What are decorators in Python?

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In Python, decorators are a secure, versatile instrument for changing a function’s or class actions. They are employed to enclose an additional function or method to modify its operation for some time without making a permanent alteration to the function.

This is a common practice at the Softronix IT Training, which is the best institute for Python in Nagpur, where we aim at making students understand these basic as well as the core concepts like decorators through which one can write clean and optimal code in Python.

What is a Decorator?

Therefore, a decorator can be described as a function that requires another function and further enhances its operations without actually altering the said function. A decorator is a representational tool that gives the end user the ability to add utility to any predefined functions or methods but does not alter the original functions. This concept proves very useful in following the DRY—Don’t Repeat Yourself principle, thus making the code more modular and easy to read.

Types of Decorators

It is noteworthy that the decorators could be used for func, method and classes in Python. Here are the primary types:

  1. Function Decorators: These are the most popular and they are applied to function.

  2. Method Decorators: These decorators are used for methods within classes Specifically, it is used in classes and apply to them whatever function is decorated.

  3. Class Decorators: They change classes Concordance These decorators transform classes.

Use Cases of Decorators

Decorators are versatile and can be used in numerous scenarios, such as:

●   Logging: Monitoring occurrences at the time when a code is executed.

●   Authorization: Authorizing the users to use particular functions.

●   Timing: Timing the execution of the functions.

●   Memoization: Delaying, or storing in memory, the outcomes of costly computations done to arguments passed.

Conclusion

Decorators are advanced components in Python that help the programmer to write less code, easily understandable and reusable code. They let you extend the functionality of the code that you already have without altering basic logic and design. For instance, at the Softronix IT Training – the institute for Python in Nagpur – we pay a lot of attention to such datasets and observe diverse difficulties arising from their employment in actual programming. Whether you are logging calls, authorizing a function, timing functions, or caching the results, decorators are a perfect way to do so.

Through the involvement in our courses, one will acquire extensive proficiency in decorators and all other advanced features of Python making the person a well-rounded Python developer.

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