Load Bitly data to DuckDB

Bitly is a link management platform providing a REST API for creating and managing Bitlinks, custom domains, groups, and click analytics. Everything needed to build a working Bitly → 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.

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Build your Bitly to DuckDB pipeline

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

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Bitly 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 Bitly 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.

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Bitly API at a glance

These values come from the Bitly API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Bitly API?

Bitly uses Bearer token authentication. Every request must include an 'Authorization' header with the value 'Bearer {TOKEN}'.

1. Get your credentials

To generate an OAuth access token for the Bitly API, log in to your Bitly account and navigate to the Settings page in the left sidebar. Select the API option, enter your Bitly account password when prompted in the access token section, and click Generate token. Copy the resulting token immediately, as navigating away will require re-authentication to view it again. If you use SSO and do not have a set Bitly password, you must reset your password via the login screen to create one before accessing the token generation flow.

2. Add them to .dlt/secrets.toml

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[sources.bitly_source]
access_token = "your_bitly_access_token_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.

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What Bitly data can I load into DuckDB?

These are the Bitly endpoints dlt can load into DuckDB:

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How do I load only new Bitly records?

The Bitly API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "groups", "endpoint": {
    "path": "groups",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "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.

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What does the generated Bitly pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /v4/shorten and /v4/bitlinks from the Bitly API into DuckDB:

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

@dlt.source
def bitly_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api-ssl.bitly.com/v4",
            "auth": {"type": "bearer", "token": access_token},
        },
        "resources": [
            {"name": "groups", "endpoint": {"path": "groups", "data_selector": "groups"}},
            {"name": "group_bitlinks", "endpoint": {"path": "groups/{group_guid}/bitlinks", "data_selector": "links"}}
        ],
    }
    yield from rest_api_resources(config)


def load_bitly_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="bitly_pipeline",
        destination="duckdb",
        dataset_name="bitly_data",
    )
    load_info = pipeline.run(bitly_source())
    print(load_info)


if __name__ == "__main__":
    load_bitly_to_duckdb()

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

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How do I query Bitly 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):

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import dlt

data = dlt.pipeline("bitly_pipeline").dataset()
df = data.group_bitlinks.df()
print(df.head())

SQL:

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SELECT * FROM bitly_data.group_bitlinks LIMIT 10;

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

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How do I deploy the Bitly 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 Bitly loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Bitly data to?

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

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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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack