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Cphorm

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🧬 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

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