Recipe Suggestion System 🥕

This project is a Recipe Suggestion System that allows users to search for recipes based on various criteria such as keywords, ingredients, or categories. It utilizes Flask, JavaScript, Jinja templates, MongoDB, and BeautifulSoup for web scraping.

Overview

The Recipe Suggestion System provides users with a platform to discover and explore recipes. Users can search for recipes using keywords, ingredients, or categories, and view detailed recipe information including ingredients, instructions, and images. The system utilizes MongoDB to store user data, recipes, and user preferences, and performs web scraping with BeautifulSoup to populate the recipe database.

Features

• Recipe searching by keywords, ingredients, or categories.
• Detailed recipe pages with ingredients, instructions, and images.
• MongoDB for storing user data, recipes, and user preferences.
• Web scraping with BeautifulSoup to populate the recipe database.

Prerequisites 📒

Before you begin, ensure you have met the following requirements:

• Python 3.x installed.
• MongoDB installed and running.
• Basic knowledge of Flask, Python, JavaScript, MongoDB, BeautifulSoup, HTML, CSS, Bootstrap.

Tech Stack👨‍💻

Frontend:

• Flask
• HTML, CSS, Bootstrap
• JavaScript

Backend:

• MongoDB
• JavaScript

Contributing 🍴

Contributions are welcome! If you want to contribute to this project, please follow these steps:

1. Fork the repository.
2. Create a new branch for your feature or bug fix: git checkout -b feature/your-feature-name.
3. Make your changes and commit them with clear, concise commit messages.
4. Push your changes to your fork: git push origin feature/your-feature-name.
5. Create a pull request to merge your changes into the main repository.