Implement Asynchronous Execution for the "Staging" Function in Genomeshader

[bshifaw]

Problem:

The "staging" function in Genomeshader is computationally expensive and can take a significant amount of time to complete. In an interactive environment like Jupyter notebooks, this can block the user from executing other tasks while waiting for the "staging" function to complete.

Proposed Solution:

Implement asynchronous execution for the "staging" function. This would allow the function to run in the background, freeing up the user to execute other tasks in the meantime. The user can then check back later to see if the "staging" function has completed.

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Tasks:

• Refactor the "staging" function to support asynchronous execution. This may involve using Python's built-in asyncio library or a similar library.
• Update any calls to the "staging" function to handle the asynchronous execution. This may involve using await or similar syntax.
• Test the updated "staging" function in a Jupyter notebook to ensure that it runs in the background and allows other tasks to be executed while it is running.

Acceptance Criteria:

• The "staging" function should support asynchronous execution.
• Calls to the "staging" function should not block the execution of other tasks.
• The user should be able to check the status of the "staging" function and retrieve the results when it has completed.
• The updated functionality should be covered by tests to ensure it works as expected.