Proxy | ScrapeRouter

A proxy is an intermediary server that sends requests on your behalf, so the target site sees the proxy IP instead of yours. In scraping, proxies are mainly used to reduce IP-based blocking, spread traffic, and make requests appear from specific networks or countries, but proxies alone do not solve rendering, fingerprinting, or rate-limit problems.

Examples

A basic example: instead of hitting a site directly from your server, you route the request through a proxy.

curl -x http://proxy-user:proxy-pass@proxy.example.com:8000 https://httpbin.org/ip

In Python with requests:

import requests

proxies = {
    "http": "http://proxy-user:proxy-pass@proxy.example.com:8000",
    "https": "http://proxy-user:proxy-pass@proxy.example.com:8000",
}

resp = requests.get("https://httpbin.org/ip", proxies=proxies, timeout=30)
print(resp.text)

What this changes in practice: - Without a proxy: the target sees your server IP - With a proxy: the target sees the proxy IP - With a proxy pool: each request may leave from a different IP or network

Practical tips

Treat proxies as one layer, not the whole system: they help with IP reputation and geography, but they will not fix bad request patterns, obvious bot fingerprints, or broken session handling.
Match proxy type to the job: datacenter for cheap high-volume work, residential for tougher targets, mobile for a small set of very protected flows where cost is justified.
Expect variance: some proxy IPs are slow, burned, or already blocked. This is normal. Build retry logic, health checks, and provider failover.
Watch the real metrics: success rate, median latency, cost per successful page, block rate, CAPTCHA rate.
Rotate carefully: rotating every request can help on some targets and break sessions on others. If the site expects a stable user journey, keep the same IP for that session.
Use country targeting only when it matters: localized pricing, region-locked content, compliance pages. Otherwise you're often paying extra for no reason.
Don't overbuy before you need it: a lot of teams jump into expensive residential proxies when the real issue is bad concurrency, no backoff, or no browser automation.
If you're juggling multiple proxy vendors, that's usually the point where a router layer starts making sense: fewer hardcoded integrations, easier failover, less time wasted swapping providers around.

Use cases

Avoiding IP bans during scraping: spread requests across multiple IPs instead of hammering a target from one machine.
Accessing geo-specific pages: check search results, product pricing, or availability from the US, UK, Germany, and so on.
Running account or session-based flows: keep one proxy attached to one session so the traffic looks consistent.
Collecting data from protected sites: use residential or mobile proxies when datacenter IPs get blocked immediately.
Building redundancy into production scrapers: route traffic across multiple providers so one vendor outage does not take your pipeline down.
Separating workloads by difficulty and cost: easy targets on cheap datacenter proxies, harder ones on residential, and only escalate when the cheaper path stops working.