Load Doku data to DuckDB

DOKU is a payment processing platform providing various APIs for managing transactions, tokenization, and business integration. Everything needed to build a working Doku → 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 Doku 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 Doku 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 Doku 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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Doku API at a glance

These values come from the Doku API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the Doku API?

Authentication requires a Bearer token obtained by calling the OAuth 2.0 access token endpoint. Protected resource requests must include the 'Authorization: Bearer <access_token>' header along with mandatory signature headers such as 'X-SIGNATURE', 'X-TIMESTAMP', and 'X-CLIENT-KEY'.

1. Get your credentials

1. Log in to your DOKU Dashboard at https://dashboard.doku.com/bo/login. 2. Navigate to the side navigation bar and select Settings. 3. Under the Account section, click on API Keys. 4. On the API Keys page, click Reveal Key. 5. Enter the 6-digit verification code (OTP) sent to your registered email address. 6. Upon successful verification, your Secret Key will be visible for 30 seconds. You may copy the Client ID and Secret Key from this page.

2. Add them to .dlt/secrets.toml

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[sources.doku_source]
client_id = "REPLACE_ME"

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 Doku data can I load into DuckDB?

These are the Doku endpoints dlt can load into DuckDB:

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How do I load only new Doku records?

Doku exposes updated_at on wallet-as-a-service/status, 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": "transaction_status", "endpoint": {
    "path": "wallet-as-a-service/status",
    "data_selector": "data",
    "incremental": {"cursor_path": "updated_at", "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 Doku pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading token and payment from the Doku API into DuckDB:

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

@dlt.source
def doku_source(client_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.doku.com",
            "auth": {"type": "bearer", "token": client_id},
        },
        "resources": [
            {"name": "transaction_status", "endpoint": {"path": "wallet-as-a-service/status", "data_selector": "data"}},
            {"name": "sub_accounts", "endpoint": {"path": "wallet-as-a-service/sub-accounts", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def load_doku_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="doku_pipeline",
        destination="duckdb",
        dataset_name="doku_data",
    )
    load_info = pipeline.run(doku_source())
    print(load_info)


if __name__ == "__main__":
    load_doku_to_duckdb()

Run it with python doku_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 Doku 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("doku_pipeline").dataset()
df = data.transaction_status.df()
print(df.head())

SQL:

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SELECT * FROM doku_data.transaction_status LIMIT 10;

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

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How do I deploy the Doku 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 Doku 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 Doku 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