This is a simple RESTful API built using the Flask web framework for Python. It provides two main functionalities:

• Creating new requests
• Inquiring about the status of existing requests

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

You will need to have the following installed on your machine:

• Python 3.x
• Flask web framework
• Flask-Cors
• numpy
• scikit-learn
• xgboost

To install the necessary dependencies, navigate to the root of the project and run the following command:

pip install -r requirements.txt

Open another terminal, navigate to the root of the project and run the following command:

python computation.py

To run the application, navigate to the root of the project and run the following command:

python app.py

This will start the server on http://0.0.0.0:8080/ and the application will be ready to handle incoming requests.

To use this package, you first need to import it:

from jsonprocessor import RequestHandler, PredictionStatus, RequestData

The RequestHandler class can be used to write request data to a file and create a subdirectory.

request_handler = RequestHandler(request_id, request_data)
request_handler.write_request()
request_handler.create_subdirectory()

The PredictionStatus class can be used to inquire about the status of processed files.

prediction_status = PredictionStatus(request_id)
status = prediction_status.inquire_status()

The RequestData class can be used to get the request data of a processed file.

request_data = RequestData(request_id)
data = request_data.get_request()

• The package is currently only able to handle request and response data as file operations, you can integrate the package with your processing service to make it more useful.
• The package is a simple example and you can modify it to suit your needs.

• Flask - The web framework used
• Flask-Cors - To handle cross-origin requests

• This project is just a demonstration of basic functionality that can be built using Flask, it is not production-ready.
• You should consider storing the data in a real database for production-ready.
• Depending on your use case, you might consider adding authentication and access control mechanisms to the API.
• You might also want to think about ways to handle errors and exceptions gracefully, for example, by returning appropriate error messages or status codes.
• Also you may consider adding other endpoints to update or delete the request, or even include an endpoint to handle the requests.

This project is licensed under the MIT License