Python is widely used in various fields, including web development, data science, artificial intelligence, and automation. Its simplicity and versatility have made it one of the most popular programming languages globally. Large organizations like Google, NASA, and Facebook use Python for various applications.
| File | Description |
|---|---|
Python Ⅰ.py |
Covers Chapter 1 (Introduction to Python) through Chapter 16 (Collections), including Exercises 1–7. |
Python Ⅱ.py |
Covers Chapter 17 (2D Collections) through Chapter 25 (Match-Case Statement), including Exercises 8–13. |
Python Ⅲ.ipynb |
Covers Chapter 26 (Modules) through Chapter 28 (if __name__ == '__main__'), including Exercises 14–17. |
Python Ⅳ.py |
Covers Chapter 29 (Objects) through Chapter 41 (Exceptions). |
Python Ⅴ.py |
Covers Chapter 42 (Python File Detection) through Chapter 56 (PyQt5 CSS), including Exercise 18 (Python Alarm Clock). |
Python Ⅵ.ipynb |
Contains Exercise 19 (Python PyQt5 Digital Clock) and Exercise 20 (Python PyQt5 Stopwatch). |
Python Ⅶ.py |
A larger project: the Python Weather App. |
Foundations: Variables, data types, string formatting, and type casting.
Control Flow: if/elif/else statements, for loops, while loops, and break/continue.
Functions: Defining functions, *args and **kwargs, lambda functions, and scope.
Data Structures: Lists, tuples, sets, dictionaries, and their key methods.
Object-Oriented Programming (OOP): Classes, objects, inheritance, and polymorphism.
Practical Skills: File I/O, error handling (try/except), and working with modules.
Advanced Concepts: List comprehensions, generators, and decorators.
Python is dynamically typed and garbage-collected, making it flexible and easy to use. It is often described as a "batteries included" language due to its comprehensive standard library. This extensive library supports various tasks, from web development to data analysis and scientific computing.
Python's syntax is designed to be readable and straightforward, using significant indentation to define code blocks instead of curly braces or keywords. This feature makes Python code visually uncluttered and easy to understand.
To run these projects, you can simply use the Python code from each folder and run it on any IDE you prefer.
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Clone the repository to your local machine:
git clone https://github.com/your-username/your-repository-name.git
-
Navigate to any Python or Jupyter Notebook files, for example:
cd your-repository-name/Python Ⅵ.ipynb -
Run the script from your terminal or IDE:
python your_file_name.py
Feel free to fork this repository and submit your own Python projects or improvements via pull requests!
This project is licensed under the MIT License - see the LICENSE file for details.