Common pitfalls with decorators include not preserving function metadata and unintentionally altering function behavior. Use `functools.wraps` to maintain metadata and ensure that decorators are properly designed.

Using decorators in Python can enhance code modularity and readability, but there are common pitfalls that developers should be aware of. One significant issue is that decorators can alter the behavior of the functions they wrap, which may lead to unexpected outcomes if not carefully designed. Always ensure that your decorator function returns the original function or a modified version that preserves the expected behavior. Additionally, decorators can strip away function metadata, such as the function name and docstring. To prevent this, utilize functools.wraps in your decorator definition, which helps maintain the original function’s metadata when it is wrapped. Another common mistake is to apply decorators inappropriately, such as stacking them without a clear understanding of their order and how they will interact. Thoroughly test your decorators in isolation to ensure they behave as expected, and consider documenting their usage and potential side effects for other developers. By being mindful of these pitfalls, you can leverage decorators effectively in your Python code.