Unit1

1. Introduction to Python Programming

  • Course Code: 10211CS213

2. Course Objectives

  • Understand the basic program structure and elements of Python Language.

  • Learn about file manipulation, string manipulation, and regular expressions.

  • Grasp concepts of exception handling and multithreading in Python.

  • Use Python modules for data analysis, gaming, and UI design.

3. Why Programming?

  • Turns ideas (games, applications) into executable instructions for the computer.

  • Programming enables the realization of software-related concepts.

4. Why Python is Popular?

  • User-friendly applications

  • Free libraries and community support

5. Advantages of Python

  • Easy to use and learn.

  • Flexibility in various applications.

  • Efficient, fast, and reliable.

  • Widely applicable in web development, data analysis, machine learning, AI, automation, and scientific computing.

  • Robust libraries available for numerous projects.

6. Code Comparisons

  • C Example:

    #include <stdio.h>
int main() {
    printf("Hello, World!");
    return 0;
}

  • Python Example:

    print("Hello, World!")

7. What is Python?

  • Python is a general-purpose, high-level, interpreted language known for its easy syntax and dynamic semantics.

  • Created by Guido Van Rossum in 1989.

8. Semantic Rules in Python

  • Static Semantics: Rules checked before execution.

  • Dynamic Semantics: Rules checked during execution.

9. Features of Python

  • Embeddable & open-source

  • Object-oriented programming (OOP)

  • Extensible libraries

  • Simplicity and portability

10. Python Basics

10.1 Variables

  • Variables are containers for storing data. No specific command for declaration in Python.

  • Example:

    x = 5
y = "John"
print(x)
print(y)

10.2 Data Type Flexibility

  • Variables can change type after assignment.

  • Example:

    x = 4  # int
x = "Rajesh"  # now str
print(x)

10.3 Type Function

  • Use type() to check the data type of a variable.

    x = 5
y = "John"
print(type(x))
print(type(y))

10.4 Changing Data Types

  • Example to change from int to float and vice versa:

    num1 = 10
num1_float = float(num1)
print(type(num1_float))
num2 = 2.5
num2_int = int(num2)
print(type(num2_int))

10.5 Strings

  • Strings can be declared using single or double quotes.

  • Case-sensitive variables:

    a = 4
A = "Sally"  # A does not overwrite a

10.6 Naming Variables

  • Criteria:

    • Must start with a letter or underscore

    • Cannot start with a number

    • Can contain alpha-numeric characters and underscores

    • Case-sensitive (age, Age, AGE are different variables)

11. Data Types in Python

  • Integer: Whole numbers, no limit on size.Example: x = 5

  • Float: Real numbers, can be scientific notation.Example: x = 5.5

  • Complex Numbers: Two values, real and imaginary parts.Example: x = 2 + 3j

11.1 Dictionary

  • Stores data in key:value pairs, ordered and changeable without duplicates.

    dict1 = {"brand": "maruthi", "model": "Alto", "year": 1964}
print(dict1)

11.2 Boolean

  • Represents one of two values: True or False.

    print(10 > 9)
print(10 == 9)
print(10 < 9)

11.3 Sets

  • Unordered, unchangeable collections without duplicate values.

    myset = {"apple", "banana", "cherry"}
print(myset)

11.4 Sequence Data Types

  • Containers: List (mutable), Tuple (immutable), String (immutable).

12. Python Lists

12.1 Creation

  • Ordered and changeable; allow duplicates.

    thislist = ["apple", "banana", "cherry"]
print(thislist)

12.2 Methods of Lists

  • Add an Item: append().

  • Remove an Item: remove().

  • Remove by Index: pop().

13. Tuples

  • Immutable, ordered collection.

thistuple = ("apple", "banana", "cherry")
print(thistuple)

14. Strings

  • Immutable sequence of characters.

  • Accessing characters via indexing, supports negative index for reverse.

15. Python Operators

  • Types: Arithmetic, Assignment, Comparison, Logical, Identity, Membership, Bitwise.

16. Control Statements

  • Used to control code execution flow: Conditional, Looping, and Branching statements.

16.1 Conditional Statements

  • If Statement: Executes block if condition is true.

  • If-else Statement: Executes one of two blocks based on condition.

  • Nested if Statements: Complex conditions.

16.2 Looping Statements

  • While Loop: Repeats as long as the condition is true.

  • For Loop: Iterates over a sequence.

17. Functions in Python

  • Enclosed block of statements for specific tasks, enhancing readability and reusability.

17.1 Defining a Function

  • Use def keyword.

  • Example to create and call a function.

17.2 Function Arguments

  • Accepts arguments and can return values.

17.3 Lambda Functions

  • Anonymous functions for quick operations.

18. Python Modules

  • Files containing code for reuse.

18.1 Importing

  • Use import statement to include a module in your code.

18.2 Packages

  • Collection of modules, including initialization via __init__.py.

19. Object-Oriented Programming

19.1 Classes and Objects

  • Classes are blueprints for creating objects.

  • Instance methods and attributes for each object.

20. Iterators and Generators

  • Iterator: Object for iterating over values.

  • Generator: Function that returns an iterator using the yield keyword.