This repository serves as the remote Python code execution backend for the Pennant notebook application. It uses Flask, Celery, RabbitMQ and Redis to handle code execution requests and manage notebook states.

• Installation
• Configuration
• Usage
• API Endpoints
• Contributing

1. Clone the repository:

git clone https://github.com/marwan37/pennant-flask-server.git

2. Install the required packages:

pip install -r requirements.txt

• Celery Configuration: Modify the settings in the config/celery.py file.
• Celery Worker Service: A systemd service file is provided in config/celery-worker.service.

Run the Flask application:

python app.py

1. Navigate to the project directory.
2. Run the following command to start the Celery worker:

celery -A app.celery worker

Submits code for execution.

URL: /api/submit

Method: POST

Response:

Retrieves the status of a submitted notebook.

URL: /api/status/:submissionId

Method: GET

Resets the context for a notebook.

URL: /api/reset/:notebookId

Method: POST

Checks if a notebook is active.

URL: /notebookstatus/:notebookId

Method: GET

Formats Python code.

URL: /format-python

Method: POST

Returns: 202 Accepted and submissionId (token)

Initiates submission. Starts code execution process.

{
	"notebookId": "111",
	"cells": [
      {
        	"cellId": "3",
        	"code": "print('Hello, world!')"
      }
  ]  
}

Returns: 200 OK and payload of results.

{
   "submissionId": "0c5796d7-c8fb-4b4c-a13d-9ebedc914551",
   "status": "success",
   "results": [
         {
           "cellId": "3",
           "type": "output",
           "output": "Hello, world!"
       }
   ]
}