Introduction to Python

• Module I covers the fundamentals of Python programming.

Introduction to Python

• Python is a high-level, interpreted, general-purpose language known for simplicity and readability
• Created by Guido van Rossum and released in 1991
• Python emphasizes code readability and simplicity
• Python code is executed line by line, making debugging and development easier.
• Python is used across various domains: web development, data science, automation, AI, cybersecurity, and game development
• Python syntax resembles plain English, making it beginner-friendly and easy to learn
• Python is dynamically typed, which means variable types are determined at runtime
• Python is driven by an active open-source developer community that is continuously improving

History and Evolution of Python

• Python began development in the late 1980s at CWI in the Netherlands
• Guido van Rossum guided the development of Python
• Python 1.0 was the first official release in 1991
• Python 1.0 included features inspired by the ABC programming language, such as exception handling, modules, and functions
• Python 2.0 was released in 2000 with key features like list comprehensions and a cycle-detecting garbage collector
• Python 3.0, released in 2008, broke backward compatibility but introduced enhanced Unicode support and better memory management
• The latest versions continue to improve performance, security, and usability
• Python is utilized in AI, machine learning, automation, and scientific computing.

Reasons to Learn Python

• Python is one of the most popular programming languages due to its versatility, ease of use, and extensive support
• Python has a clean and readable syntax that makes it ideal for new programmers
• Python supports object-oriented, procedural, and functional programming styles
• Python provides powerful libraries and frameworks for various applications
• NumPy, Pandas, Scikit-learn, TensorFlow are used for Data Science & Machine Learning
• Django and Flask are used for Web Development
• Selenium, BeautifulSoup, and PyAutoGUI are used for Automation & Scripting
• Python is compatible and runs on Windows, macOS, Linux, and embedded systems
• AI researchers, cyber security professionals, data analysts, and software developers should learn Python

Installing Python

• Download the latest stable version from the official website https://www.python.org/
• Follow the installation instructions for the operating system
• Select the "Add Python to PATH" option during installation for Windows users
• After the installation, check if Python is correctly installed by running the command python --version or python3 --version in the terminal

Writing a Simple Python Program

• Python program can be written and executed using a Python interpreter, script files, or an IDE
• The example Hello World program print("Hello, World!") displays output on the screen
• Python does not use semicolons or require explicit variable declarations
• To run the program: open a text editor, save the file with a .py extension, and run with the command python hello.py or python3 hello.py
• The Python language is considered simple, powerful, and flexible, so it is for both beginners and professionals

Python Interactive Shell

• The Python Interactive Shell is environment for executing Python commands immediately
• It is a Read-Eval-Print Loop (REPL)
• Python Interactive Shell is great for testing code snippets and instant feedback
• The Interactive Shell allows for dynamic execution
• To Access the Interactive Shell:
• Open a Terminal (Linux/macOS) or Command Prompt (Windows)
• Type python (or python3 on some systems) and press Enter
• The interactive shell will start, showing a >>> prompt
• Type exit() or press Ctrl + Z (Windows) / Ctrl + D (Linux/macOS) to exit the shell

Python Script Execution

• Python programs are commonly written as scripts and saved in files with a .py extension
• To execute a script:
• Write Python code in a text editor
• Save the file with a .py extension
• Open a terminal or command prompt
• Navigate to the folder where the file is saved
• Run the script by entering in python script.py or python3 script.py

Building Blocks of Python

• Fundamental components include keywords, identifiers, operators, and literals

Keywords

• Reserved words that cannot be used as variable names. Example keywords: if, else, while, for, def, class, return, import, True, False, None

Identifiers

• Names given to variables, functions, classes, and modules
• Can contain letters (a-z, A-Z), digits (0-9), and underscores (_) only.
• Identifiers cannot start with a digit or be a keyword
• Variable names are case-sensitive (myVar and myvar are distinct)

Operators

• Symbols that perform operations in Python

Literals

• Fixed values assigned to variables
• Numeric Literals: num = 100
• String Literals: text = "Hello"
• Boolean Literals: is_active = True
• Python includes various types of literals, including numbers (int, float), strings (str), booleans (True/False), and more

Python Data Types

• Python Categories of Data Types:
• Numeric: int, float, complex
• Sequence: str, list, tuple
• Set: set, frozenset
• Mapping: dict
• Boolean: bool
• Binary: bytes, bytearray, memoryview

Values and Variables

• A value is any data stored in memory, and a variable is a named reference to a value

Understanding Variables

• Variables store reusable values
• Python allows dynamic typing (no need to specify variable type explicitly)
• The type of a variable is determined at runtime

Variable Reassignment

• Python allows changing the value of a variable
• Since Python is dynamically typed a variable can hold different types of values at different times

Variable Naming Rules

• Python has specific rules for naming variables, must follow these rules for code to be readable
• Valid Variable Naming Rules:
• Can contain letters (a-z, A-Z), digits (0-9), and underscores (_) only.
• Cannot start with a digit.
• Cannot use Python keywords as variable names.
• Variable names are case-sensitive
• Best Practices for Naming Variables
• Use descriptive names for clarity
• Avoid single-letter names unless necessary
• Avoid hyphens use snake_case (underscores between words) for variable names in Python

Expressions

• An expression is a combination of values, variables, and operators that produces a result when evaluated
• Expressions always evaluate to a single value
• Expressions includes constants, variables, and operators
• Python expressions follow the order of precedence

Arithmetic Operators

• Python operators perform mathematical operations:
• + Addition
• - Subtraction
• * Multiplication
• / Division (float)
• // Floor Division
• % Modulus (Remainder)
• ** Exponentiation

Logical and Relational Operators

• Used to perform conditional checks.

Logical Operators:

• and: Returns True if both conditions are True
• or: Returns True if at least one condition is True
• not: Reverses the logical value

Relational (Comparison) Operators:

• ==: Equal to
• !=: Not equal to
• >: Greater than
• <: Less than
• >=: Greater than or equal to
• <=: Less than or equal to

Order of Operations (PEMDAS)

• Python follows a specific order of precedence when evaluating expressions
• PEMDAS - Parentheses, Exponentiation, Multiplication, Division, Addition, Subtraction
• Takeaways: Parentheses change the order, Exponentiation, Multiplication, and division happen before addition and subtraction

Control Codes within Strings

• Escape sequences format and manipulate strings start with a backslash ()
• \n Newline (moves to the next line)
• \t Tab
• \\ Backslash itself
• \' Single quote (')
• \" Double quote (")
• \r Carriage return (moves cursor to the beginning of the current line)
• \b Backspace (removes one character) help in formatting strings and working with file paths

Comments in Python

• Comments are ignored by the Python interpreter, they provide documentation
• Single-line: Begin with #
• Multi-line: Enclosed within """ """ or ''' '''

User Input and Output

• Provide built-in functions for interacting with users
• input() reads input as a string by default and it can convert to int() or float()
• print() displays text or variables on the screen
• Can create interactive Python programs

Errors in Python

• Occur when Python fails to execute a program Types:
• Syntax Errors
  • The code violates Python's syntax rules.
  • Detected before execution.
• Run-time Errors (Exceptions)
  • Happen while the program is running
  • Occur when dividing by zero
  • Accesses undefined variables
  • Incorrect data types. Common Run-time Errors:
• ZeroDivisionError: Dividing by zero (x / 0)
• NameError: Using an undefined variable
• TypeError: Performing operations on incompatible types ("5" + 3)
• IndexError: Accessing an index that doesn't exist (list[10])
• Logic Errors
  • Incorrect results occur due to faulty logic.
  • No error message is shown.

Control Structures

• Control structures determine the flow of execution Types of Control Structures
• Conditional Statements
• Used for decision-making and executes different code blocks based on conditions.
• Examples: if, if-else, if-elif-else.
• Loops
  • Executes a block of code multiple times.
  • Examples: for, while loops.
• Jump Statements
• Alters the loop flow.
• Examples: break, continue, pass.
• Helps in writing logical and efficient programs
• Reduces redundancy
• Enhances code readability and organization

Conditional Expressions

• Boolean expressions evaluating to True or False
• Used in decision-making statements.
• Relational Operators in Conditional Expressions:
• ==: Equal to.
• !=: Not equal to.
• >: Greater than.
• <: Less than.
• >=: Greater than or equal to.
• <=: Less than or equal to.

Simple IF Statement

• Executes a block of code when the condition is True
• The code is skipped if false

IF...ELSE Statement

• Executes one code block if the condition is True and another block if it is False
• Used when needing to handle two outcomes based on a condition

Compound Boolean Expressions

• Combines multiple conditions using logical operators

Logical Operators:

• and: The code is considered true if expressions are true
• or: The code is True if True if one conditional is valid
• not: The code is considered false for True and False for True values

The pass Statement

• Acts as a placeholder
• A statement is syntactically required, but no action is needed.
• It helps in writing incomplete code avoiding syntax errors

Nested Conditionals

• An if statement inside another if statement used for multiple levels of decision-making
• Enhances code specificity but can lead to deep nesting, use elif or logical operators to deal with nesting

Multi-way Decision Statements (if-elif-else)

• Provides multiple conditions to evaluate sequentially
• Grading systems and menu driven programs use this

Iteration Statements (Loops)

• Types of Loops in Python:
• while loop: Repeats as long as a condition holds True
• for loop: Iterates over elements in a sequence (list, tuple, range)
• Important Note: The condition is checked before each iteration. If the condition never turns False, it results in an infinite loop

While Loop

• Repeats a block of code as long as a condition remains True

For Loop

• Iterates over elements in a sequence

Nested Loops

• A loop inside another loop
• Time complexity increases exponentially
• Used when working with multi-dimensional data

Break and Continue Statements

• Jump statements allow for better loop control

Break Statement:

• Exits the loop completely when encountered.
• Used to stop execution when the conditions are met.

Continue Statement:

• Skips the current iteration and moves to the next
• This avoids running certain functions
• Used when we want to avoid executing iterations.

While/else and for/else Statements

• In Python, loops can have an else block that runs only if the loop wasn't terminated using break.
• The else runs only if the for loop completes normally.
• If break is used in the loop, else is used and the loop does not execute