Automate Serpstat Data Collection With Python
Serpstat provides a Python guide for accessing the Serpstat API programmatically. Use it to automate keyword research, domain analysis, and backlink data collection from your own Python scripts — with ready-to-use code examples in Google Colab that show how to convert Serpstat's JSON API methods into working Python requests.
What you can achieve:
Automate recurring data collection: Schedule Python scripts to pull keyword rankings, domain metrics, or backlink data on a regular basis — no manual exports or interface logins required.
Build custom SEO tooling: Integrate Serpstat data into your own internal tools, dashboards, or data pipelines using Python as the connection layer.
Process large datasets efficiently: Use Python to query Serpstat API across hundreds of domains or keywords, handle pagination, and structure results for analysis or storage.
Getting Started
Go to your Serpstat account → Profile → generate and copy your API token. API access requires the Team plan or higher.
Open the Serpstat API Python Colab notebook — find the link in your Serpstat account or on the tutorial page. The notebook contains ready-to-use Python request examples for each API method.
In the Colab notebook, paste your API token into the designated cell.
Choose the API method you need (e.g. domain keywords, keyword selection, backlinks) and run the corresponding cell. The notebook shows both the JSON request structure and its Python equivalent.
Adapt the code for your own scripts — copy the relevant request function into your Python environment and modify parameters as needed.
What You Can Query
Domain analysis: Domain summary, keyword count, visibility, traffic estimates, domain history, top pages, and competitors — for any domain you pass to the API.
Keyword research: Keyword overview, related keywords, search suggestions, keyword selection, and top-100 SERP results — for any keyword or keyword list.
Backlink data: Backlink summary, referring domains, anchors, and backlink dynamics — for any domain or URL.
API credits per request: Each API method call consumes credits. The Colab notebook documents credit cost per method. Monitor your remaining credits via the API or in your Serpstat profile.
Pro Tip: Use Colab as a Low-Friction API Testing Environment
Google Colab is the fastest way to test Serpstat API calls before integrating them into production scripts.
Open the Serpstat Colab notebook and run a single API method cell with your token to verify authentication and see the raw JSON response structure.
Inspect the response keys and data types in Colab before writing your production parser — this prevents integration surprises with unexpected field names or nested structures.
Use Colab's built-in pandas integration to convert API responses to DataFrames directly in the notebook for quick analysis.
The goal: Validate your API logic interactively in Colab, then copy the working code into your scheduled Python job with confidence.
⚠️ Important: Serpstat API access requires the Team plan or higher. Each API method call consumes credits from your plan's API credit pool. Review the API documentation at serpstat.com/api to understand credit costs per method before running high-volume scripts. |
❓ Frequently Asked Questions
Q: Do I need to install anything to use the Colab notebook?
A: No installation needed — Google Colab runs in your browser. You need a Google account to save a copy of the notebook to your own Drive.
Q: Which Python version is required?
A: The Colab notebook uses standard Python 3 with the requests library, which is pre-installed in Colab. For local scripts, Python 3.7+ with requests installed is sufficient.
Q: Where is the full API reference?
A: The complete Serpstat API documentation, including all available methods, parameters, and response formats, is at serpstat.com/api.
Next Steps
Domain Batch Analysis — Use batch domain analysis inside Serpstat before automating it via the Python API.
Site Analysis — Overview — Understand the domain data available via the Serpstat API.
Keyword Research — Overview — Explore keyword research data you can pull programmatically.