Cphorm

🧬 Cphorm

A lightweight, offline-first health data collection and synchronization platform designed for field workers, researchers, and organizations working in connectivity-challenged regions.

🚀 Key Features

• Dynamic form creation - selecting your own parameters

• Offline data entry & syncing when online

• Clean web dashboard for accessing data, viewing submissions & regional health patterns

• Role-based access (enumerators, reviewers)

🛠️ Tech Stack

• Frontend: React / Next.js / Tailwind CSS

• Backend: Flask / Node.js /

• Database: Mongo DB

• Data Pipeline: Pandas

📦 Folder Structure

/Cphorm
├── form/
│   ├── back-end/
│   │   ├── app/
│   │   │   ├── __init__.py
│   │   │   ├── models.py
│   │   │   ├── routes.py
│   │   │   └── utils.py
│   │   ├── tests/
│   │   │   └── test_api.py
│   │   └── requirements.txt
│   └── front-end/
│       ├── components/
│       │   ├── FormBuilder.jsx
│       │   ├── Dashboard.jsx
│       │   └── Navbar.jsx
│       ├── pages/
│       │   ├── index.jsx
│       │   └── dashboard.jsx
│       ├── public/
│       │   └── favicon.ico
│       ├── styles/
│       │   └── globals.css
│       ├── utils/
│       │   └── api.js
│       └── package.json
├── platform/
│   ├── analytics/
│   │   ├── src/
│   │   │   └── data_generation.py
│   │   ├── tests/
│   │   │   └── test_analytics.py
│   │   ├── notebooks/
│   │   │   └── main.ipynb
│   │   └── __init__.py
│   └── dashboard/
│       ├── components/
│       │   └── Chart.js
│       └── app.py
├── utils/
│   └── helpers.py
├── docs/
│   └── architecture.md
└── README.md

Prerequisites

• Python 3.10+
  (Required for analytics, data generation, and backend scripts)
• Node.js (Recommended v18+ for frontend)
• pip (Python package manager)
• npm or yarn (Node.js package manager)
• MongoDB (for backend database)
• [Optional] Docker (for containerized deployment)

Setup

git clone https://github.com/STACK-42/Cphorm.git
cd cphorm

Then follow setup steps for /frontend and /backend in their respective READMEs.

📊 Use Cases

• Health survey campaigns

• Rapid response to humanitarian crises (by detecting patterns early)

• Offline-first data collection in rural areas