Ghana-AMR-Surveillance-Center/data-standardizer

# 🏥 AMR Data Harmonizer **Advanced Data Processing & Standardization Platform for AMR Surveillance** A comprehensive platform designed to address critical data cleaning challenges in **Antimicrobial Resistance (AMR) surveillance** across African laboratories. This tool helps laboratories prepare their data for submission to global surveillance systems like GLASS and WHONET. ### Application Overview **App — Workflow Selection** *Main interface with sidebar navigation and workflow selection.* **App — Workflow Cards** *Choose Your Workflow: Standardize Single File, Merge Multiple Files (Recommended), and AMR Analytics.* **About Page** *Platform overview, challenges, solutions, and features with quick navigation.* ## 🚀 Quick Start ### Option 1: Streamlit Cloud Deployment (Recommended for Sharing) 1. Push your code to GitHub (this repository) 2. Go to share.streamlit.io 3. Connect your repository: `drmichaeladu/data-standardizer` 4. Set main file path: `app.py` 5. Click "Deploy" and wait for deployment to complete 6. Your app will be live at `your-app-name.streamlit.app` **Note**: For Streamlit Cloud, ensure your `requirements.txt` includes all dependencies. ### Option 2: Local Development Setup #### Windows (Easy Launch) ```bash # Double-click or run (starts in detached mode - works in all terminals): launch.bat # For interactive logs in CMD, use: launch.bat -f ``` #### Linux/macOS ```bash # Make scripts executable chmod +x deploy_production.sh scripts/deploy.sh # Run deployment script ./deploy_production.sh ``` ### Option 3: Manual Setup (Local) ```bash # 1. Create virtual environment python -m venv .venv # 2. Activate virtual environment # Windows: .venv\Scripts\activate # Linux/macOS: source .venv/bin/activate # 3. Install dependencies pip install -r requirements.txt # 4. Run application python run.py # OR for production mode: python run_production.py ``` ### Option 4: Docker Deployment ```bash # Build and run with Docker …