Holidu Python API Docs | dltHub

Holidu's REST API enables developers to manage vacation rental portfolios via well-structured endpoints. It uses the HTTP protocol and requires API keys from the Holidu Developer Hub. The API documentation is available at https://developer.holidu.com/v1.0/reference/intro-to-the-connectivity-api. The REST API base URL is https://provider-api-sandbox.holidu.com/v2 and Holidu uses an API key for authentication; all requests require a valid API key..

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 Holidu data in under 10 minutes.

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What data can I load from Holidu?

Here are some of the endpoints you can load from Holidu:

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How do I authenticate with the Holidu API?

Holidu provides an API key that must be presented with API requests. The developer hub indicates the API key is required for both test and live environments and that a 401 is returned for authentication errors.

1. Get your credentials

1. Contact Holidu partner support or sign up as a partner via Holidu's partners page to request API access. 2) Holidu will provide an API key for your integration (a provider identifier is also issued). 3) Use the API key in requests to the sandbox or live base URL shown in the developer hub. 4) Use the provider identifier and providerApartmentId (or holiduApartmentId) as required by per-endpoint URL parameters.

2. Add them to .dlt/secrets.toml

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[sources.holidu_connectivity_api_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.

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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 Holidu 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 holidu_connectivity_api_pipeline.py

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

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Pipeline holidu_connectivity_api_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset holidu_connectivity_api_data
The duckdb destination used duckdb:/holidu_connectivity_api.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 holidu_connectivity_api_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 apartment and bookings from the Holidu 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 holidu_connectivity_api_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://provider-api-sandbox.holidu.com/v2",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "apartment", "endpoint": {"path": "v2/apartment"}},
            {"name": "bookings", "endpoint": {"path": "v2/bookings"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="holidu_connectivity_api_pipeline",
        destination="duckdb",
        dataset_name="holidu_connectivity_api_data",
    )
    load_info = pipeline.run(holidu_connectivity_api_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("holidu_connectivity_api_pipeline").dataset()
sessions_df = data.apartment.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM holidu_connectivity_api_data.apartment LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("holidu_connectivity_api_pipeline").dataset()
data.apartment.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 Holidu 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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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