Chronological Memory Explorer

Inspired by the non-linear storytelling of 'Memento' and the complex worlds of 'Hyperion', this project delves into the temporal dynamics of e-commerce pricing. The core idea is to build a data scraper that collects historical pricing data for specific products or product categories from various online retailers. Instead of a simple price tracker, the focus is on understanding how prices fluctuate, exhibit seasonality, or respond to external events over extended periods. The 'Memento' influence comes into play by treating the pricing data as fragmented pieces of a timeline, which the data science component then reconstructs and analyzes to reveal hidden patterns. 'Hyperion''s vastness inspires the potential for exploring niche markets or complex product ecosystems. The scraper will collect data points like price, date, time, and source URL. The data science aspect will involve time series analysis, anomaly detection (identifying unusual price spikes or drops), and potentially predictive modeling to forecast future price movements based on historical trends. The 'niche' aspect lies in focusing on specific product categories often overlooked by general price trackers (e.g., rare collectibles, vintage electronics, specialized craft supplies). The 'low-cost' implementation involves utilizing readily available Python libraries for web scraping (like BeautifulSoup and Scrapy) and data analysis (like Pandas and SciPy). The 'high earning potential' stems from offering this specialized historical pricing intelligence as a service to collectors, resellers, investors, or even businesses looking to understand market dynamics for their specific niche. The output could be detailed reports, dashboards, or even an API providing real-time historical trend analysis for a subscription fee.