How can you change the order of method resolution in multiple inheritance?
- By changing the order of base classes in the class definition
- By using the @method_resolution decorator
- Using the C3 Linearization algorithm (C3 superclass linearization)
- Using the super() function
You can change the order of method resolution in multiple inheritance in Python by using the C3 Linearization algorithm (C3 superclass linearization). This algorithm calculates the order in which base classes are considered when looking up methods. The super() function is used to call methods in the method resolution order, but it doesn't change the order itself. Changing the order of base classes in the class definition directly affects method resolution but is discouraged. There is no standard @method_resolution decorator in Python.
How can you configure a Flask application to use an external configuration file?
- a. Define configuration settings directly in your Flask app's main Python file.
- b. Create a separate Python module with configuration settings and import it into your Flask app.
- c. Use environment variables for configuration.
- d. Flask doesn't support external configuration files.
You can configure a Flask application to use an external configuration file by creating a separate Python module with configuration settings and importing it into your Flask app. This allows for better separation of concerns and easier configuration management. Options a, c, and d are not recommended practices.
How can you create a decorator that takes arguments?
- By modifying the Python interpreter.
- By using the @decorator syntax with argument values.
- Decorators in Python cannot take arguments.
- Using a function that takes the decorator arguments and returns the actual decorator function.
To create a decorator that takes arguments, you can define a function that accepts those arguments and returns a decorator function. This allows you to customize the behavior of the decorator based on the arguments provided.
How can you create a generator in Python?
- Using a class with __iter__ and __next__ methods
- Using a for loop
- Using a while loop
- Using the yield keyword in a function
You can create a generator in Python by defining a function with the yield keyword. When the function is called, it returns an iterator that generates values one at a time when you iterate over it. This is a fundamental feature for working with large datasets efficiently.
How can you create a generator that produces values infinitely?
- JavaScript doesn't support infinite generators.
- Use a for loop and return values endlessly.
- Use a while loop with a condition that never becomes false.
- Use the function* syntax and an infinite while (true) loop, yielding values within the loop.
To create a generator that produces values infinitely, you can use the function* syntax and an infinite while (true) loop, yielding values within the loop. This allows you to generate an endless sequence of values efficiently.
How can you create class methods that cannot be overridden by subclasses?
- By defining the method inside the constructor.
- By making the method static.
- By marking the method as final.
- By using the const keyword.
In many object-oriented programming languages, including JavaScript and Java, you can create methods that cannot be overridden by subclasses by marking them as final. This keyword indicates that the method is the final implementation and cannot be further overridden.
How can you customize the appearance of your plots in Matplotlib, like setting the line width, color, and style?
- By modifying the plt.style attribute
- By passing arguments to Matplotlib plotting functions
- By using the plot_format() method
- Using the customize() function
In Matplotlib, you can customize plot appearance by passing various arguments like linewidth, color, and linestyle directly to the plotting functions (e.g., plot() or scatter()). This allows you to control the line width, color, and style for individual elements in your plot.
A decorator in Python is a design pattern used to add new functionality to an object without altering its ____.
- attributes
- class
- methods
- structure
In Python, decorators are typically used to add new functionality to methods of a class without changing the method's name or signature. This is commonly used for tasks like logging, authorization, and caching.
A ____ algorithm guarantees to run in the same time (or space) for any input of the same size.
- Deterministic
- In-Place
- Non-Deterministic
- Stable
A Deterministic algorithm guarantees to run in the same time (or space) for any input of the same size. It is predictable and has consistent performance.
A ____ in Python is a collection of key-value pairs, where the keys must be immutable.
- Dictionary
- List
- Set
- Tuple
In Python, a dictionary is a collection of key-value pairs, where the keys must be immutable (and usually unique). Tuples are immutable, making them suitable for use as dictionary keys.