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Okay, let's dive into how to wrap functions in Python while meticulously preserving their metadata. This is a crucial technique for building decorators, enhancing function behaviors, and maintaining a clean and understandable codebase.

*Why Preserve Metadata?*

When you wrap a function, you're essentially replacing the original function with a new one (your wrapper). By default, the wrapper function will inherit its own attributes, such as its name, docstring (documentation), and argument specifications. This can be problematic for a few key reasons:

*Introspection:* Tools like help() and IDEs rely on a function's metadata to provide useful information to the user. If the metadata is incorrect, users will see the wrapper's information instead of the original function's.
*Testing:* Automated testing often checks function names and docstrings. Incorrect metadata can lead to test failures.
*Readability/Maintainability:* Incorrect metadata reduces code clarity and makes it harder to understand what a function is actually doing.

*The `functools` Module to the Rescue*

Python's `functools` module provides the tools to wrap functions while keeping the original function's metadata intact. The most important tool is the `functools.wraps` decorator.

*1. The `functools.wraps` Decorator*

`functools.wraps(wrapped, assigned=('__module__', '__name__', '__qualname__', '__doc__', '__dict__'), updated=('__dict__',))`

*`wrapped`:* The original function whose metadata you want to preserve.
*`assigned`:* A tuple of attribute names to copy directly from the original function to the wrapper. The default values cover the most common and important attributes:
`'__module__'` (the module the function is defined in)
`'__name__'` (the function's name)
`'__qualname__'` (the fully qualified name, e.g., `MyClass.my_method`)
`'__doc__'` (the function's docstring)
`'__dict__'` (the function's `__dict__`, whic ...

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