Stock Recommender Platform with Go, Vue, and CockroachDB
The Stock Recommender is a complete web application designed to simulate stock market data analysis and investment recommendations using scraped dummy data. The data for this platform was generated using a custom Go stock-worker, a separate lightweight service that scrapes dummy stock price data from predefined sources or static endpoints, mimicking real-world data scraping without relying on actual financial APIs. The backend, developed in Golang, provides a RESTful API using the net/http package to: Receive the scraped dummy data from the stock-worker Process price trends using configurable thresholds or percentage changes Generate simulated buy, sell, or hold recommendations CockroachDB, a distributed SQL database, is used to persist: Historical dummy stock price data Recommendation logs The frontend, built with Vue.js, delivers a reactive and user-friendly interface. It communicates with the Go API to: Display simulated real-time stock data Render interactive charts showing price movements Present clear recommendation indicators Key technologies include: Go REST API with dummy data processing CockroachDB for distributed, fault-tolerant storage Vue.js SPA for visualization and interaction Axios for API requests A custom Go stock-worker for scraping and populating dummy data The system follows a modular and scalable architecture: Stock-Worker (Go): Scrapes dummy stock data to feed the system Backend (Go): Processes data and generates recommendations Frontend (Vue.js): Displays results and visualizations Database (CockroachDB): Persists simulated price history and recommendations While based on dummy data, the project realistically demonstrates full-stack integration, system communication, and investment logic simulation, making it a strong foundation for future enhancements like live data integration or advanced analytics.
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