Load Trestle API data to DuckDB

Trestle is a real estate data platform providing access to MLS data via a RESO Web API and OData compliant interface. Everything needed to build a working Trestle API → DuckDB pipeline is on this page: the API's base URL, authentication, endpoints, pagination and incremental field — plus a prompt that hands the whole job to your coding agent.

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Build your Trestle API to DuckDB pipeline

Paste this prompt into Claude, Codex, or Cursor. The agent does the rest.

PromptCopy prompt
Run uvx dlthub-init@latest to build a pipeline from Trestle API to DuckDB and run it on dltHub

That scaffolds a dltHub workspace and installs the dltHub AI harness — the project rules, the secrets-management skill, and the dlt MCP server your agent needs to work safely. From there it reads the Trestle API API, proposes the endpoints to load, then writes, runs and validates the pipeline while you review rather than type. Credentials are inspected through MCP tools, so your agent never reads secrets.toml itself. How the LLM-native workflow works →

Prefer to write it yourself? Every fact the agent uses is below.

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Trestle API API at a glance

These values come from the Trestle API API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Trestle API API?

The service uses OAuth2 client_credentials flow, requiring a POST request to the token endpoint to obtain a Bearer token; this token is then passed in the Authorization header for subsequent API calls.

1. Get your credentials

To obtain credentials for the Trestle Identity APIs, sign up for a Developer Portal account at https://portal.trestleiq.com/signup. Once your account is verified, log in to the Trestle Developer Portal to access your account dashboard, where you can generate and manage your API keys. Your API key is used as the primary authentication method by including it in the x-api-key HTTP header in your requests. Note that Trestle also provides real estate-specific data (RESO Web API) which uses a separate OAuth2 client_credentials authentication flow.

2. Add them to .dlt/secrets.toml

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[sources.trestle_api_source]
api_key = "your_api_key_here"

dlt reads this file automatically at runtime. With the harness, the setup-secrets skill prompts you for the values and never handles the raw credential in chat. For production, see setting up credentials with dlt.

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What Trestle API data can I load into DuckDB?

These are the Trestle API endpoints dlt can load into DuckDB:

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How do I load only new Trestle API records?

Trestle API exposes ModificationTimestamp on trestle/odata/Property, so dlt can request only the records that changed since the last run. Set it as the cursor_path and dlt tracks the high-water mark for you between runs.

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{"name": "property", "endpoint": {
    "path": "trestle/odata/Property",
    "data_selector": "value",
    "incremental": {"cursor_path": "ModificationTimestamp", "initial_value": "2024-01-01T00:00:00Z"},
}}

On the first run dlt loads everything from initial_value; on every run after that it requests only what changed and appends with write_disposition="merge" if you set a primary key. See incremental loading.

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What does the generated Trestle API pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading phone (for Identity APIs) and Property (for OData/RESO Web API) from the Trestle API API into DuckDB:

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

@dlt.source
def trestle_api_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.cotality.com/trestle/odata",
            "auth": {"type": "bearer", "token": token},
        },
        "resources": [
            {"name": "property", "endpoint": {"path": "trestle/odata/Property", "data_selector": "value"}},
            {"name": "media", "endpoint": {"path": "trestle/odata/Media", "data_selector": "value"}}
        ],
    }
    yield from rest_api_resources(config)


def load_trestle_api_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="trestle_api_pipeline",
        destination="duckdb",
        dataset_name="trestle_api_data",
    )
    load_info = pipeline.run(trestle_api_source())
    print(load_info)


if __name__ == "__main__":
    load_trestle_api_to_duckdb()

Run it with python trestle_api_pipeline.py. The agent iterates on this until it loads cleanly — you review and approve, rather than write it from scratch.

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How do I query Trestle API data in DuckDB?

dlt creates one table per resource. Query the loaded data with Python or SQL — or ask your agent to, through the MCP server's execute_sql_query tool.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("trestle_api_pipeline").dataset()
df = data.property.df()
print(df.head())

SQL:

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SELECT * FROM trestle_api_data.property LIMIT 10;

See querying your data with dataset and exploring it in marimo notebooks.

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How do I deploy the Trestle API to DuckDB pipeline in production?

The pipeline runs locally, which is ideal for prototyping and one-off analysis. When you need it on a schedule, monitored on every load, and shared with your team, deploy the same dlt code on the dltHub platform — no infrastructure to maintain. The prompt above already ends with "run it on dltHub", so your agent can take it there directly.

• Deploy & schedule — run the pipeline as a managed job with automatic retries.
• Monitor — observable job queues, alerting, and load metrics for every run.
• Transform — promote raw Trestle API loads into governed, documented models.
• Visualize & share — explore data in notebooks and publish live dashboards instead of static screenshots.

Book a demo →

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What other destinations can I load Trestle API data to?

dlt loads into any of these — only the destination argument changes:

Set dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. On the dltHub platform the same pipeline runs against a managed Iceberg lakehouse. See the full destinations list.

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Next steps

• Ready for production? Book a demo of the dltHub platform →
• dlt LLM-native workflow docs
• REST API source reference
• Join the dlt community on Slack