Webpay Python API Docs | dltHub

Webpay is Transbank's payment processing REST API for creating, confirming, querying and managing card transactions (Webpay Plus and Mall). The REST API base URL is https://webpay3g.transbank.cl and All requests require commercial code and secret via request headers..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Webpay data in under 10 minutes.

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What data can I load from Webpay?

Here are some of the endpoints you can load from Webpay:

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How do I authenticate with the Webpay API?

Authentication uses two HTTP headers on every request: Tbk-Api-Key-Id (commerce code) and Tbk-Api-Key-Secret (API secret). Use TLS 1.2. Content-Type: application/json for JSON payloads.

1. Get your credentials

1. Contact Transbank to obtain production credentials (commerce code and API secret) via your Transbank integrator or support. 2) For integration/testing use the published integration commerce codes and API keys in the Transbank docs or SDK examples. 3) Never hardcode production credentials; store them in environment variables or a secret store.

2. Add them to .dlt/secrets.toml

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[sources.webpay_source]
# Put in [sources.webpay_source]
tbk_api_key_id = "597055555532"
tbk_api_key_secret = "579B532A7440BB0C9079DED94D31EA1615BACEB56610332264630D42D0A36B1C"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Webpay API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python webpay_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline webpay_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset webpay_data
The duckdb destination used duckdb:/webpay.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline webpay_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads transactions_status and transactions_create from the Webpay API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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

@dlt.source
def webpay_source(tbk_api_key_id=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://webpay3g.transbank.cl",
            "auth": {
                "type": "api_key",
                "tbk_api_key_id": tbk_api_key_id,
            },
        },
        "resources": [
            {"name": "transactions_status", "endpoint": {"path": "rswebpaytransaction/api/webpay/v1.2/transactions/{token}"}},
            {"name": "transactions_create", "endpoint": {"path": "rswebpaytransaction/api/webpay/v1.2/transactions"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="webpay_pipeline",
        destination="duckdb",
        dataset_name="webpay_data",
    )
    load_info = pipeline.run(webpay_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("webpay_pipeline").dataset()
sessions_df = data.transactions_status.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM webpay_data.transactions_status LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("webpay_pipeline").dataset()
data.transactions_status.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Webpay data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

Webpay returns 401 for invalid or missing Tbk-Api-Key-Id/Tbk-Api-Key-Secret. Verify headers, correct commerce code for environment (integration vs production) and TLS 1.2.

Invalid JSON / validation errors

Requests with malformed JSON or invalid fields return 400 or 422 with body {"error_message":"..."}. Check required fields (buy_order, session_id, amount, return_url for create) and numeric types.

Transaction not found

GET /transactions/{token} returns 404 if token is unknown or expired — ensure you use the token returned by create and the correct environment.

Rate limits and server errors

API may return 500 on unexpected errors. Retry with backoff for transient server errors. No public rate‑limit headers documented; contact Transbank support for quota questions.

Mall details array

Mall transaction status responses include a "details" array (data selector: "details") containing per‑store result objects; other responses are top‑level objects (no list data selector).

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack