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Load Short.io data to DuckDB

Build a Short.io to DuckDB pipeline with your coding agent. One prompt scaffolds it with the dltHub AI harness, plus the Short.io API base URL, auth, endpoints, and incremental loading.

SourceShort.ioDestinationDuckDBIn-process analytical database. The default local destination for dlt pipelines.

Short.io is a link shortening platform providing a REST API for managing domains, links, and analytics. Everything needed to build a working Short.io → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.


Build your Short.io to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

Prompt
Run uvx dlthub-init@latest to build a pipeline from Short.io to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Short.io API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.


Short.io API at a glance

Base URLhttps://api.short.io
Example endpointGET links
Records found atlinks
Authenticationall requests require an API key passed in the Authorization header — sent in the Authorization header
PaginationCursor-based via pageToken, next cursor at nextPageToken, page size via limit (default 150, max 150)
Incremental fieldcreatedAt
Record ididString
API referencehttps://developers.short.io/reference

These values come from the Short.io API reference — the authoritative source if anything here looks out of date.


How do I authenticate with the Short.io API?

Short.io API authentication is handled by passing a secret API key as the value of the 'Authorization' header in every request. No specific prefix (like 'Bearer') is required based on the provided documentation examples.

1. Get your credentials

To obtain your Short.io API key, follow these steps: 1. Log in to your Short.io account dashboard. 2. Navigate to the Integrations & API section (typically via the menu or by visiting https://app.short.io/settings/integrations/api-key). 3. Click the Create API key button. 4. Provide a description, choose your key type (Public or Private), and set access restrictions if needed. 5. Click Create. Copy the resulting API key immediately, as it cannot be retrieved once you navigate away from the page.

2. Add them to .dlt/secrets.toml

[sources.short_io_source] shortio_api_key = "your_api_key_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.


What Short.io data can I load into DuckDB?

These are the Short.io endpoints dlt can load into DuckDB:

ResourceEndpointMethodData selectorDescription
links/linksGETGet list of links for a domain (requires domain_id)
link_details/links/{linkId}GETGet link info by link id
domains/domainsGETList all domains
domain_stats/statistics/domain/{domainId}GETGet domain-level statistics
link_clicks/statistics/link/{linkId}GETGet click statistics for a specific link

How do I load only new Short.io records?

Short.io exposes createdAt on links, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

{"name": "links", "endpoint": { "path": "links", "data_selector": "links", "incremental": {"cursor_path": "createdAt", "initial_value": "2024-01-01T00:00:00Z"}, }}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.


What does the generated Short.io pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading links (used for listing and creating short links) and links/{linkId} (used for retrieving specific link information) from the Short.io API into DuckDB:

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, "name": "Authorization", "location": "header"}, }, "resources": [ {"name": "links", "endpoint": {"path": "links", "data_selector": "links"}}, {"name": "link_details", "endpoint": {"path": "links/{linkId}", "data_selector": "links"}} ], } yield from rest_api_resources(config) def load_short_io_to_duckdb() -> 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) if __name__ == "__main__": load_short_io_to_duckdb()

Run it with python short_io_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.


How do I query Short.io data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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

SQL:

SELECT * FROM short_io_data.links LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.


How do I deploy the Short.io to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

  • Deploy & schedule — run the pipeline as a managed job with automatic retries.
  • Monitor — observable job queues, alerting, and load metrics for every run.
  • Transform — promote raw Short.io loads into governed, documented models.
  • Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →


What other destinations can I load Short.io data to?

dlt loads into any of these — only the destination argument changes:

DestinationExample value
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.


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