The Python wraps Decorator

One common challenge with decorators is that they can unintentionally strip away important metadata from the functions they decorate. Fortunately, there is a solution to this problem in the form of the Python wraps decorator, which is available in the functools module. You can use wraps in any decorator you create to preserve the original metadata.
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Python Decorators

Python decorators allow you to add functionality to existing functions without modifying their original code directly. They are especially useful for adding common functionality such as logging, authentication, performance monitoring, and caching to specific functions you implement. To crate a decorator, you don't need to use new Python features beyond that of functions, however Python does have specialized @ syntax that can simplify the process.
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Python Generator Expressions

Python generator expressions offer a succinct and efficient way of creating simple generators. Generator expression syntax is similar to that of list comprehensions. And much like those, generator expressions allow you to generate sequences by applying expressions to items in an iterable and potentially filtering them based on specified conditions.
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Python Generators

Python generators allow you to easily create efficient sequences of values using iterators. They can be implemented with special functions called generator functions, which use the yield keyword to yield values one at a time, rather than returning them all at once. Generators can also be created with generator expressions, which are similar to list comprehensions but produce values lazily as well.
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