Funnel Python API Docs | dltHub

Funnel is a property listings and leasing platform API exposing property, listing, prospect and leasing endpoints for integrations. The REST API base URL is https://{your_funnel_host}/api/v2 and Most requests use an API key via the key query parameter; Listings Sync uses HTTP Basic Auth..

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 Funnel data in under 10 minutes.

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What data can I load from Funnel?

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

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How do I authenticate with the Funnel API?

Standard endpoints require an API key supplied as the key query parameter; the Listings Sync endpoint requires HTTP Basic Authentication with a username and password.

1. Get your credentials

1. Sign in to your Funnel account or contact your Funnel account representative. 2) Navigate to Account → Integration → API Settings. 3) Request or generate an API key for your company. 4) If you need the Listings Sync endpoint, confirm that your plan includes sync access and obtain the Basic Auth username/password from the same settings page or via support.

2. Add them to .dlt/secrets.toml

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[sources.funnel_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 Funnel 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 funnel_pipeline.py

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

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Pipeline funnel_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset funnel_data
The duckdb destination used duckdb:/funnel.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 funnel_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 listings and sync_listings from the Funnel 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 funnel_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your_funnel_host}/api/v2",
            "auth": {
                "type": "api_key",
                "key": api_key,
            },
        },
        "resources": [
            {"name": "listings", "endpoint": {"path": "listings/all/", "data_selector": "items"}},
            {"name": "sync_listings", "endpoint": {"path": "sync/listings/", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="funnel_pipeline",
        destination="duckdb",
        dataset_name="funnel_data",
    )
    load_info = pipeline.run(funnel_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("funnel_pipeline").dataset()
sessions_df = data.listings.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM funnel_data.listings LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("funnel_pipeline").dataset()
data.listings.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 Funnel 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 401/403 check that you are supplying the API key as ?key=YOUR_KEY on standard endpoints. For the Listings Sync endpoint confirm you are using the Basic Auth username/password Funnel provided and that Sync access is enabled on your account.

Pagination and sync pointer

Listings search endpoints use page & total_pages for standard searches (responses include items, total_pages, page, total_items). The Listings Sync endpoint uses pointer‑based pagination: responses include pointer.next_id; pass that value as max_id on the next request (and preserve any filter params).

Rate limiting & courteous usage

Funnel does not publish strict rate limits but requests that you be reasonable. Excessive automated polling can result in revoked access; use the Listings Sync endpoint for large or frequent syncs and contact Funnel for higher‑volume needs.

Common API errors

• 400 Bad Request – invalid parameters (e.g., wrong date format on onlineleasing-link).
• 401/403 Unauthorized/Forbidden – missing or invalid API key or Basic Auth credentials.
• 404 Not Found – resource does not exist or private listing without include_private.
• 302 Redirect – onlineleasing-link returns 302 to the leasing app when parameters are valid.

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