When using the unittest framework, which method is executed before each test method is run?
- beforeTest()
- init()
- setUp()
- setUpClass()
In the unittest framework, the setUp() method is executed before each test method is run. This method is used to set up any preconditions or resources needed for the test.
What would be the result of attempting to import a module that does not exist?
- It will prompt you to create the module.
- It will silently fail, and no error will be thrown.
- You will get a runtime error, and the program will crash.
- You will receive a warning but the program will continue running.
When attempting to import a non-existent module in JavaScript, it will silently fail, and no error will be thrown. This is because ES6 modules use static imports, and errors are only raised at runtime when the module cannot be found during the initial load.
What would be the time complexity of inserting an element in a balanced Binary Search Tree?
- O(1)
- O(log n)
- O(n log n)
- O(n)
In a balanced Binary Search Tree (BST), inserting an element takes O(log n) time on average. This is because the tree's balanced structure ensures that you traverse down the tree logarithmically with respect to the number of nodes.
What is the time complexity of inserting an element into a balanced binary search tree?
- O(1)
- O(log n)
- O(n log n)
- O(n)
The time complexity of inserting an element into a balanced binary search tree (BST) is O(log n), where n is the number of nodes in the BST. In a balanced BST, each insertion or search operation reduces the search space by half, leading to logarithmic time complexity.
What would be the best data structure to implement a priority queue?
- Heap
- Linked List
- Queue
- Stack
A Heap is the best data structure to implement a priority queue. Heaps, such as Binary Heaps or Fibonacci Heaps, efficiently maintain the highest-priority element at the top, allowing for quick access and extraction of elements with the highest priority.
What would be the best sorting algorithm to use if you are concerned about worst-case time complexity?
- Bubble Sort
- Merge Sort
- Quick Sort
- Selection Sort
Merge Sort is known for its consistent and reliable worst-case time complexity, which is O(n log n) for both average and worst cases. Quick Sort, although efficient in practice, can have a worst-case time complexity of O(n^2) if not implemented carefully.
What would be the most efficient way to handle real-time data updates between a Python back-end and a front-end application?
- Poll the server at regular intervals
- Use HTTP long polling
- Use WebSockets
- Utilize RESTful APIs
Using WebSockets is the most efficient way to handle real-time data updates. WebSockets provide full-duplex communication channels over a single TCP connection, enabling real-time, bidirectional data transfer between the server and client.
What is the primary purpose of the HTTP OPTIONS method in RESTful APIs?
- To delete a resource on the server
- To request data from the server
- To retrieve information about the communication options for the target resource
- To update resource data on the server
The primary purpose of the HTTP OPTIONS method in RESTful APIs is to retrieve information about the communication options available for the target resource. It is used to inquire about the HTTP methods and other communication options supported by a resource.
What is the primary purpose of using metaclasses in Python?
- To create instances of classes
- To define constants
- To encapsulate data
- To modify the behavior of classes
Metaclasses in Python are primarily used to modify the behavior of classes. They allow you to customize class creation, attribute handling, and more. This makes them a powerful tool for advanced customization in Python.
What is the primary use of a generator expression in Python?
- To create a dictionary.
- To create a list of values.
- To create a new generator object.
- To modify an existing generator.
The primary use of a generator expression in Python is to create an iterable generator object. Generator expressions are memory-efficient and generate values on-the-fly, making them useful for working with large datasets.