Load OpenCage Data data to DuckDB

OpenCage Geocoding API is a geocoding service that converts addresses into coordinates and vice versa using open data. Everything needed to build a working OpenCage Data → 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 OpenCage Data 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 OpenCage Data 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 OpenCage Data 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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OpenCage Data API at a glance

These values come from the OpenCage Data API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the OpenCage Data API?

Authentication is performed by passing a valid API key as the 'key' parameter in the query string of every HTTP GET request; no HTTP headers are required or used for authentication.

1. Get your credentials

1. Sign up for an account at the OpenCage Data website. 2. Log in to your account dashboard. 3. Navigate to the Geocoding API section to view your unique 32-character alphanumeric API key. You may generate, disable, or manage multiple keys (for subscription customers) from this page.

2. Add them to .dlt/secrets.toml

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[sources.opencage_data_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 OpenCage Data data can I load into DuckDB?

These are the OpenCage Data endpoints dlt can load into DuckDB:

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How do I load only new OpenCage Data records?

The OpenCage Data API reference does not document a timestamp or sequence field for these endpoints, so there is nothing to advertise here as verified. Pick a field from the endpoints table above that increases with every write, then set it as the cursor_path.

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{"name": "geocode_json", "endpoint": {
    "path": "geocode/v1/json",
    # Replace with a field that increases on every write.
    "incremental": {"cursor_path": "REPLACE_ME", "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 OpenCage Data pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading /json and /geojson from the OpenCage Data API into DuckDB:

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

@dlt.source
def opencage_data_source(key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.opencagedata.com/geocode/v1",
            "auth": {"type": "api_key", "api_key": key, "name": "key"},
        },
        "resources": [
            {"name": "geocode_json", "endpoint": {"path": "geocode/v1/json", "data_selector": "results"}},
            {"name": "connectivity_ping", "endpoint": {"path": "geocode/v1/ping"}}
        ],
    }
    yield from rest_api_resources(config)


def load_opencage_data_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="opencage_data_pipeline",
        destination="duckdb",
        dataset_name="opencage_data_data",
    )
    load_info = pipeline.run(opencage_data_source())
    print(load_info)


if __name__ == "__main__":
    load_opencage_data_to_duckdb()

Run it with python opencage_data_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 OpenCage Data 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("opencage_data_pipeline").dataset()
df = data.geocode_json.df()
print(df.head())

SQL:

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SELECT * FROM opencage_data_data.geocode_json LIMIT 10;

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

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How do I deploy the OpenCage Data 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 OpenCage Data 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 OpenCage Data 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