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• For video data, frame extraction at specific intervals allows me to capture key visual elements without processing every frame.

Scheduling periodic scrapes enables tracking auction trends, such as price changes as auctions near their end time.

• Randomized delays and IP rotation help reduce detection when frequently accessing popular product listings.

• Organizing rentals by genre or product type makes the data more useful for analysis, allowing me to identify trending items.

• With Rust’s Actix framework, I can manage concurrent requests efficiently, capturing multiple flight routes in a single run.

If API endpoints are accessible through network requests, mimic them directly, which can be faster than scraping HTML.

By setting my scraper to check prices daily, I capture fluctuations in rates for hotels, flights, and activities, especially during peak seasons.

Tracking both ratings and reviews on each platform reveals which gadgets have high satisfaction rates, helping identify quality products.

• By comparing prices and availability across both platforms, I get a clearer picture of consumer preferences and pricing strategies.

• By setting up periodic scrapes for listings by zip code, I capture price changes over time, which is useful for forecasting trends.