Adaface Sample Flask Questions

Consider a complex Flask application that uses an application factory pattern for scalability and flexibility. The application also utilizes global variables to manage configurations across different parts of the app. Review the following pseudo-code, which illustrates a portion of this application where an issue with application context might arise when deploying:

In this scenario, where the application is configured to run with multiple threads, what is the potential issue that could arise when processing multiple requests concurrently?

A: The db_connection in g might be shared across requests leading to data integrity issues.
            B: The USE_CACHE configuration might reset to its default value in between requests.
            C: Multiple threads might cause the application to crash due to improper locking mechanisms.
            D: There will be no issues as Flask naturally handles application contexts per request in a thread-safe manner.
            E: The configuration change in current_app.config['USE_CACHE'] will not be visible to the request handlers.

Examine the advanced Flask application setup below which uses an application factory pattern and is intended to handle multiple user requests simultaneously using threading. The developer has configured an endpoint to perform data processing based on user inputs and global settings. However, the application might exhibit unexpected behavior due to its handling of the Flask context and multithreading. Your task is to determine the output of this setup under concurrent requests.
            
            The pseudo-code for the Flask application is as follows:

In this code, the threads are launched almost simultaneously. Thread1 executes a POST request to /set_cache, and Thread2 executes a GET request to /get_data. What is the likely output of Thread2 when it runs concurrently with Thread1?

A: "Using Cache"
            B: "Not Using Cache"
            C: The output is non-deterministic, depending on the execution timing of Thread1 and Thread2.
            D: A Flask RuntimeError due to the application context being improperly managed.
            E: No response due to a deadlock in resource access between the threads.