SERP Rank Tracker in Python — Track Google Positions Over Time

A minimal but honest keyword rank tracker: query Google through a SERP API, find your domain's position for each keyword, append to CSV, alert on movement. No Search Console lag, no per-seat SaaS pricing — a script and a cron job.

Find your position for one keyword

import requests

resp = requests.post(
    "https://app.quantumproxies.io/api/v1/scraper/serp",
    headers={"Authorization": "Bearer qp_live_YOUR_KEY"},
    json={"query": "residential proxies", "engine": "google", "country": "us", "num": 20},
)

for hit in resp.json()["organic"]:
    if "yourdomain.com" in hit["link"]:
        print(f'rank {hit["rank"]}: {hit["title"]}')
        break
else:
    print("not in top 20")

Why scraped ranks ≠ your browser's ranks

Your logged-in browser gets personalized, geo-biased results. Rank tracking needs neutral, per-country SERPs — which is exactly what the API returns: each query exits from a clean residential IP in the target country with no cookie history. Track country="us" and country="de" separately; they genuinely differ.

The full tracker

rank_tracker.py:

• keywords.txt — one keyword per line
• appends date, keyword, country, rank, url to ranks.csv
• prints ▲/▼ movement vs. the previous run

QP_API_KEY=qp_live_... DOMAIN=yourdomain.com python rank_tracker.py

Run it daily from cron/GitHub Actions and ranks.csv becomes your position history — plot it with anything.

Cost model

Rank tracking is bursty: 50 keywords × 2 countries × daily = ~3,000 searches/month. Per-search pricing (no monthly tier) is what makes a DIY tracker cheaper than rank-tracker SaaS. Searches run on the QuantumProxies SERP API — Google/Bing/DuckDuckGo as JSON, docs here, keys at app.quantumproxies.io/api-keys.