
• 1989: Python conceived by Guido van Rossum.
• 1991: Python 0.9.0 released, included features like exception handling
and functions.
• 2000: Python 2.0 introduced list comprehensions and garbage
collection.
• 2008: Python 3.0 released with improvements, including better
Unicode support.

5. Why Learn Python?
• Easy to Learn and Use: Simple syntax resembles natural language.
• Versatility: Used in web development, data science, automation, etc.
• Extensive Libraries and Frameworks: Like NumPy, pandas, matplotlib,
seaborn etc.
• Community Support: Large, active community and plenty of learning
resources.
• Example Use Cases: Data analysis with pandas, web development
with Flask.

6. IDEs for Python
• PyCharm
• VS Code
• Jupyter Notebook
• Spyder
• IDLE (built-in)

7. Python as an Interpreter, Not a Compiler
Interpreter vs Compiler:
• Interpreter: Executes code line by line, translating each line into
machine code and running it immediately.
• Compiler: Translates the entire code into machine code at once,
creating an executable file before running.

8. Python as Interpreter:
• Python is an interpreted language, meaning the Python interpreter
processes each line of code one at a time.
• This allows for immediate execution and feedback, making it great for
scripting, rapid prototyping, and debugging.

9. Advantages of Interpretation in Python:
• Ease of Debugging: Errors are reported immediately, and debugging
can be done interactively.
• Platform Independence: Python code can run on any machine with a
Python interpreter, without needing platform-specific compilation.
• Flexibility: Python supports dynamic typing and can execute code
dynamically at runtime.

10. Disadvantages of Interpretation in Python:
• Speed: Interpreted languages like Python tend to be slower than
compiled languages because they process code at runtime.
• Performance: The line-by-line execution means that interpreted
programs may have higher runtime overhead.

11. Basic Syntax and Structure
• Python uses indentation to define
code blocks.
• No need for semicolons to end
statements.
• Comments start with # and are
ignored by the interpreter.

12. Example
Comments
• Single-line comments: # This is a
comment
• Multi-line comments: '''This is a
comment''‘
First Python program:
```
print("Hello, World!")
```
.

13. • Python uses indentation to define blocks of code.
Example:
```
if 5 > 2:
print("Five is greater than two!")
```

14. Variables in Python
What are Variables?
Containers for storing data values
• No Need to declare a variable type
• Python infers the type automatically
#Declaring Variables
x = 5
name = "John“

15. Naming Variables
Rules for Naming
• Must start with a letter or underscore (_)
• Can contain letters, numbers, and underscores
• Case-sensitive (name and Name are different)
• Examples:
• Valid: age, first_name, _count
• Invalid: 2name, first-name, first name

17. Data Types
• x = 10 # int
• y = 3.14 # float
• name = "Alice" # str
• is_valid = True # bool

18. Python Data Types Overview
List
• Ordered: Elements have a specific order.
• Mutable: Can be changed (add, remove, modify elements).
• Duplicates Allowed: Lists can contain duplicate elements.
Example:
my_list = [1, 2, 3, "apple", 3]

19. Python Data Types Overview
Set
• Unordered: Elements do not have a specific order.
• Mutable: Can add, remove, or modify elements.
• No Duplicates: Sets do not allow duplicate elements.
Example:
my_set = {1, 2, 3, "apple", 3}

20. Python Data Types Overview
Tuple
• Ordered: Elements have a specific order.
• Immutable: Cannot be changed once created (no adding, removing, or
modifying elements).
• Duplicates Allowed: Tuples can contain duplicate elements.
Example:
my_tuple = (1, 2, 3, “apple”, 3)

21. Python Data Types Overview
Dictionary
• Key-Value Pairs: Each element is stored as a key-value pair.
• Mutable: Can add, remove, or change key-value pairs.
• No Duplicates: Keys must be unique, but values can be duplicated.
Example:
my_dict = {"name": "John", "age": 25, "city": "New York"}

22. Working with Strings
String Operations
• Concatenation: "Hello " + "World!“ #Output :"Hello World!"
• Repetition: "Hello" * 3 #Output:"HelloHelloHello"
String Methods
• upper(), lower(), len()
Example:
greeting = "Hello"
print(greeting.upper())
# Output: HELLO

23. Numbers in Python
Integers and Floats
• Integer: 5, -10
• Float: 3.14, -0.001
Basic Arithmetic
• Addition: 5 + 2
• Subtraction: 5 - 2
• Multiplication: 5 * 2
• Division: 5 / 2

24. Boolean Data Type
Booleans
• Represents True or False
Boolean Expressions
• Comparison operators: ==, !=, >, <

25. Converting Data Types
• int(), float(), str()
Example:
num_str = "123“
num_int = int(num_str)
print(type(num_int))
# Output: <class 'int'>
Type Conversion

26. Basic Operators
• Arithmetic Operators: +, -, *, /, // (floor division), % (modulus),
** (exponentiation).
• Assignment Operators: =, +=, -=, *=, /=
• Comparison Operators: ==, !=, >, <, >=, <=
• Logical Operators: and, or, not

27. Example:
• a= 5
• b = 2
• result = a + b # Addition
• is_greater = a > b # Comparison

28. Arithmetic Operators
Example:
a = 10
b = 3
print(a % b)
# Output: 1
print(a ** b)
# Output: 1000

29. Assignment Operators
x = 5
x += 3 # Equivalent to x = x + 3
x -= 3 # Equivalent to x = x - 3
print(x)
# Output:8

30. Comparison and Logical Operators
• Comparison Operators
x = 5
y = 10
print(x == y) # Output: False
print(x < y) # Output: True
• Logical Operators
print(True and False) # Output: False
print(True or False) # Output: True
print(not True) # Output: False

31. Exercise 1: Simple Calculator
• Write a Python program that asks the user to input two numbers and then performs the
following operations:
• Addition
• Subtraction
• Multiplication
• Division
Exercise 2: Greeting the User
• Write a Python program that:
• Takes the user's first name and last name as input.
• Greets them using their full name in a nicely formatted message.

32. Exercise 3: Even or Odd Checker
• Write a Python program that:
• Asks the user to input an integer.
• Checks whether the number is even or odd and prints the result.
Exercise 4: Word Manipulator
• Write a Python program that:
• Takes a string input from the user.
• Prints the length of the string.
• Converts the string to uppercase and prints the result.
• Repeats the string 3 times and prints the result.

33. Thank you