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backendnstructions.md

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To build and deploy the backend for your instance of the AcademicInsights Extension efficiently, you can follow this step-by-step guide.

Step 1: Set Up a Virtual Environment

Create a Python virtual environment to manage dependencies:

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

Verify the backend runs locally:

python app.py

The backend should be accessible at http://localhost:5000.

Step 2: Add Docker Support

Containerize your backend for deployment using Docker.

Dockerfile:

FROM python:3.9-slim

WORKDIR /app

# Install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy project files
COPY . .

# Expose port 5000
EXPOSE 5000

# Run the application
CMD ["python", "app.py"]

Build and Run the Docker Image:

  1. Build the image: 
    docker build -t web-extension-backend .
  2. Run the container: 
    docker run -p 5000:5000 web-extension-backend

Step 3: Deploy the Backend

Choose a cloud platform to host the backend. Below are some common options:

Option 1: Deploy on AWS (Elastic Beanstalk or EC2)

  1. Elastic Beanstalk:

    • Install the Elastic Beanstalk CLI: 
      pip install awsebcli
    • Initialize the project: 
      eb init
    • Deploy the application: 
      eb create web-extension-env

  2. EC2 Instance:

    • Launch an EC2 instance with Python pre-installed.
    • Install Docker: 
      sudo apt update
sudo apt install docker.io
    • Transfer files to the instance and build the Docker image: 
      docker build -t web-extension-backend .
docker run -p 5000:5000 web-extension-backend

Option 2: Deploy on Heroku

  1. Install the Heroku CLI: 
    curl https://cli-assets.heroku.com/install.sh | sh
  2. Log in to Heroku: 
    heroku login
  3. Create a new Heroku app: 
    heroku create web-extension-backend
  4. Add a Procfile to the project: 
    web: gunicorn app:app
  5. Push the app to Heroku: 
    git init
git add .
git commit -m "Initial commit"
heroku git:remote -a web-extension-backend
git push heroku main

Option 3: Deploy on Google Cloud Platform (GCP)

  1. Google App Engine:

    • Create an app.yaml file: 
      runtime: python39
entrypoint: gunicorn -b :$PORT app:app
    • Deploy the app: 
      gcloud app deploy

  2. Google Kubernetes Engine:

    • Set up a Kubernetes cluster.
    • Push the Docker image to Google Container Registry (GCR): 
      docker tag web-extension-backend gcr.io/<project-id>/web-extension-backend
docker push gcr.io/<project-id>/web-extension-backend
    • Deploy the image using Kubernetes YAML configuration.

Step 4: Update Frontend API URLs

After deployment, update the API base URL in your extension's popup.js:

const BASE_URL = "https://your-deployment-url.com";

Replace http://localhost:5000 with your production backend URL.

Step 5: Secure Your Backend

  1. Add Authentication:

    • Verify Firebase ID tokens for all endpoints.
    • Use HTTPS for secure communication.

  2. Rate Limiting:

    • Protect your APIs from abuse using libraries like Flask-Limiter.

  3. Environment Variables:

    • Use .env files or cloud-specific environment variable managers for sensitive data like Firebase credentials.

Step 6: Monitor and Maintain

  1. Logging:

    • Add logging to track requests and errors using Python's logging module.

  2. Monitoring:

    • Use tools like Prometheus, AWS CloudWatch, or Google Monitoring for real-time tracking.

  3. Scaling:

    • Configure autoscaling for cloud services to handle varying traffic loads.