Develop a minimalistic, data-driven e-commerce application using Streamlit. This project integrates three databases — MongoDB, Redis, and Neo4j — each responsible for a specific aspect of the app:
- MongoDB: Product and purchase data storage
- Redis: Shopping cart functionality and caching
- Neo4j: Graph-based product recommendations
All components are connected using Python, with a Streamlit-based UI for visualization.
- Stores product information.
- Loads product data into the app.
- Saves purchase data after checkout.
- Models product relationships as a graph.
- Generates product recommendations using Cypher queries.
- Stores shopping cart data temporarily.
- Caches recommendations to improve performance.
- Serves as the glue between all components.
- Interfaces with databases and provides recommendation endpoints.
This guide helps you set up and run a Streamlit-based e-commerce app with a multi-database backend. While a production-grade application would include a full API layer, this MVP focuses on visualizing the system via Streamlit for faster feedback and iteration.
Make sure you have the following installed:
- Python 3.x
- Python packages:
streamlit,pymongo,redis,neo4j,pandas - Local installations of MongoDB, Redis, and Neo4j (or use cloud versions like MongoDB Atlas, Redis Cloud, and Neo4j AuraDB)
git clone https://github.com/your-username/e_commerce_app.git
cd e_commerce_apppip install -r requirements.txt
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