🐍 Python Workshop

Comprehensive Python Workshop: Mastering Fundamentals and Advanced Techniques

📖 Table of Contents

0. Introduction to Python
   A beginner-friendly introduction to Python, its features, and basic syntax.
1. Data Structures
   Explore essential data structures like int, float, list, tuple, dictionary, and set.
2. Index and Slice
   Learn how to access and manipulate elements of sequences using indexing and slicing.
3. Operators and Operands
   Study various operators (arithmetic, comparison, logical, etc.) and how they work with operands.
4. Type Conversions
   Understand how to convert data types in Python with explicit and implicit conversions.
5. Conditional Statements
   Learn about if-elif-else and match-case statements for controlling the flow of your programs.
6. Loops
   Master loops (for, while) to iterate over sequences and perform repeated tasks.
7. Functions
   Understand how to define and use functions, including parameters and return values.
8. Built-In Functions
   Explore Python's powerful built-in functions and how to leverage them in your programs.
9. Namespaces and Scopes
   Learn about namespaces and scope resolution to avoid name conflicts in your code.
10. Anonymous Functions (Lambda)
    Discover the usage of lambda expressions for creating small, anonymous functions.
11. Pack and Unpack Data
    Learn how to pack multiple values into a variable and unpack them in Python.
12. Type Hints and Docstrings
    Understand how to improve code readability with type hints and document your functions with docstrings.
13. Dependencies
    Learn how to manage and install dependencies using pip and requirements.txt and use them in your code.
14. Comprehensions
    Master list, set, dictionary, and generator comprehensions for concise and readable code.
15. Introduction to Object-Oriented Programming (OOP)
    Get introduced to the basic concepts of object-oriented programming in Python.
16. Closures and Decorators
    Learn about closures and how to use decorators for enhancing functions.
17. Object-Oriented Programming Concepts
    Explore core OOP concepts such as encapsulation, inheritance, polymorphism, and abstraction.
18. Context Managers
    Learn to manage resources efficiently using with statements and defining custom context managers.
19. Special Methods
    Discover Python's dunder (double underscore) methods for creating custom behavior in your classes.
20. Errors and Exceptions
    Learn about handling errors and exceptions to make your code more robust.
21. Meta Classes
    Dive into metaclasses to understand how classes in Python are created and customized.

📋 Prerequisites

• Basic Computer Skills
  • Familiarity with using a computer, web browsers, and file management.
• Python Environment Setup
  • Ability to set up a Python development environment, including:
    • Installation of Python (Anaconda or standalone).
    • Familiarity with using Integrated Development Environments (IDEs) like Jupyter Notebook, PyCharm, or Visual Studio Code.

⚙️ Setup

This project was developed using Python v3.12.3. If you encounter issues running the specified version of dependencies, consider using this specific Python version.

📦 Installing Dependencies

You can install all dependencies listed in requirements.txt using pip.

pip install -r requirements.txt

🛠️ Usage Instructions

• Open the root folder with VS Code
  • Windows/Linux: Ctrl + K followed by Ctrl + O
  • macOS: Cmd + K followed by Cmd + O
• Open .ipynb files using Jupyter extension integrated with VS Code
• Allow VS Code to install any recommended dependencies for working with Jupyter Notebooks.
• Note: Jupyter is integrated with both VS Code & Google Colab

🔗 Useful Links

• Python:
  • Official Website:
    • The main website for Python, offering downloads, news, and community resources.
    • Official site: python.org
  • Documentation
    • Comprehensive guide and reference for all functionalities and features of the Python programming language.
    • Doc: docs.python.org
  • Source Code
    • Over 2500 contributors are currently working on Python.
    • Link: github.com/python/cpython
• Looking Ahead:
  • NumPy
    • A fundamental package for scientific computing in Python, providing support for arrays, matrices, and a large collection of mathematical functions.
    • Official site: numpy.org
    • My NumPy Workshop: github.com/mr-pylin/numpy-workshop
  • Pandas
    • A powerful, open-source data analysis and manipulation library built on top of NumPy for Python
    • Official site: pandas.pydata.org
    • My Pandas Workshop: Coming Soon
  • MatPlotLib
    • A comprehensive library for creating static, animated, and interactive visualizations in Python
    • Official site: matplotlib.org
    • My MatPlotLib Workshop: Coming Soon
  • PyTorch
    • An open-source machine learning library for Python developed by Meta AI, used for applications such as deep learning and neural networks.
    • Official site: pytorch.org
    • My PyTorch Workshop: github.com/mr-pylin/pytorch-workshop

🔍 Find Me

Any mistakes, suggestions, or contributions? Feel free to reach out to me at:

• 📍linktr.ee/mr_pylin

I look forward to connecting with you! 🏃‍♂️

📄 License

This repository is licensed under the MIT License, except for the contents in the ./assets/images/SVGs/ path, which are licensed under the CC BY-ND 4.0.