backend code

Perfect 🔥 — now that you’ve got the backend code, let’s make it enterprise-ready from scratch → deployment → frontend integration → testing.

Here’s the complete DevOps-style production setup — like how you’d do it in a real company.

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🧭 PHASE 1 — PROJECT SETUP

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1️⃣ Create project structure

mkdir shipping-backend && cd shipping-backend
mkdir -p app/services
touch app/{main.py,schemas.py,utils.py}
touch app/services/{shiprocket.py,delhivery.py,dtdc.py,bluedart.py}
touch requirements.txt .env README.md

Your structure should look like:

shipping-backend/
├── app/
│   ├── main.py
│   ├── schemas.py
│   ├── utils.py
│   ├── services/
│   │   ├── shiprocket.py
│   │   ├── delhivery.py
│   │   ├── dtdc.py
│   │   └── bluedart.py
├── .env
├── requirements.txt
└── README.md

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2️⃣ Create a Python virtual environment

python3 -m venv venv
source venv/bin/activate     # On Windows: venv\Scripts\activate

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3️⃣ Install dependencies

echo "fastapi
uvicorn
requests
python-dotenv" > requirements.txt
pip install -r requirements.txt

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4️⃣ Add environment variables

Edit .env:

[email protected]
SHIPROCKET_PASSWORD=your_password
DELHIVERY_TOKEN=your_delhivery_token

🔐 Store secrets in AWS Secrets Manager or Vault in real environments.

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⚙️ PHASE 2 — BUILD & RUN LOCALLY

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5️⃣ Run the FastAPI server

uvicorn app.main:app --reload

Visit your API: 👉 http://127.0.0.1:8000/docs (Auto Swagger UI)

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6️⃣ Test with sample data

curl -X POST http://127.0.0.1:8000/compare-rates \
-H "Content-Type: application/json" \
-d '{"origin_pincode": "110001", "destination_pincode": "400001", "weight": 2.5, "length": 10, "width": 10, "height": 10}'

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7️⃣ Frontend connection (Lovable AI app)

In your frontend, modify the Compare Rates button handler to make an API request like:

const response = await fetch("https://your-domain.com/compare-rates", {
  method: "POST",
  headers: { "Content-Type": "application/json" },
  body: JSON.stringify({
    origin_pincode,
    destination_pincode,
    weight,
    length,
    width,
    height
  }),
});
const data = await response.json();
console.log(data.results);

✅ Display data.results dynamically in your Lovable frontend UI.

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🧱 PHASE 3 — PRODUCTION DEPLOYMENT

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8️⃣ Create a production Dockerfile

FROM python:3.11-slim

WORKDIR /app
COPY . .
RUN pip install --no-cache-dir -r requirements.txt

ENV PORT=8000
EXPOSE 8000

CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

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9️⃣ Build & run Docker locally

docker build -t shipping-api .
docker run -d -p 8000:8000 --env-file .env shipping-api

Test: 👉 http://localhost:8000/docs

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🔟 Push to container registry (example: GitHub or Docker Hub)

docker tag shipping-api yourdockerhubuser/shipping-api:latest
docker push yourdockerhubuser/shipping-api:latest

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☁️ PHASE 4 — DEPLOYMENT OPTIONS

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🧩 Option 1: Render (free & easy)

1. Go to https://render.com

2. Create a new “Web Service”

3. Connect your GitHub repo

4. Set environment variables in Render Dashboard

5. Command:

   uvicorn app.main:app --host 0.0.0.0 --port 8000

6. Deploy and get your API endpoint like 👉 https://shipping-api.onrender.com/compare-rates

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🧩 Option 2: AWS ECS / EKS (for enterprise)

• Store image in Amazon ECR

• Deploy via ECS (Fargate) or EKS (Kubernetes)

• Expose with an Application Load Balancer (ALB)

• Use AWS Parameter Store / Secrets Manager for .env variables

• Enable HTTPS via ACM + Route53

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🧠 PHASE 5 — MONITORING & LOGGING

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Enable FastAPI logging

Add in app/main.py:

import logging
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)
logger.info("Shipping API started successfully.")

For production:

• Use AWS CloudWatch, Grafana Loki, or ELK stack

• Set up alerts for errors or API downtime

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✅ PHASE 6 — TESTING

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Unit testing

Create tests/test_api.py:

from fastapi.testclient import TestClient
from app.main import app

client = TestClient(app)

def test_compare_rates():
    response = client.post("/compare-rates", json={
        "origin_pincode": "110001",
        "destination_pincode": "400001",
        "weight": 1.0,
        "length": 10,
        "width": 10,
        "height": 10
    })
    assert response.status_code == 200
    assert "results" in response.json()

Run tests:

pytest -v

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🔒 PHASE 7 — SECURITY HARDENING

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1. Add CORS middleware in FastAPI:

   from fastapi.middleware.cors import CORSMiddleware
   app.add_middleware(
       CORSMiddleware,
       allow_origins=["*"],  # restrict to frontend domain later
       allow_methods=["*"],
       allow_headers=["*"],
   )

2. Always use HTTPS

3. Rotate API tokens periodically

4. Use rate limiting (e.g., slowapi)

5. Set up error monitoring via Sentry

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🌍 PHASE 8 — FRONTEND INTEGRATION (Lovable)

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In your Lovable frontend:

• Add .env variable for backend URL Example: VITE_API_URL=https://shipping-api.onrender.com

• Replace your button handler with:

  const response = await fetch(`${import.meta.env.VITE_API_URL}/compare-rates`, {
    method: "POST",
    headers: { "Content-Type": "application/json" },
    body: JSON.stringify({
      origin_pincode,
      destination_pincode,
      weight,
      length,
      width,
      height
    }),
  });
  const data = await response.json();
  setRates(data.results);

• Show rates list in a UI card.

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🎯 FINAL RESULT

✅ Fully functional production-grade backend ✅ Integrated securely with frontend ✅ Deployable on any cloud ✅ Tested & Monitored

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Would you like me to add GitHub Actions CI/CD (auto deploy backend to Render or AWS on every push)? That’s the next logical step for an enterprise-grade setup.