Load Duda Collections API data to DuckDB

Duda Collections API is a RESTful interface for managing website collections, fields, and data content across Duda partner and app platforms. Everything needed to build a working Duda Collections API → 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 Duda Collections API to DuckDB pipeline

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

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Run uvx dlthub-init@latest to build a pipeline from Duda Collections API 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 Duda Collections API 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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Duda Collections API API at a glance

These values come from the Duda Collections API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Duda Collections API API?

Duda APIs use HTTP Basic Authentication for account-level access by sending a base64 encoded 'username:password' string in the 'Authorization' header. Site-specific operations additionally require an 'X-DUDA-ACCESS-TOKEN' header containing a 'Bearer ' string.

1. Get your credentials

To obtain your API credentials for the Duda REST API, follow these steps: 1. Log in to your Duda dashboard. 2. Navigate to the Business Tools section. 3. Select API Access. 4. Here you will find your assigned username and password. If you are setting this up for the first time, you may need to reset or generate these credentials. Note that resetting them may impact existing integrations using these keys.

2. Add them to .dlt/secrets.toml

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[sources.duda_collections_api_source]
# Replace with your actual credentials retrieved from the dashboard\n# The API requires a Base64 encoded string of 'username:password'\napi_key = "dGhlX3VzZXJuYW1lOnRoZV9wYXNzd29yZA==" \n# For dlt headers, you might need to supply these separately or as a pre-encoded header\nduda_username = "your_username"\nduda_password = "your_password"

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 Duda Collections API data can I load into DuckDB?

These are the Duda Collections API endpoints dlt can load into DuckDB:

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How do I load only new Duda Collections API records?

The Duda Collections API 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": "collections_list", "endpoint": {
    "path": "api/sites/multiscreen/{site_name}/collection",
    # 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 Duda Collections API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /sites/multiscreen/{site_name}/collection and /sites/multiscreen/{site_name}/collection/{collection_name} from the Duda Collections API API into DuckDB:

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

@dlt.source
def duda_collections_api_source(api_user=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.duda.co/api",
            "auth": {"type": "http_basic", "username": "REPLACE_ME", "password": api_user},
        },
        "resources": [
            {"name": "collections_list", "endpoint": {"path": "api/sites/multiscreen/{site_name}/collection"}},
            {"name": "collection_get", "endpoint": {"path": "api/sites/multiscreen/{site_name}/collection/{collection_name}"}}
        ],
    }
    yield from rest_api_resources(config)


def load_duda_collections_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="duda_collections_api_pipeline",
        destination="duckdb",
        dataset_name="duda_collections_api_data",
    )
    load_info = pipeline.run(duda_collections_api_source())
    print(load_info)


if __name__ == "__main__":
    load_duda_collections_api_to_duckdb()

Run it with python duda_collections_api_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 Duda Collections API 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("duda_collections_api_pipeline").dataset()
df = data.collection_get.df()
print(df.head())

SQL:

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SELECT * FROM duda_collections_api_data.collection_get LIMIT 10;

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

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How do I deploy the Duda Collections API 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 Duda Collections API 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 Duda Collections API 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