PlantPal - Houseplant Identification & Care Guide

PlantPal is a web-based application that helps users identify common houseplants and provides detailed care instructions. The application focuses on 50-100 common houseplants with comprehensive care tips.

Features

• Plant Identification: Search for plants by name, scientific name, or description

• Detailed Care Information: Each plant comes with specific care instructions including:

  • Light requirements
  • Watering schedule
  • Soil type recommendations
  • Humidity needs
  • Temperature preferences
  • Fertilizing guidelines
  • Difficulty level
  • Toxicity information

• Filtering System: Find plants that match your specific needs:

  • Light conditions (low light, bright indirect, direct sun)
  • Experience level (beginner, intermediate, advanced)
  • Pet friendliness (toxic vs non-toxic)

• Categorized Browsing: Browse plants by categories such as:

  • Low Light
  • Pet Friendly
  • Air Purifying
  • Drought Tolerant
  • And more

Technology Stack

• Backend: Python with Flask framework
• Database: PostgreSQL
• ORM: SQLAlchemy
• Frontend: HTML, CSS, JavaScript
• CSS Framework: Bootstrap (Replit dark theme)
• Icons: Font Awesome

Getting Started

Prerequisites

• Python 3.11
• PostgreSQL database

Installation

1. Clone the repository:

git clone <repository-url>

2. Install the required dependencies:

pip install -r requirements.txt

3. Set up the environment variables:

DATABASE_URL=postgresql://<username>:<password>@<host>:<port>/<database>
SESSION_SECRET=<your-secret-key>

4. Initialize the database with seed data:

python seed_data.py

5. Run the application:

python main.py

The application will be available at http://localhost:5000.

Database Schema

The application uses two main models:

1. Plant: Stores information about individual plants

   • Basic details (name, scientific name, description, image URL)
   • Care information (light, water, soil, etc.)
   • Difficulty and toxicity

2. Category: Represents plant categories

   • Name and description
   • Many-to-many relationship with plants

Project Structure

• app.py: Flask application configuration
• main.py: Application entry point
• models.py: Database models (Plant, Category)
• routes.py: Route definitions for all pages
• seed_data.py: Script to populate the database with initial plant data
• static/: Static assets (CSS, JavaScript, images)
• templates/: HTML templates for all pages

Future Enhancements

• User accounts for saving favorite plants
• Plant problem diagnosis
• Watering reminder functionality
• Plant growth tracking
• Community plant care tips
• Image-based plant identification

License

This project is licensed under the MIT License - see the LICENSE file for details.