How I Built an SEO Rank Tracking System Using Python and SERP API

August 27, 2026

I run a small SaaS and I wanted to track my keyword rankings.

I didn't want to pay $100/month for an SEO tool that I'd only use for one thing.

So I decided to build my own rank tracker.

The first version was a scraper. It worked for a week. Then Google changed something and everything broke.

This is the story of how I rebuilt it properly — using Python and a SERP API — and ended up with a system that can scale to thousands of keywords.

I'm sharing the code and architecture so you can build your own.

The Problem

I needed to track rankings for about 200 keywords across 3 websites.

My first attempt was a simple Python script using requests and BeautifulSoup.

Here's what happened:

Week 1: It worked perfectly.

Week 2: Google changed their HTML layout. My parser stopped working.

Week 3: I fixed the parser. Then I hit CAPTCHAs.

Week 4: I added proxies. Then I realized search results differ by location.

Week 5: I gave up and started looking for a better solution.

The Solution

I switched to a SERP API approach.

Instead of scraping Google, I send structured requests and receive structured JSON:

python

import os import requests API_TOKEN = os.getenv("TALOR_API_TOKEN") API_URL = "https://serpapi.talordata.net/serp/v1/request" def google_search(keyword): headers = {"Authorization": f"Bearer {API_TOKEN}"} payload = {"engine": "google", "q": keyword} response = requests.post(API_URL, headers=headers, json=payload) return response.json()

That's it. No proxies. No parser maintenance. No headaches.

The Architecture

Here's the entire system architecture:

text

Keyword List ↓ SERP API Collector ↓ Ranking Processor ↓ Database ↓ SEO Dashboard

Keyword List: The keywords you want to track. Stored in JSON or database.

SERP API Collector: The code above. Returns structured search results.

Ranking Processor: Extracts ranking positions from the results.

Database: Stores historical data.

SEO Dashboard: Displays charts and reports.

Finding Rankings

The core logic is simple:

python

def find_position(results, domain): organic = results.get("organic_results", []) for item in organic: if domain in item["link"]: return item["position"] return None

Tracking Multiple Keywords

python

keywords = [ "python serp api", "google search api", "seo automation" ] for keyword in keywords: results = google_search(keyword) position = find_position(results, "example.com") print(f"{keyword}: {position}")