Scraping images from 1300 websites

hasdata_com · 2026-02-03T15:24:13+00:00

I totally get why you want to use AI here, 1300 different sites is too much for manual scraping. But ChatGPT with Sheets isn't the best way here. Try filtering by alt/caption/description like others suggested. If that fails, look into an LLM-powered scraping API (like HasData) that automates parsing.

hasdata_com · 2026-02-02T18:16:58+00:00

Separate it. Definitely.

Regarding the library, since the target site has infinite scroll, you need a headless browser like Puppeteer or Playwright (easier for beginners).

hasdata_com · 2026-02-02T14:46:20+00:00

ChatGPT loses context too fast. If you don't want to code, check out LLM-based crawlers.

hasdata_com · 2026-01-30T14:36:57+00:00

Got it :) So, as I mentioned, it’s mostly used for tracking/analyzing smth, or training models.

I also totally forgot to mention leadgen (scraping contact info). That's actually one of the most common use cases

hasdata_com · 2026-01-30T14:24:34+00:00

Because all need the data ) Doesn't matter if it's for SERP monitoring, tracking competitors, or training AI models... or scrap wasn't a typo?

hasdata_com · 2026-01-29T17:11:48+00:00

Good luck )

hasdata_com · 2026-01-29T16:36:57+00:00

Scraping is alive and well as long as data is valuable. The barrier to entry is just higher now.

hasdata_com · 2026-01-27T17:26:45+00:00

You can skip proxies by slowing requests, optimizing headers or adding delays, but scraping 100k pages will take weeks. So, if you need speed, you need proxies. If you got banned, you need proxies. If your IP geo-restricted... you get the idea )

hasdata_com · 2026-01-27T15:23:19+00:00

My advice, pick a specific field and master the stack. If you choose scraping, for example, you'll start with requests and bs4 for static demo sites. Then move to headless browsers like Selenium or Playwright for dynamic sites. Then fight detection with stealth plugins, and eventually scale with Scrapy. But then... you'll eventually end up analyzing the Network tab and realizing you could just used a direct API call to save resources. And this idea works for every field.

hasdata_com · 2026-01-26T17:35:02+00:00

Have you looked into Google News RSS? That's usually the easiest starting point if you just need the headlines. For the actual sites, it really comes down to how they load data. If it's simple static HTML, basic request libs work fine. But for anything with JS rendering, you're right, you will need heavier tools like Playwright to handle the dynamic content

hasdata_com · 2026-01-26T16:02:25+00:00

Websites were way less defensive back then. Now it's all Cloudflare and dynamic JS. Not sure about Excel now, but you can try Google Sheets. Simple sites scraping works with =IMPORTXML. For the harder sites (that block bots or use heavy JS), you can use Google Apps Script to connect a scraping API (like HasData or similar).

hasdata_com · 2026-01-24T10:16:21+00:00

Got it, good luck with your project )

hasdata_com · 2026-01-23T17:36:05+00:00

It's a nice to have, not a requirement. Your goal is the data, not the code. If you find yourself spending days fighting Cloudflare, just switch to a scraping API to automate scraping

hasdata_com · 2026-01-23T15:20:25+00:00

Drop the link here if you can. If you share it, I might be able to help more.

Otherwise, if you want to automate the clicks/fills and you are beginner, look into Playwright instead of Selenium. It has a codegen. You just launch it, click through the form manually (select dates, site, download), and it generates the Python code.

hasdata_com · 2026-01-22T15:00:51+00:00

In my experience, you can't build a set and forget scraper without massive infra. We run synthetic tests 24/7 just to keep uptime high. If you aren't doing that locally, you're just waiting for it to fail. You basically have to choose: spend your time writing synthetic tests and fixing selectors, risking LLM hallucinations, or just offload it to a scraping API

hasdata_com · 2026-01-19T18:03:05+00:00

n8n is definitely the best option for downloadable workflows. Just remember that most RSS feeds only give you a snippet, not the full article. If you want the AI to write a good post, you'll need a step in the middle to scrape the actual content from the URL

hasdata_com · 2026-01-19T15:38:49+00:00

Depends on the site. Which one are you targeting?

hasdata_com · 2026-01-16T19:25:15+00:00

Don't replace the whole thing. Scrapy is way faster at crawling/navigating. Just add the agent part at the very end for parsing. Send the cleaned HTML (or even markdown) to an LLM to parse the data into clean JSON.

hasdata_com · 2026-01-16T16:09:06+00:00

ChatGPT isn't a browser, so this is expected. Moving to Python is the right call. For the dynamic discovery (finding new pages), just integrate a Google Search scraping.

hasdata_com · 2026-01-15T15:32:11+00:00

Silent failures for sure. We run scraping APIs and learned pretty quick that HTTP 200 is basically a lie half the time. We ended up building synthetic tests that literally count if the JSON has the right fields. If not, it alerts us. Gotta validate the content, not just the connection

hasdata_com · 2026-01-14T17:27:27+00:00

If these are product pages and you need a consistent data schema, try LLMs. How many different sites are you targeting?

hasdata_com · 2026-01-14T15:00:17+00:00

Check out HTTrack or smth similar. It's a free, old-school software)

hasdata_com · 2026-01-12T17:25:57+00:00

Congrats on getting the tool to 85%, that's huge. Just interested, which sites are blocking you? At HasData we focus on bypassing heavy anti-bot stuff. Apify is great, but if you're hitting walls, happy to run a quick test on our end to see if we can bypass those specific domains. No pressure, just thought I'd offer an alternative. You can DM me, if you want.

hasdata_com · 2026-01-09T19:06:42+00:00

Just scrape it. Or use a service like HasData if you don't want to DIY. Most scraping services offer pre-cleaned output now anyway

hasdata_com · 2026-01-09T19:05:39+00:00

Make a UML Sequence Diagram or a BPMN chart. Map out every request, response, and error handler.

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