Scraping From One IP: Captchas, Rate Limits and Collection That Stalls Halfway

You launch a scraper, the first few hundred rows come in fine, and then the familiar picture begins. The site serves a captcha instead of data, then answers with a 429 «too many requests», and a couple of minutes later your address gets banned outright. The reason is singular: the whole bulk collection runs from one IP, and the target sees an unnatural stream of hits from a single point.

The frustrating part is that collection stalls exactly halfway. Half the product cards are exported, half are missing, and the output table is incomplete and useless for analysis. The bigger the job, the faster one address hits the limits, and the more often you have to manually restart the process from where it broke off.

How work changes with a proxy pool and rotation

The core idea is to spread the load. Instead of hammering thousands of requests at one address, you take a proxy pool and distribute the hits across many IPs. Rotation swaps in a fresh address on a schedule or per request, so load never piles up on a single point. To the site this looks like traffic from many different visitors rather than one aggressive bot — captchas drop noticeably, and collection no longer stalls midway.

Integration is simple and familiar. Proxies are provided as IP:PORT (or host:port:login:password) and plug into any tool: requests and Scrapy in Python, Puppeteer and Playwright for headless browsers, A-Parser for ready-made presets. HTTP(S) support fits ordinary API and HTML requests, while SOCKS5 covers cases that need a low-level tunnel and work beyond plain HTTP. You feed the address list into the settings once.

Threads handle the speed. With a pool in place you can raise dozens of parallel threads, each running through its own address. A job that would drag on for hours from a single IP — and still hit a ban — splits into many independent branches. A sensible pause between requests plus rotation gives steady collection: even if one address slows down somewhere, the rest keep pulling data. In Scrapy this is tuned through middleware and concurrency settings, in a custom scraper through an address pool and a task queue. The logic stays the same: you do not push one thread faster at any cost, you widen the collection sideways.

Where to get proxies for scraping

WinGate provides addresses tuned for data collection. A rotating pool, HTTP and SOCKS5 support, the familiar IP:PORT format and multi-threaded work — everything a scraper needs to see fewer captchas and stop losing collected data halfway. The proxies connect to Python, Scrapy, Puppeteer and A-Parser without complex setup. Before committing to volume, it is sensible to run a free test on your own real task and watch how the target site behaves.

Details and setup are on the WinGate parsing proxy page.