Python Programming for Beginners

What you'll Learn

1. Introduction to Python

• What is Python?: Overview of Python as a high-level, interpreted language known for its readability and simplicity.
• Setting up Python: Install Python on your computer and set up the development environment (IDLE, VS Code, PyCharm, Jupyter Notebooks).
• Writing Your First Python Program: Creating a basic “Hello, World!” program.

2. Python Syntax and Structure

• Basic Syntax: Understanding Python’s syntax rules, indentation, and case sensitivity.
• Comments: Using comments (#) to annotate code.
• Python as an Interpreted Language: Running Python interactively and understanding its line-by-line execution.

3. Variables and Data Types

• Variables: Declaring variables and understanding dynamic typing.
• Data Types: Basic data types such as int, float, str, bool, and None.
• Type Casting: Converting between data types using functions like int(), float(), str(), and bool().

4. Operators and Expressions

• Arithmetic Operators: Using +, -, *, /, // (floor division), % (modulus), and ** (exponentiation).
• Comparison Operators: ==, !=, >, <, >=, <=.
• Logical Operators: and, or, not.
• Assignment Operators: =, +=, -=, *=, /=, etc.
• Bitwise Operators: Working with binary numbers using &, |, ^, ~, <<, and >>.

5. Control Flow Statements

• If-Else Statements: Making decisions using if, elif, and else.
• Ternary Operator: Simplifying conditional expressions (x if condition else y).
• Loops:
  • For Loop: Iterating over sequences (lists, strings, ranges).
  • While Loop: Repeating code while a condition is proper.
• Break and Continue: Controlling loop flow with break and continue.

6. Functions in Python

• Defining Functions: Using the def keyword to define reusable blocks of code.
• Function Parameters and Arguments: Passing data to functions using parameters.
• Return Statement: Returning values from functions using return.
• Default and Keyword Arguments: Using default parameter values and calling functions with named arguments.
• Lambda Functions: Writing small anonymous functions using lambda.

7. Lists, Tuples, and Dictionaries

• Lists: Creating, accessing, and modifying lists (mutable).
  • List methods like append(), remove(), sort(), reverse(), and slicing ([start:end]).
• Tuples: Creating and using tuples (immutable).
• Dictionaries: Storing key-value pairs in dictionaries, adding and removing key-value pairs.
  • Dictionary methods like get(), keys(), values(), and items().

8. Sets and Strings

• Sets: Creating and using sets (unordered, no duplicates) and set operations like union, intersection, and difference.
• String Operations: Working with strings (str) and string methods (upper(), lower(), strip(), replace(), split()).
• String Formatting: Using f-strings and format() to format strings.

9. File Handling

• Reading from a File: Opening and reading text files using open(), read(), readlines().
• Writing to a File: Writing data to files using write() and writelines().
• File Modes: Understanding file modes: r (read), w (write), a (append).
• Using Context Manager: Safely manage file resources. with open().

10. Exception Handling

• Try-Except Blocks: Handling errors using try, except, finally.
• Raising Exceptions: Raising custom exceptions using raise.
• Custom Exceptions: Defining and using your exception classes.

11. Modules and Packages

• Modules: Importing and using external modules (e.g., math, random, datetime).
• Creating Modules: Writing reusable code in your modules.
• Packages: Organizing modules into packages using directories and __init__.py.

12. Object-Oriented Programming (OOP) in Python

• Classes and Objects: Defining classes and creating objects.
• Attributes and Methods: Working with instance variables (attributes) and defining methods (functions inside classes).
• Constructor (__init__()): Using the constructor to initialize objects.
• Inheritance: Creating new classes from existing classes using inheritance (class ChildClass(ParentClass)).
• Polymorphism: Using method overriding and inheritance to achieve polymorphism.
• Encapsulation: Restricting access to data using private (_ and __) attributes.
• Class vs Instance Variables: Understanding class variables vs instance variables.
• Static Methods and Class Methods: Defining static methods (@staticmethod) and class methods (@classmethod).

13. Python Libraries and Standard Modules

• Math Module: Using mathematical functions from the math module (sqrt(), sin(), cos(), etc.).
• Random Module: Generating random numbers and selecting random choices.
• Datetime Module: Working with dates and times.
• OS Module: Interacting with the operating system, reading file directories, and executing shell commands.

14. Working with External Libraries

• Installing Libraries: Using pip to install external packages (e.g., pip install requests, pip install numpy).
• Popular Python Libraries:
  • NumPy: For numerical computations.
  • Pandas: For data manipulation and analysis.
  • Matplotlib/Seaborn: For data visualization.
  • Requests: For making HTTP requests.

15. Python Regular Expressions

• Introduction to Regular Expressions: Using the re module for pattern matching.
• Common Regex Patterns: Matching characters, digits, whitespace, repetitions, and groups.
• Search and Replace: Using search(), match(), and sub() to find and replace text.

16. Working with APIs (JSON)

• Introduction to APIs: Understanding how to interact with web APIs using Python.
• Sending HTTP Requests: Using the requests library to make GET and POST requests.
• Handling JSON Data: Parsing JSON responses with json.loads() and generating JSON using json.dumps().

17. Python Debugging and Testing

• Debugging Techniques: Using print() statements for debugging and using the built-in debugger (pdb).
• Unit Testing: Writing tests using the unittest framework.
• Assertions: Using assert statements for debugging and testing.

18. Python Virtual Environments

• Introduction to Virtual Environments: Creating isolated environments using venv.
• Managing Dependencies: Installing packages in a virtual environment and generating requirements.txt.

19. Web Scraping with Python

• Introduction to Web Scraping: Understanding the basics of scraping web pages.
• Using BeautifulSoup: Parsing HTML documents and extracting data.
• Using requests and lxml: Making requests and parsing HTML/XML.

20. Project Ideas for Beginners:

To apply your knowledge, here are some beginner-friendly Python projects:

1. Simple Calculator:
   • Create a program that can perform basic arithmetic operations like addition, subtraction, multiplication, and division.
2. To-Do List:
   • A command-line tool to manage your tasks (add, remove, and mark tasks as completed).
3. Number Guessing Game:
   • Build a simple number-guessing game where the user tries to guess a random number within a range.
4. Weather App:
   • Use an API to fetch and display the current weather for a given city.
5. Password Generator:
   • Create a program that generates random, secure passwords based on user input (length, character types).
6. Basic Web Scraper:
   • Scrape data from a website, such as retrieving headlines from a news site.