Python Tutorial by AI

中文版

Welcome to this interactive Python tutorial! This course is designed to take you from a complete beginner to a proficient Python developer, equipped with modern tools and best practices.

How It Works

The tutorial is divided into 52 lessons, each covering a specific topic. Each lesson has its own directory containing two files:

• instructions.md: A Markdown file with the lesson's content, explanations, and examples.
• exercise.py (or main.py for FastAPI): A Python file with practice exercises for you to complete.

Getting Started

1. Navigate to a lesson directory: Start with lesson_01.

2. Read the instructions: Open the instructions.md file to learn about the topic.

3. Complete the exercise: Open the exercise file and write the code to complete the exercises.

4. Run your code: To run your exercise file and see the output, use the following command in your terminal, replacing lesson_01/exercise.py with the correct file path:

   python lesson_01/exercise.py

Beginner Lessons

• Lesson 01: Intro to Python — Install Python, set up your environment, and write your first "Hello, World!" program.
• Lesson 02: Variables & Data Types — Learn about integers, floats, strings, and booleans.
• Lesson 03: Basic Operators — Arithmetic, comparison, and logical operators.
• Lesson 04: User Input & Type Casting — Read input from users and convert between data types.
• Lesson 05: Conditional Statements — Control flow with if, elif, and else.
• Lesson 06: Lists — Create lists, access elements by index, and use slicing.
• Lesson 07: List Methods — Mutate and manipulate lists with built-in methods.
• Lesson 08: For Loops — Iterate over lists and ranges with for loops.
• Lesson 09: While Loops — Repeat code while a condition is true.
• Lesson 10: Dictionaries — Store and retrieve key-value pairs.
• Lesson 11: Tuples & Sets — Immutable sequences and unordered unique collections.
• Lesson 12: Defining & Calling Functions — Reuse code by writing your own functions.
• Lesson 13: Function Arguments & Return Values — Positional, keyword, and default arguments; returning data.
• Lesson 14: Variable Scope — Understand local vs. global scope and the global keyword.
• Lesson 15: Modules & Importing — Use the standard library and import your own modules.
• Lesson 16: File I/O Reading — Open and read text files with Python.
• Lesson 17: File I/O Writing — Write and append data to files.
• Lesson 18: Error Handling — Catch and handle exceptions with try, except, and finally.
• Lesson 19: OOP Intro — Introduction to classes, objects, attributes, and methods.
• Lesson 20: Next Steps — Review your progress and explore project ideas to keep learning.

Advanced Lessons

• Lesson 21: OOP Inheritance — Extend classes and reuse code through inheritance.
• Lesson 22: OOP Polymorphism — Override methods and use polymorphism for flexible code.
• Lesson 23: OOP Encapsulation — Control access with public, protected, and private attributes.
• Lesson 24: OOP Dunder Methods — Customise objects with magic methods like __str__ and __len__.
• Lesson 25: Static and Class Methods — Use @staticmethod and @classmethod decorators.
• Lesson 26: List Comprehensions — Write concise list transformations in a single expression.
• Lesson 27: Dict and Set Comprehensions — Apply the comprehension pattern to dictionaries and sets.
• Lesson 28: Lambda Functions — Create small anonymous functions with lambda.
• Lesson 29: Map Filter Reduce — Functional-style data processing with map(), filter(), and reduce().
• Lesson 30: Generators — Produce values lazily with generator functions and the yield keyword.
• Lesson 31: Decorators — Wrap and enhance functions using decorators.
• Lesson 32: Collections Module — Powerful container types: Counter, defaultdict, deque, and more.
• Lesson 33: Dates and Times — Parse, format, and calculate dates and times with the datetime module.
• Lesson 34: JSON Data — Serialize and deserialize JSON data with the json module.
• Lesson 35: OS and Sys Modules — Navigate the filesystem and interact with the OS using os and sys.
• Lesson 36: Multithreading — Run tasks concurrently with the threading module.
• Lesson 37: Multiprocessing — Achieve true parallelism with the multiprocessing module.
• Lesson 38: Asyncio Intro — Understand the event loop and the basics of asyncio.
• Lesson 39: Async Await — Write clean asynchronous I/O code with async and await.
• Lesson 40: Advanced Project — Build a capstone project that combines everything you've learned.

Essential Python Packages

• Lesson 41: Requests Module — requests - Make HTTP requests to APIs and websites.
• Lesson 42: BeautifulSoup4 — BeautifulSoup4 - Parse HTML and scrape web pages.
• Lesson 43: Pandas — pandas - Powerful data analysis and manipulation.
• Lesson 44: Matplotlib — matplotlib - Create charts and data visualisations.
• Lesson 45: Seaborn — seaborn - High-level statistical data visualisation.
• Lesson 46: FastAPI — FastAPI - Build high-performance web APIs with automatic docs.

Professional Development Practices

• Lesson 47: Git and GitHub — Track changes and collaborate using Git & GitHub.
• Lesson 48: Pytest — Write and run automated tests with pytest.
• Lesson 49: Ruff — Keep code clean with fast formatting and linting via ruff.
• Lesson 50: UV Dependency Management — Manage virtual environments and dependencies with uv.
• Lesson 51: Databases — Store and query data with SQLAlchemy and SQLite.
• Lesson 52: Config Management — Manage secrets and settings safely using .env files.

Happy learning!