Saving product data in a local SQLite database allows for easy querying, particularly for high-demand categories like electronics.

• Extracting star ratings along with text comments helps me correlate positive or negative sentiment with specific aspects of the product.

Engaging with the site’s support or developer team can sometimes provide more guidance on how best to scrape or gather data.

If the site offers an API with price data, using it is preferable, as APIs are often more stable and intended for data retrieval.

• Some sites provide inventory information in JSON, accessible via network requests. Pulling this data directly is often more accurate than HTML scraping.

Spectrogram analysis can reveal patterns in audio for specific tasks, though it requires more advanced machine learning techniques.

Randomizing headers and proxies helps reduce detection when accessing popular auctions, particularly for high-value items.

Organizing items by genre, like books, games, or electronics, keeps data structured and enables targeted trend analysis.

Randomizing user-agents and rotating proxies helps prevent IP bans, especially on high-traffic sections of DMM.com.