FarmIQ is a data-driven solution designed to help farmers make better decisions related to crop health, water management, and yield quality using NASA MERRA-2 satellite data.

• Prerequisites
• Installation
• Running the Application Locally
• Running the Application with Docker
• Folder Structure
• License

Before you begin, ensure you have the following installed on your local machine:

• Python 3.8+ (Download Python)
• pip (Python package installer, comes with Python)
• Git (Download Git)
• Docker (Install Docker) required if running with Docker

git clone https://github.com/tramya16/nasa_hackathon.git
cd nasa_hackathon

# Set up a virtual environment (optional but recommended)
python3 -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

# Install the required Python packages
pip install -r requirements.txt

To run the application without Docker:

1. Ensure all dependencies are installed via requirements.txt.
2. Run the Flask app:

   export FLASK_APP=app.py   # On Windows: set FLASK_APP=app.py
   flask run

The app should now be running on http://127.0.0.1:8080/.

To run the application using Docker:

In the project directory (where your Dockerfile is located), run the following command to build the Docker image:

docker build -t flask-app .

Once the image is built, you can run the application inside a Docker container:

docker run -d -p 8081:8080 flask-app

• -d: Runs the container in detached mode (in the background).
• -p 8081:8080: Maps port 8000 on your machine to port 8081 in the container, allowing you to access the Flask app via http://localhost:8081.

The Flask app should be accessible at http://localhost:8081/.

To stop the running container, first find the container ID by using:

docker ps

Then, stop the container with:

docker stop <container-id>

To view the logs from your Docker container, use the following command:

docker logs <container-id>

nasa_hackathon/
│
├── app.py                     # Main Flask application
├── templates/                 # HTML templates for Flask
├── static/                    # Static assets (CSS, JS, images)
├── Dockerfile                 # Docker configuration file
├── combined_europe_data_Test1.zip   # Example of large file
├── requirements.txt           # Python dependencies
├── README.md                  # Project documentation
└── .gitattributes             # Git LFS tracked files configuration