What are the common use cases for Python decorators?

  1. Logging: Decorators can be used to record the input parameters and output results of a function, or to record information such as the execution time of a function, making it easier to debug and analyze the program.
  2. Authorization check: Decorators can be used to verify users’ permissions, such as checking if a user is logged in or has specific roles, in order to restrict access to certain functions or interfaces.
  3. Performance optimization: Decorators can be used to cache the results of a function, preventing redundant calculations and improving the program’s performance.
  4. Error handling: Decorators can be used to capture exceptions during the execution of a function and handle or log error information.
  5. Log monitoring: Decorators can be used to monitor the execution of functions, such as recording metrics like the number of times a function is called, execution time, etc., to help analyze performance bottlenecks in the program.
  6. Transaction Management: Decorators can be used to manage database transactions, ensuring that transactions are rolled back in a timely manner if an exception occurs during function execution.
  7. Caching data: decorators can be used to cache the return values of functions, avoiding redundant calculations.
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