Use cases
Collect training data at scale without watching the meter
Very high volume at the lowest cost per GB
What gets in the way
Three things that break this workload
Corpus runs move terabytes and the per-GB rate is the whole budget.
Plan rates fall as the commitment grows, and past the top published allowance the rate is quoted against your actual volume.
A crawler that fails quietly poisons the dataset.
Usage alerts at 50%, 80% and 100% from Growth up flag a run that is suddenly burning traffic, and a fresh session ID moves a failing worker onto a new exit.
Pipelines need to read usage without a human opening a dashboard.
Sub-users with their own GB limits keep each pipeline on a fixed budget, and usage alerts by email flag the one that is running through it.
In practice
What the request looks like
Targeting goes in the username string, so there is no SDK and nothing to install.
# Rotating exit per request, unlimited concurrency.
import asyncio, httpx
PROXY = "http://user-country-us:YOUR_PASSWORD@gw.foidpro.xyz:7000"
async def fetch(client, url):
r = await client.get(url, timeout=30)
return url, r.status_code, len(r.text)
async def main(urls):
async with httpx.AsyncClient(proxy=PROXY) as client:
return await asyncio.gather(*(fetch(client, u) for u in urls))Why people trust it
The parts that are not marketing
Cancel or pause anytime
One click in the dashboard. No retention call, and no contract to see out.
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