Rezdy Python API Docs | dltHub

Rezdy is a booking and distribution platform for tours and activities, providing REST APIs for agents, suppliers, RezdyConnect integrations and webhooks to manage products, availability, bookings and notifications. The REST API base URL is https://api.rezdy.com/v1 and All requests require an API key (query parameter) or OAuth2 for RezdyConnect; API Key is the primary auth for agent/supplier APIs..

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 Rezdy data in under 10 minutes.

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What data can I load from Rezdy?

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

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How do I authenticate with the Rezdy API?

Rezdy agent/supplier APIs use an apiKey (passed as a query parameter) over HTTPS; RezdyConnect also supports OAuth2 bearer tokens (Authorization: Bearer ) when configured.

1. Get your credentials

1. Log into your Rezdy account. 2) Go to Developer / API Keys (or Account > API Keys). 3) Create or copy the API Key for agent or supplier access. 4) For RezdyConnect OAuth2, request RezdyConnect access and obtain client_id/client_secret from Rezdy during integration setup.

2. Add them to .dlt/secrets.toml

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[sources.rezdy_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 Rezdy 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 rezdy_pipeline.py

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

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Pipeline rezdy_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset rezdy_data
The duckdb destination used duckdb:/rezdy.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 rezdy_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 products and bookings from the Rezdy 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 rezdy_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.rezdy.com/v1",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "products", "endpoint": {"path": "v1/products", "data_selector": "products"}},
            {"name": "bookings", "endpoint": {"path": "v1/bookings", "data_selector": "bookings"}}
        ],
    }
    yield from rest_api_resources(config)


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

SQL (DuckDB example):

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SELECT * FROM rezdy_data.bookings LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("rezdy_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 Rezdy 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 receive 403 or an auth-related error, verify you are sending the correct apiKey (agent/supplier APIs expect apiKey as a query parameter) and using HTTPS. RezdyConnect OAuth2 flows require a valid bearer token in Authorization header.

Rate limits & server errors

Rezdy documents rate limits and availability; transient 500/503 responses indicate server-side issues — implement retries with exponential backoff. 403 indicates invalid API key; 422 indicates invalid product/order or no availability.

Pagination and selectors

Many list endpoints return objects wrapped in a top-level key (e.g., "products", "bookings", "sessions" or "availability"). Use the exact top-level key as the data selector when extracting record arrays; if the endpoint returns a single object (e.g., GET /v1/bookings/{orderNumber}) there is no array selector.

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