Bookeo Python API Docs | dltHub

Bookeo is an online appointment and booking management platform with a REST API to access accounts, bookings, customers, products, resources and related data. The REST API base URL is https://api.bookeo.com/v2 and All requests require both a secret key and an API key (app secret + account apiKey)..

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 Bookeo data in under 10 minutes.

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What data can I load from Bookeo?

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

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How do I authenticate with the Bookeo API?

Bookeo uses two credentials: the application secret key (issued when registering the app) and an apiKey (issued when a Bookeo account authorizes/installs the app). Both must be sent on every request either as URL parameters (secretKey and apiKey) or as HTTP headers (X-Bookeo-secretKey and X-Bookeo-apiKey).

1. Get your credentials

1. Register an application in Bookeo (Application setup page) to obtain the secret key. 2) Ask the account owner to authorize/install your application; after authorization Bookeo returns an apiKey for that account. 3) The account owner can revoke/uninstall the app at any time; reinstalling issues a new apiKey.

2. Add them to .dlt/secrets.toml

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[sources.bookeo_source]
secretKey = "your_app_secret_here"
apiKey = "user_account_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 Bookeo 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 bookeo_pipeline.py

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

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Pipeline bookeo_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset bookeo_data
The duckdb destination used duckdb:/bookeo.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 bookeo_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 bookings and customers from the Bookeo 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 bookeo_source(secret_key_and_api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.bookeo.com/v2",
            "auth": {
                "type": "http_basic",
                "apiKey and secretKey": secret_key_and_api_key,
            },
        },
        "resources": [
            {"name": "bookings", "endpoint": {"path": "bookings", "data_selector": "data"}},
            {"name": "customers", "endpoint": {"path": "customers", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="bookeo_pipeline",
        destination="duckdb",
        dataset_name="bookeo_data",
    )
    load_info = pipeline.run(bookeo_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("bookeo_pipeline").dataset()
sessions_df = data.bookings.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM bookeo_data.bookings LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("bookeo_pipeline").dataset()
data.bookings.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 Bookeo 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 omit or send invalid secretKey or apiKey, Bookeo returns a non-success HTTP status (e.g., 401/403) with a JSON body containing httpStatus, message and errorId. Include both credentials as query parameters (secretKey, apiKey) or as headers (X-Bookeo-secretKey, X-Bookeo-apiKey).

Pagination

Many list endpoints return paginated responses in the shape {"data": [ ... ], "info": {"totalItems": n, "totalPages": p, "currentPage": x, "pageNavigationToken": "..."}}. To retrieve another page, call the same endpoint with pageNavigationToken and pageNumber; when paging use the token returned by the response.

Rate limiting and errors

The API uses normal HTTP status codes and provides a JSON error body with an errorId. For server‑side or unexpected errors quote the errorId when contacting Bookeo support (api@bookeo.com). There is no explicit published rate limit in the docs — implement exponential backoff on 5xx and 429 responses.

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