Web Scraping

Here's the step-by-step I follow for a typical scrape — say, pulling product titles and prices from a category page:

1. Start with one page. I write a simple script using Python's requests and BeautifulSoup (or Node's axios and cheerio). I fetch the HTML, parse it, and extract the data using the selector I found earlier. I print it to the console first to verify it works.
2. Handle pagination. Most category pages have a "next" button or a page number in the URL. I look for the pattern — often ?page=2 — and loop through pages. I add a delay between requests (usually 2-5 seconds) to avoid hammering the server.
3. Store the output. I write the data to a CSV file. I keep it simple: headers like title, price, url. No databases yet. CSV is universal and I can open it in Excel or load it into a tool like Google Sheets.
4. Add error handling. Websites break. I wrap requests in try/except blocks, log failed URLs, and retry once after a longer delay. If a page returns a 403 or 429, I stop and check if I'm being blocked.
5. Scale carefully. Once the script works for 10 pages, I run it for 100. I monitor the response codes. If I see a pattern of 403s, I rotate user agents or use a proxy. But honestly, for most SEO tasks, you don't need thousands of pages — a few hundred is usually enough.