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One thing I noticed is Puppeteer’s resource consumption—it’s heavier compared to Scrapy. Plan your hardware needs if you’re using Puppeteer for large-scale scraping.

To avoid storing duplicate images, I check for existing files before saving new ones. This reduces redundancy and saves storage space.

For handling dynamic content, Puppeteer works better than Selenium due to its faster execution and support for headless browsers.

For dynamic blogs, I prefer Puppeteer because it ensures all JavaScript-rendered content, including author names and dates, is fully loaded before scraping.

Adding time-based intervals to capture updates ensures that I can collect scores periodically without overwhelming the server or missing key events.

To store the scraped data efficiently, I use a relational database like PostgreSQL. This makes it easy to query and analyze real estate trends.

Storing job listings in a structured database allows me to track trends over time and makes the data easy to analyze and filter.