Jupyter File, Generator , Decorator, function 8 Python 25

Jupyter File, Generator , Decorator, Function 8,

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A Python generator is a function that returns an iterator object, allowing you to iterate over a potentially infinite sequence of values without having to store them all in memory at once. Generators are defined using the "yield" keyword instead of "return", and can be paused and resumed during execution. They are useful for tasks such as reading large files, generating permutations or combinations, and implementing coroutines. Generators can also be combined with other functions like "map" and "filter" to create powerful data processing pipelines. Overall, Python generators offer a flexible and memory-efficient way to work with large or complex data sets.

A Python decorator is a function that modifies the behavior of another function. It is defined with the '@' symbol followed by the name of the decorator function, and placed before the function being decorated. Decorators can be used to add functionality such as logging, caching, or authentication to a function without modifying its source code. They work by wrapping the original function with a new function that can modify its behavior before and/or after its execution. Decorators are a powerful feature of Python and are commonly used in web frameworks, data science libraries, and other applications where code reusability is important.