Load Ola Maps data to DuckDB

Ola Maps is an AI-powered geospatial platform providing routing, geocoding, places search, and map visualization APIs tuned for India. Everything needed to build a working Ola Maps → 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 Ola Maps 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 Ola Maps 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 Ola Maps 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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Ola Maps API at a glance

These values come from the Ola Maps API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Ola Maps API?

The API supports OAuth 2.0 (Bearer token in Authorization header) and API Key (passed as a query parameter).

1. Get your credentials

To obtain credentials for the Ola Maps API: 1. Sign up or log in to the Krutrim Cloud portal at https://cloud.olakrutrim.com. 2. Navigate to the 'Credentials' section within the dashboard. 3. Click 'New Credentials' in the top right corner. 4. Provide a name and description for your credentials. 5. Once created, click on the credential name in the list to view your 'API Key' and 'OAuth2 client credentials'. 6. Ensure you whitelist your domains as comma-separated values in the credential details.

2. Add them to .dlt/secrets.toml

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[sources.ola_maps_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 Ola Maps data can I load into DuckDB?

These are the Ola Maps endpoints dlt can load into DuckDB:

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How do I load only new Ola Maps records?

The Ola Maps 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": "geofences", "endpoint": {
    "path": "geofencing/v1/geofences",
    # 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 Ola Maps pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading autocomplete and directions from the Ola Maps API into DuckDB:

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

@dlt.source
def ola_maps_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.olamaps.io",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "geofences", "endpoint": {"path": "geofencing/v1/geofences"}}
        ],
    }
    yield from rest_api_resources(config)


def load_ola_maps_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="ola_maps_pipeline",
        destination="duckdb",
        dataset_name="ola_maps_data",
    )
    load_info = pipeline.run(ola_maps_source())
    print(load_info)


if __name__ == "__main__":
    load_ola_maps_to_duckdb()

Run it with python ola_maps_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 Ola Maps 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("ola_maps_pipeline").dataset()
df = data.geofences.df()
print(df.head())

SQL:

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SELECT * FROM ola_maps_data.geofences LIMIT 10;

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

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How do I deploy the Ola Maps 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 Ola Maps 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 Ola Maps 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