Absolutely! Here's a longer, more detailed commit message that explains the changes thoroughly while maintaining a polite and constructive tone:
refactor: Improve code structure, readability, and maintainability of machine learning model training and testing script
This commit introduces several enhancements to the codebase, focusing on making it more organized, easier to understand, and simpler to maintain in the long run.
Specific changes include:
- **Modularity:** The core machine learning model functions (classification and regression) have been moved into separate modules. This improves the overall structure of the code and makes it easier to manage and test individual components.
- **Documentation:** Comprehensive docstrings have been added to all functions. These docstrings describe the purpose of each function, explain its parameters and return values, and provide usage examples. This documentation will be invaluable for future developers (including your future self!) who need to understand or modify the code.
- **Type Hints:** Type hints have been introduced to provide additional information about the expected data types for function parameters and return values. This can help catch errors early on and make the code more predictable.
- **Naming Conventions:** Variable and function names have been refined to follow the Pythonic snake_case convention and to be more descriptive of their purpose. This improves code readability and makes it easier to reason about the code's logic.
- **Error Handling:** A `try...except` block has been added to the main API endpoint to catch and handle potential exceptions gracefully. This will help prevent unexpected crashes and provide more informative error messages to users.
While the core functionality of the script remains the same, these changes significantly enhance the overall quality and maintainability of the codebase. They represent a step towards making the code more robust, scalable, and accessible to other developers.