AquaGrow API

AquaGrow is a Flask-based API that provides water usage recommendations for agricultural lands based on real-time weather data. The recommendations are generated using a machine learning model trained on historical weather data and crop-specific water usage patterns.

Features

• Fetch real-time weather data for any location.
• Generate water usage recommendations for five crops: Rice, Wheat, Beets, Corn, and Potatoes.
• API endpoint for health checks.

Getting Started

Prerequisites

• Python 3.7+
• Flask
• Requests
• Pandas
• Scikit-learn
• WeatherAPI key (you can sign up for an API key at WeatherAPI)

Installation

1. Clone the repository:

   git clone https://github.com/yourusername/aquagrow.git
   cd aquagrow

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the required packages:

   pip install -r requirements.txt