Short.io Python API Docs | dltHub

Short.io is a URL shortening and link management platform with an API for creating, listing, and managing short links, domains, and link statistics. The REST API base URL is https://api.short.io and All requests require an API key sent in the Authorization header..

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 Short.io data in under 10 minutes.

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What data can I load from Short.io?

Here are some of the endpoints you can load from Short.io:

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How do I authenticate with the Short.io API?

Short.io uses API keys. Send your API key in the Authorization HTTP header for every request (Authorization: ). The API key is created from the Integrations & API → API menu in the Short.io dashboard.

1. Get your credentials

1. Log in to your Short.io account.
2. Go to Integrations & API → API.
3. Click "Create API key".
4. Choose key type (Public or Private), optionally set description, expiration, and access restrictions (All domains / restrict to team / restrict to domain).
5. Create and copy the API key – this is the only time you can view the secret.

2. Add them to .dlt/secrets.toml

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[sources.short_io_source]
api_key = "your_shortio_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.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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

1. Install the dlt AI Workbench:

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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:

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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 Short.io 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:

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python short_io_pipeline.py

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

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

Inspect your pipeline and data:

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dlt pipeline short_io_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.

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Python pipeline example

This example loads links and domains from the Short.io API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def short_io_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.short.io",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "links", "endpoint": {"path": "links", "data_selector": "links"}},
            {"name": "domains", "endpoint": {"path": "api/domains", "data_selector": "domains"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="short_io_pipeline",
        destination="duckdb",
        dataset_name="short_io_data",
    )
    load_info = pipeline.run(short_io_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.

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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):

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import dlt

data = dlt.pipeline("short_io_pipeline").dataset()
sessions_df = data.links.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM short_io_data.links LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("short_io_pipeline").dataset()
data.links.df().head()

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

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What destinations can I load Short.io 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.

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Troubleshooting

Authentication failures

If you receive 401/403 errors, verify that the Authorization header contains the correct API key (Authorization: ). API keys can only be viewed once when created — if lost, create a new key in Integrations & API → API.

Rate limits and request limits

Short.io enforces a request rate limit (documented as 20‑50 RPS). Exceeding limits may result in 429 responses. The API also limits link‑creation throughput: you can create up to 1000 links per API call but calls may be rate‑limited (1 API call per ~5 seconds for bulk creation in some contexts). Implement exponential backoff and respect 429 Retry‑After headers.

Pagination quirks

List endpoints use limit and offset query parameters. Ensure you iterate by offset + limit until you receive an empty list. Some list responses return arrays under keys such as links or domains (see data selectors above).

Common error responses

• 400 Bad Request: malformed request body or invalid parameters.
• 401 Unauthorized: missing or invalid API key.
• 403 Forbidden: access restrictions on the API key (e.g., domain/team restrictions).
• 404 Not Found: resource does not exist (invalid link id).
• 429 Too Many Requests: rate limit exceeded — back off and retry after indicated interval.
• 500/502/503: server errors — retry with backoff.

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

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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.

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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