Hostex Python API Docs | dltHub

Hostex is a property management system API that provides endpoints for managing properties, bookings, availability, pricing, guest messaging, and reviews. The REST API base URL is https://api.hostex.io/v3 and requests require a Hostex-Access-Token header or an Authorization Bearer token.

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 add "dlt[hub]" and start loading Hostex data in under 10 minutes.

---

What data can I load from Hostex?

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

---

How do I authenticate with the Hostex API?

Authentication is handled either via a static API token passed in the 'Hostex-Access-Token' header, or through OAuth 2.0 where a Bearer token is provided in the standard 'Authorization' header. Static tokens are preferred for individual accounts, while OAuth is intended for software partners.

1. Get your credentials

To obtain your Hostex API credentials, log in to your account via the Hostex Host Portal. Navigate to the OpenAPI Settings page (typically found under account settings or API section). Click the '+ Add new' button to generate a new access token. Name the token, select the required access scope (read-only or writable), and save it. Once generated, copy the token string immediately as it will be used in your API request headers.

2. Add them to .dlt/secrets.toml

Copy
[sources.hostex_source]
api_key = "your_access_token_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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv init
uv add "dlt[hub]"

1. Install the dlt AI harness:

Copy
uv run dlthub 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:

Copy
uv run dlthub ai toolkit install rest-api-pipeline

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 Hostex 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:

Copy
uv run python hostex_pipeline.py

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

Copy
Pipeline hostex_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset hostex_data
The duckdb destination used duckdb:/hostex.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
uv run dlthub show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

---

Python pipeline example

This example loads /oauth/authorizations and /oauth/revoke from the Hostex API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def hostex_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.hostex.io/v3",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "properties", "endpoint": {"path": "properties"}},
            {"name": "reservations", "endpoint": {"path": "reservations"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="hostex_pipeline",
        destination="duckdb",
        dataset_name="hostex_data",
    )
    load_info = pipeline.run(hostex_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.

---

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):

Copy
import dlt

data = dlt.pipeline("hostex_pipeline").dataset()
sessions_df = data.reservations.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM hostex_data.reservations LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("hostex_pipeline").dataset()
data.reservations.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Hostex 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.

---

Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI harness:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-platform — Deploy, schedule, and monitor your pipeline in production.

Copy
uv run dlthub ai toolkit install data-exploration
uv run dlthub ai toolkit install dlthub-platform

• 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