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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