creeksonJoseph/shamba-records

# Smart Season Field Monitoring System A full-stack, production-ready web application designed to track crop progress across multiple fields during a growing season. Admins can add agents, add fields to agents and then the agents can add plants to the field and everything trackead and visible to the admins ### Live Deployments - **Frontend App:** smartseas0n.vercel.app - **Backend API:** shamba-records-rkb7.onrende… ## Tech Stack - **Backend:** Django, Django REST Framework,(Deployed on Render via docker) - **Frontend:** React, Vite, React Router v6, TailwindCSS, React Query, shadcn/ui (Deployed on Vercel) - **Database:** PostgreSQL (Neon Serverless Postgres) - **Containerization:** Multi-stage Dockerfile architecture for isolated, pristine production backend deployment. --- ## Table of Contents 1. Setup & Deployment Instructions - Local Backend Development - Populating Test Data - Local Frontend Development 2. Production Architecture & Performance Patterns - Decoupled Deployment Model - Progressive Rendering (UI Performance) 3. Data & Risk Architecture - Separation of Fields and Plants - Automated Risk Algorithm 4. Demo Credentials --- ## 1. Setup & Deployment Instructions ### Local Backend Development 1. Navigate to the backend directory: ```bash cd backend ``` 2. Create your `.env` file (ensure your Neon `DATABASE_URL` is configured): ```bash cp .env.example .env ``` 3. Build the Docker image: ```bash docker build -t smartseason-backend . ``` 4. Run the Docker container (mapping port 8000 and feeding the environment file): ```bash docker run --env-file .env -p 8000:8000 smartseason-backend ``` *The Django backend will now be cleanly running at `127.0.0.1` via Gunicorn in a pristine Docker container without needing any local Python configuration!* ### Populating Test Data We have a custom management command to effortlessly populate realistic farm data: ```bash python manage.py seed_db ``` *This command intelligently gener …