Load PayU data to DuckDB

PayU is a global payment processing platform offering various REST APIs for merchants to integrate payment capabilities into their applications and websites. Everything needed to build a working PayU → 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 PayU 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 PayU 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 PayU 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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PayU API at a glance

These values come from the PayU API reference — the authoritative source if anything here looks out of date.

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How do I authenticate with the PayU API?

PayU APIs generally use either an OAuth2 Bearer token in the 'Authorization' header or a custom HMAC signature header. For the OAuth2 flow, the token is obtained via a POST request and then passed in the 'Authorization' header as 'Bearer '. For the HMAC-based v2 APIs, the 'Authorization' header contains a string formatted as 'hmac username="<merchant_key>", algorithm="sha512", headers="date", signature="<calculated_hash>"' along with a mandatory 'date' header.

1. Get your credentials

To obtain PayU API credentials, navigate to the PayU Merchant Dashboard at https://onboarding.payu.in/app/account/signin. Log in, then use the toggle menu bar to switch between Test Mode or Live Mode. Navigate to the Developer section on the left-hand side menu and select either API Details or API Keys. Your merchant Key and Salt will be visible there. Note that for Partner-specific or modern OAuth-based integrations, you may instead need a Client ID and Client Secret, which are also accessible within the Developer section of the dashboard.

2. Add them to .dlt/secrets.toml

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[sources.payu_source]
api_key = "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 PayU data can I load into DuckDB?

These are the PayU endpoints dlt can load into DuckDB:

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How do I load only new PayU records?

PayU exposes dateFrom on v2/payments/transactions, 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_details", "endpoint": {
    "path": "v2/payments/transactions",
    "data_selector": "result",
    "incremental": {"cursor_path": "dateFrom", "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 PayU pipeline look like?

A standard dlt REST API pipeline — the same code you would write by hand, loading _payment and verify_payment from the PayU API into DuckDB:

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

@dlt.source
def payu_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "PayU provides multiple environment-specific base URLs depending on the region and service, such as 'https://secure.payu.com' for GPO Europe or 'https://api.payu.in' and 'https://apitest.payu.in' for PayU India v2 APIs.",
            "auth": {"type": "bearer", "token": api_key},
        },
        "resources": [
            {"name": "transaction_details", "endpoint": {"path": "v2/payments/transactions", "data_selector": "result"}},
            {"name": "settlement_details", "endpoint": {"path": "settlement/range", "data_selector": "result"}}
        ],
    }
    yield from rest_api_resources(config)


def load_payu_to_duckdb() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="payu_pipeline",
        destination="duckdb",
        dataset_name="payu_data",
    )
    load_info = pipeline.run(payu_source())
    print(load_info)


if __name__ == "__main__":
    load_payu_to_duckdb()

Run it with python payu_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 PayU 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("payu_pipeline").dataset()
df = data.transaction_details.df()
print(df.head())

SQL:

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SELECT * FROM payu_data.transaction_details LIMIT 10;

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

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How do I deploy the PayU 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 PayU 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 PayU 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