backend-development-phases

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.

---

🧭 PHASE 1 — PROJECT SETUP

---

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

---

2️⃣ Create a Python virtual environment

python -m venv venv   # make sure u run it in proj dir - after running this command venv folder created in project dir
source venv/bin/activate     # On Windows: source venv/Scripts/activate
  = i used this
  When you log out, the virtual environment automatically deactivates — it doesn’t persist across sessions.
  source venv/Scripts/activate

Note: running all command via git bash

3️⃣ Install dependencies

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

---

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.

get token by login to delhivery and activate account with pan and aadhar

check both b2c ad b2b api options

ACCOUNT - DELHIVERY

PAHURAGON#GMAIL

Patil@4593

Delhivery API Documentation - Seamless Integration Guideone.delhivery.com

Chatgpt discusion

ChatGPTChatGPT

use production url which is working using curl

https://track.delhivery.com/api/kinko/v1/invoice/charges/.json?md=E&ss=Delivered&d_pin=110053&o_pin=110042&cgm=10&pt=Pre-paid

Parameter	Meaning	Example
md	Mode — shipping type (E = Express, S = Surface)	md=E
ss	Shipment status (mandatory) — must be one of: Delivered, RTO, or DTO	ss=Delivered
o_pin	Origin Pincode	o_pin=110042
d_pin	Destination Pincode	d_pin=110053
cgm	Chargeable weight in grams	cgm=10
pt	Payment Type (Pre-paid or COD)	pt=Pre-paid

Delhivery expects those fields

working delivery API test

curl --request GET --url 'https://api.delhivery.com/api/kinko/v1/invoice/charges/.json?md=E&ss=Delivered&o_pin=110042&d_pin=110053&cgm=500&pt=Pre-paid' --header 'Authorization: Token c9e91ab885e2012958d0562cbccf1524b9f524e8' --header 'Content-Type: application/json'

Perfect, Pavan 🎯

That output means your Delhivery Production API is working successfully now! 🚀

You just received a valid rate calculation JSON response 👇

---

✅ Breakdown of Response

[
  {
    "zone": "A",
    "status": "Delivered",
    "charged_weight": 500,
    "gross_amount": 34.94,
    "total_amount": 41.22,
    "tax_data": {
      "CGST": 3.14,
      "SGST": 3.14
    },
    "charge_DL": 30,
    "charge_LM": 2.5,
    "charge_PEAK": 2,
    "charge_DPH": 0.44
  }
]

---

🧠 Meaning of Important Fields

Field	Meaning
zone	Delivery zone based on distance between pincodes
charged_weight	Weight considered for billing (in grams)
charge_DL	Delivery logistics charge
charge_LM	Last-mile charge
charge_PEAK	Peak season surcharge
tax_data	GST breakdown (CGST + SGST)
gross_amount	Subtotal before taxes
total_amount	✅ Final total after adding all charges and taxes

So in your case: Total shipping cost = ₹41.22 for a 500g express pre-paid delivery from 110042 → 110053

---

🚀 Next Step — Python Integration

You can now safely call this same endpoint in your backend. Here’s the ready-to-use version for your delhivery.py:

import requests
from app.schemas import ShippingRequest, CourierRate
from app.utils import get_env

def get_rate(request: ShippingRequest) -> CourierRate:
    try:
        url = "https://api.delhivery.com/api/kinko/v1/invoice/charges/.json"
        headers = {
            "Authorization": f"Token {get_env('DELHIVERY_TOKEN')}",
            "Content-Type": "application/json"
        }
        params = {
            "md": "E",
            "ss": "Delivered",
            "o_pin": request.origin_pincode,
            "d_pin": request.destination_pincode,
            "cgm": request.weight,
            "pt": request.payment_type  # "Pre-paid" or "COD"
        }

        response = requests.get(url, headers=headers, params=params)
        response.raise_for_status()
        data = response.json()[0]  # API returns a list

        return CourierRate(
            courier="Delhivery",
            total_charge=data.get("total_amount", 0),
            currency="INR",
            raw_data=data  # optional for debugging
        )

    except Exception as e:
        return CourierRate(courier="Delhivery", total_charge=0, currency="INR", error=str(e))

---

Would you like me to help you modify this so it supports both staging and production environments automatically (based on an environment variable)?

Delhivery API Documentation - Seamless Integration Guideone.delhivery.com

Client Developer Portalhelp.delhivery.com

---

⚙️ PHASE 2 — BUILD & RUN LOCALLY

---

5️⃣ Run the FastAPI server

uvicorn app.main:app --reload

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

lenovo@DESKTOP-BQ5AHDH MINGW64 ~
$ curl -X 'POST' \
  'http://127.0.0.1:8000/compare-rates' \
  -H 'accept: application/json' \
  -H 'Content-Type: application/json' \
  -d '{
  "origin_pincode": "110001",
  "destination_pincode": "400001",
  "weight": 2.5,
  "length": 10,
  "width": 10,
  "height": 10
}'
  % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
100   578  100   447  100   131    228     67  0:00:01  0:00:01 --:--:--   295{"origin":"110001","destination":"400001","results":[{"courier":"Shiprocket","price":0.0,"eta_days":null,"remarks":"Error: Shiprocket auth failed: {\"message\":\"Too many failed login attempts. Please try after half an hour.\",\"status_code\":400}"},{"courier":"DTDC","price":137.5,"eta_days":3,"remarks":null},{"courier":"BlueDart","price":145.0,"eta_days":2,"remarks":null},{"courier":"Delhivery","price":347.03,"eta_days":null,"remarks":null}]}

lenovo@DESKTOP-BQ5AHDH MINGW64 ~
$

---

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}'

---

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.

---

🧱 PHASE 3 — PRODUCTION DEPLOYMENT

---

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"]

---

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

---

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

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

---

☁️ PHASE 4 — DEPLOYMENT OPTIONS

---

🧩 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

---

🧩 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

---

🧠 PHASE 5 — MONITORING & LOGGING

---

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

---

✅ PHASE 6 — TESTING

---

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

---

🔒 PHASE 7 — SECURITY HARDENING

---

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

---

🌍 PHASE 8 — FRONTEND INTEGRATION (Lovable)

---

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.

---

🎯 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.