What are the differences between the fastai.fastcore patch decorator and straightforward monkey-patching?

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Fastai's fastcore patch decorator and straightforward monkey-patching both are used to dynamically modify the behavior of an object or class, but they have some differences.

1. Safety and compatibility: Fastcore's patch decorator is designed to be safe and compatible with different versions of Python and third-party libraries. It takes care of the edge cases and avoids any potential conflicts with other code. In contrast, monkey-patching can be risky because it can break code that relies on the original behavior of the object or class.

2. Clarity and readability: Fastcore's patch decorator makes the code clearer and more readable because it explicitly indicates that a particular feature is being patched. Monkey-patching can be confusing for other developers reading the code because it hides the fact that the behavior of the object or class has been changed.

3. Flexibility and ease of use: Fastcore's patch decorator is more flexible and easier to use because it can patch entire functions or classes, as well as specific methods or properties. Monkey-patching can only modify specific methods or properties, and it requires more manual coding to achieve the same result.

4. Testability and maintainability: Fastcore's patch decorator is more testable and maintainable because it creates a temporary patch that can be easily removed or replaced if necessary. Monkey-patching can create hidden dependencies and make it harder to debug or maintain the code later.