Se-ranking Python API Docs | dltHub

SE Ranking is an SEO and digital marketing platform offering a Data API to retrieve SEO metrics, project data, backlinks, domain analysis, keyword data and more. The REST API base URL is https://api.seranking.com and All requests require an API key (Token) via Authorization header or apikey query parameter.

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Se-ranking data in under 10 minutes.

---

What data can I load from Se-ranking?

Here are some of the endpoints you can load from Se-ranking:

---

How do I authenticate with the Se-ranking API?

Generate a Data API key in your SE Ranking account (Settings -> API or API dashboard). Include it in requests with header 'Authorization: Token YOUR_API_KEY' (recommended) or as a query parameter 'apikey=YOUR_API_KEY'.

1. Get your credentials

1. Log into your SE Ranking account.
2. Go to Settings -> API or open the API Dashboard (online.seranking.com/admin.api.dashboard.html).
3. Click 'Create API key' or 'Generate API Key'.
4. Choose 'Data' type, name the key and create it.
5. Copy the generated key and store it securely; use it as 'Authorization: Token YOUR_API_KEY' or as 'apikey' query parameter.

2. Add them to .dlt/secrets.toml

Copy
[sources.se_ranking_source]
api_key = "your_api_key_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

Copy
dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Se-ranking API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

Copy
python se_ranking_pipeline.py

If everything is configured correctly, you'll see output like this:

Copy
Pipeline se_ranking_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset se_ranking_data
The duckdb destination used duckdb:/se_ranking.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline se_ranking_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

---

Python pipeline example

This example loads sites and backlinks from the Se-ranking API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def se_ranking_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.seranking.com",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "sites", "endpoint": {"path": "sites"}},
            {"name": "backlinks", "endpoint": {"path": "v1/backlinks/list", "data_selector": "backlinks"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="se_ranking_pipeline",
        destination="duckdb",
        dataset_name="se_ranking_data",
    )
    load_info = pipeline.run(se_ranking_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

---

How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

Copy
import dlt

data = dlt.pipeline("se_ranking_pipeline").dataset()
sessions_df = data.sites.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM se_ranking_data.sites LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("se_ranking_pipeline").dataset()
data.sites.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Se-ranking data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

---

Troubleshooting

Authentication failures

If the API returns 403 with message 'No token' or 'Incorrect token', confirm your API key is correct and passed either as 'Authorization: Token YOUR_API_KEY' header or 'apikey' query parameter. Test with GET /v1/account/subscription which returns 200 OK if the key is valid.

Rate limits and throttling

SE Ranking limits requests to 5 calls per second per API method. Exceeding the limit returns HTTP 429 Too Many Requests and a message indicating you should slow down; repeated abuse can lead to temporary blocking (e.g., 10 minutes or longer).

Error responses

API returns HTTP 4xx/5xx with a JSON body containing an error message. Common codes: 400 Bad Request (invalid format), 403 No token/Incorrect token/No access/Access denied, 404 Not Found, 429 Too Many Requests, 500 Server error.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

---

Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

Copy
dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack