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 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 primary use of the __init__ method in a Python class?
- Defining class methods
- Handling exceptions
- Inheriting from a superclass
- Initializing class attributes
The __init__ method is a special method in Python classes used to initialize class attributes when an object of the class is created. It's like a constructor in other programming languages. It allows you to set the initial state of an object's attributes.
What is the primary use of the Pandas library in Python?
- Data manipulation and analysis
- Game development
- Machine learning
- Web development
The primary use of the Pandas library in Python is for data manipulation and analysis. It provides data structures like DataFrame and Series, making it easy to work with structured data.
What is the purpose of an assertion in a unit test?
- To check if a condition is true or false
- To define test cases
- To log test results
- To pause the test execution
Assertions in unit tests are used to check if a given condition is true. If the condition is false, the assertion will raise an exception, indicating a test failure. Assertions are essential for verifying that your code behaves as expected during testing.
What is the purpose of the assert statement in Python?
- To define a function
- To pause code execution
- To print a message to the console
- To raise an exception if a condition is false
The assert statement is used to check a condition and, if the condition is False, it raises an AssertionError exception. It is often used for debugging and ensuring that assumptions about the code are valid.
What is the purpose of using setUp and tearDown methods in a unittest TestCase class?
- setUp and tearDown methods are optional and not commonly used in unittest TestCase classes.
- setUp is used to define test cases, and tearDown is used to define assertions.
- setUp is used to run test methods, and tearDown is used to finalize the test suite.
- setUp is used to set up any necessary preconditions or resources before running each test method, while tearDown is used to clean up or release resources after each test method completes.
In the unittest framework, setUp is used to prepare the environment or resources required for each test, and tearDown is used to clean up or release those resources after the test is completed. They ensure a clean and consistent state for each test method.
What is the result of the following operation in Python? ('apple',) * 3
- ('apple', 3)
- ('apple', 'apple', 'apple')
- ('apple',)
- Error
The result of ('apple',) * 3 is a tuple containing three copies of the string 'apple'. The comma in ('apple',) is necessary to create a single-element tuple.
What is the time complexity of a linear search algorithm in the worst case?
- O(1)
- O(log n)
- O(n)
- O(n^2)
In the worst case, a linear search algorithm has a time complexity of O(n). This means that in the worst-case scenario, where the element being searched for is at the end of the list or array, the algorithm may need to examine every element in the list before finding the target.