In a ____, each element points to the next one, forming a sequence.
- Array
- Heap
- Linked List
- Stack
In a "Linked List," each element (node) contains data and a reference (or pointer) to the next node, forming a sequence. Linked lists are versatile data structures used in various applications, including dynamic data storage.
Imagine you are developing a plugin system where plugins need to register themselves upon definition. How could a metaclass facilitate this registration process?
- Metaclasses can automatically register plugins by scanning the codebase for plugin classes.
- Metaclasses can create a global registry and automatically register plugins when they are defined by modifying the metaclass's __init__ method.
- Metaclasses cannot assist in plugin registration.
- Plugins can self-register by implementing a specific interface, and the metaclass can validate their registration by checking for this interface.
Metaclasses can help manage plugin registration by imposing registration checks and maintaining a central registry for plugins as they are defined.
How would you use a mock object in Python for testing a function that makes an HTTP request?
- Create a mock object that simulates the behavior of an HTTP request, allowing you to test the function's behavior without making actual network requests.
- Modify the function to skip the HTTP request when testing, replacing it with a placeholder function.
- Use a third-party library like httpretty to intercept and mock HTTP requests within the function.
- Use the built-in unittest.mock library to automatically mock HTTP requests made by the function.
To test a function making HTTP requests, creating a mock object that simulates HTTP behavior is a common practice. This ensures that tests are isolated and don't depend on external services.
How would you implement a custom loss function in a TensorFlow or PyTorch model?
- Call the loss function during evaluation
- Define a function that calculates the loss
- Use the built-in loss functions
- Use the optimizer to define a loss function
To implement a custom loss function, you need to define a function that calculates the loss based on your specific requirements. This function is used in the training loop to compute the loss during training.
How would you handle missing data for a numerical feature in a dataset before training a machine learning model?
- Ignore missing data, it won't affect the model
- Remove the rows with missing data
- Replace missing values with a random value
- Replace missing values with the mean of the feature
Handling missing data is crucial. Replacing missing values with the mean of the feature is a common practice as it retains data and doesn't introduce bias, especially in numerical features. Removing rows or using random values can lead to loss of information or noise.
How would you handle large DataFrames that do not fit into memory using Pandas?
- Reducing the precision of data
- Reshaping the DataFrame
- Splitting the DataFrame into smaller chunks
- Using the Dask library
When dealing with large DataFrames that do not fit into memory, you can use the Dask library, which allows for distributed computing and can handle larger-than-memory datasets.
How would you handle collisions in a hash table?
- Ignore the new value
- Replace the existing value with the new one
- Resize the hash table
- Use linear probing
Collisions in a hash table can be handled by using techniques like linear probing, which involves searching for the next available slot in the table when a collision occurs. This ensures that all values are eventually stored without excessive collisions.
How would you find the shortest path in a weighted graph?
- A* Algorithm
- Breadth-First Search
- Depth-First Search
- Dijkstra's Algorithm
Dijkstra's Algorithm is used to find the shortest path in a weighted graph with non-negative edge weights. It guarantees the shortest path but doesn't work with negative weights. Breadth-First and Depth-First Search are used for different purposes, and A* is for finding the shortest path with heuristics.
How would you find the loop in a linked list?
- Iterate through the list and check for a null reference
- Use a hash table to store visited nodes
- Use a stack to track visited nodes
- Use Floyd's Tortoise and Hare algorithm
Floyd's Tortoise and Hare algorithm is a popular technique to detect a loop in a linked list. It involves two pointers moving at different speeds through the list. If there's a loop, they will eventually meet. The other options are not efficient for loop detection.
How would you ensure that a piece of code in a module is only executed when the module is run as a standalone program and not when it is imported?
- #execute_if_standalone
- #only_run_when_main
- #standalone_code
- if name == "main":
To ensure that a piece of code in a Python module is only executed when the module is run as a standalone program and not when it is imported, you can use the special if __name__ == "__main__": conditional statement. Code inside this block will only run when the module is the main entry point of the program.
How would you enable Cross-Origin Resource Sharing (CORS) in a Flask application?
- Add Access-Control-Allow-Origin header to each route manually.
- CORS is not applicable to Flask applications.
- Set CORS_ENABLED = True in the Flask app configuration.
- Use the @cross_origin decorator from the flask_cors extension.
To enable CORS in a Flask application, you typically use the @cross_origin decorator provided by the flask_cors extension. This allows you to control which origins are allowed to access your API.
How would you enable Cross-Origin Resource Sharing (CORS) in a Flask application?
- CORS is enabled by default in Flask
- Modify the browser's settings
- Use the "@cross_origin" decorator
- Use the Flask-CORS extension
You can enable CORS in Flask by using the Flask-CORS extension. The other options are not the recommended way to enable CORS in Flask.