Decorators | 19/100 Days of Python Algo Trading

Congratulations on reaching this stage!

If you’re here, it means you’re truly dedicated to mastering Python. Directly below, you’ll find a quiz designed to help you reinforce what you’ve just learned. This isn’t just about recalling facts; it’s about deeply understanding the concepts. Take a moment to answer the questions and see how well you can apply the knowledge from the video. You’re doing great—every question you tackle brings you one step closer to becoming a Python expert!

Day 19: Decorators

1. What is a decorator in Python?

A) A function that modifies the functionality of another function.

B) A variable that stores data temporarily.

C) A module used exclusively for data visualization.

D) A type of Python class that encapsulates another class.

2. How are decorators typically used in Python?

A) To change the plot style of data visualization.

B) To modify or enhance the behavior of a function or method.

C) To declare static variables within a function.

D) To handle exceptions within critical functions.

3. What syntax is used to apply a decorator to a function in Python?

A) @decorator_name

B) #decorator_name

C) decorator_name!

D) $decorator_name

4. Which of the following is a valid Python decorator?

A) def my_decorator(func): def wrapper(): print("Something is happening before the function is called.") return func() return wrapper

B) def my_decorator: def wrapper(func): print("Something is happening before the function is called.") return func() return wrapper

C) my_decorator(func): def wrapper(): print("Something is happening before the function is called.") return func() return wrapper

D) @def my_decorator(func): def wrapper(): print("Something is happening before the function is called.") return func() return wrapper

5. What are common use cases of decorators in algorithmic trading?

A) To validate input data for trading algorithms.

B) To log the performance of trade execution functions.

C) To manage memory allocation for high-frequency trading data.

D) Both A and B.

6. What does a decorator do when it wraps a function?

A) It permanently alters the original function’s code.

B) It adds additional functionality before and/or after the original function executes.

C) It prevents the function from being called.

D) It compiles the function for faster execution.

7. Which feature allows decorators to be applied to any callable in Python?

A) Polymorphism

B) Inheritance

C) Dynamic typing

D) First-class functions

8. Why might decorators be used in a live trading system?

A) To change trading strategies dynamically.

B) To optimize algorithms at runtime.

C) To monitor function execution and log transactions.

D) To encrypt data streams.

9. How can decorators enhance debugging in an algo trading application?

A) By catching and handling all exceptions within the decorator.

B) By logging entry, exit, and exceptions of decorated functions.

C) By accelerating the execution of debugged code.

D) By restricting access to debugging tools.

10. What problem can occur if decorators are not designed properly?

A) They can introduce side effects that alter the state of the application.

B) They can delete the function they are meant to decorate.

C) They prevent other decorators from being applied to the same function.

D) They overwrite all existing data in the application.

11. How can you stack decorators on a single function?

A) By listing decorators one after another, separated by commas.

B) By using a single @ symbol followed by all decorator names.

C) By placing each decorator on the line directly above the function definition.

D) By nesting decorators within each other.

12. What is required to create a decorator that can accept arguments?

A) An additional nested function inside the decorator.

B) Special modules such as args and kwargs.

C) Overloading the decorator function.

D) Using global variables.

13. Which of the following decorators is built into Python?

A) @staticmethod

B) @dynamicmethod

C) @async

D) @sync

14. What is the role of the wrapper function in a decorator?

A) To execute the actual business logic of the application.

B) To handle all exceptions thrown by the application.

C) To wrap the original function and add pre- and post-execution behavior.

D) To serve as the main entry point of the program.

15. How does using decorators relate to the DRY (Don't Repeat Yourself) principle?

A) Decorators can lead to code duplication.

B) Decorators inherently violate the DRY principle.

C) Decorators promote code reuse by allowing the same functionality to be added to multiple functions.

D) Decorators are unrelated to the DRY principle.

16. What is a potential drawback of using decorators?

A) They can make stack traces harder to understand.

B) They are not compatible with modern Python versions.

C) They significantly slow down the runtime.

D) They are only available in Python 2.x.

17. How do decorators affect the scope of the variables within the functions they decorate?

A) They restrict all variables to local scope.

B) They have no effect on variable scope.

C) They make all variables global.

D) They convert local variables to nonlocal scope.

18. Can decorators be used on class methods?

A) Yes, decorators can be used on both regular functions and class methods.

B) No, decorators can only be applied to standalone functions.

C) Only if the class inherits from a specific Python base class.

D) Yes, but only if the class method does not modify any class attributes.

19. What is a decorator factory in Python?

A) A tool to mass-produce decorators.

B) A function that returns a decorator.

C) A module that contains pre-built decorators.

D) A class designed exclusively for creating decorators.

20. How would you apply multiple decorators to a function where execution order is critical?

A) Order the decorators in the order they should execute, from top to bottom.

B) Order the decorators in the order they should execute, from bottom to top.

C) Decorators do not support ordered execution.

D) Use a special @ordered decorator to manage execution.