Stonk Ticker

Project: Stonk Ticker - Reddit Sentiment Analyzer
Role: Solo Developer

Overview

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Stonk Ticker is a tool designed to analyze stock sentiment by scraping the /r/wallstbets subreddit. It aggregates mentions of stocks, correlates them with real-time data from the unofficial Yahoo Finance API, and displays insights through an interactive front-end. Built with a Ruby/Python back-end and a React front-end, the project employs Redis for caching API responses and the Interface pattern to bridge Ruby and Python components using JSON messaging. This project demonstrates my ability to integrate diverse technologies into a cohesive, high-performance application.

Challenges and Objectives

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• Reddit Scraping: Implementing a scraper to parse stock mentions from Reddit posts while handling rate limits and evolving subreddit content.
• Real-Time Data Correlation: Integrating the Yahoo Finance API to provide up-to-date stock data, overcoming API inconsistencies.
• Cross-Language Integration: Using the Interface pattern and JSON messaging to connect Ruby and Python components seamlessly.
• Interactive Front-End: Creating a user-friendly interface to visualize stock mentions and corresponding financial data.

My Contributions

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1. Back-End Development

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• Developed the core scraper in Ruby, aggregating stock mentions from /r/wallstbets posts and comments.
• Built a Python service to interface with the Yahoo Finance API, enabling real-time stock data retrieval.
• Used the Interface pattern with JSON messaging to connect Ruby and Python services for streamlined communication.

2. Front-End Development

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• Built the front-end in React, enabling users to explore aggregated stock mentions alongside real-time price, volume, and sentiment data.
• Designed sortable lists and visualizations to highlight trending stocks and patterns.

3. Caching and Optimization

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• Integrated Redis to cache Yahoo Finance API responses, mitigating the impact of inconsistent data retrieval and improving reliability.
• Optimized data processing pipelines to handle large data volumes without significant performance degradation.

4. Integration and Automation

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• Automated the Reddit scraping and data analysis pipeline to provide near-real-time updates.
• Established deployment pipelines to streamline updates and ensure minimal downtime during iterations.

Outcomes and Results

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• Insightful Analytics: Delivered a platform capable of analyzing sentiment trends and identifying popular stocks from Reddit chatter.
• Optimized Performance: Successfully mitigated unreliable API response times with Redis, ensuring a seamless user experience.
• Cross-Language Solution: Demonstrated proficiency in integrating Ruby and Python components into a unified application.

Reflection

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Stonk Ticker was a challenging but rewarding project that honed my skills in full-stack development, cross-language integration, and API optimization. This experience deepened my understanding of caching strategies and real-time data visualization, preparing me for larger-scale projects with complex data pipelines.

Technical Summary

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• Skills: Full-Stack Development, Data Scraping, Cross-Language Integration, API Optimization, Real-Time Data Visualization
• Tools: Ruby, Python, React, Redis, Yahoo Finance API
• Specialized Tasks: Reddit Scraping, API Caching, Stock Sentiment Analysis, Data Pipeline Optimization

Repositories

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Front-End

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Back-End

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