FinDock Python API Docs | dltHub

FinDock Payment API is a REST API for handling one-time and recurring payments. The REST API base URL is https://<SALESFORCE_DOMAIN_URL>/services/apexrest/cpm/v2/ and All requests require an OAuth2 Bearer token for authentication, passed in the Authorization header..

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 FinDock data in under 10 minutes.

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What data can I load from FinDock?

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

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How do I authenticate with the FinDock API?

Authentication is handled via an OAuth2.0 authorization flow. The obtained access token must be passed as a Bearer token in the Authorization header of each request.

1. Get your credentials

1. Ensure you have a licensed installation and configured FinDock app in a Salesforce org.
2. In Salesforce 'Setup', create a 'Connected App'.
3. From the Connected App, acquire the client_id and client_secret.
4. Configure the Connected App with OAuth2 authentication and at least the 'Manage user data via APIs (api)' scope.

2. Add them to .dlt/secrets.toml

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[sources.findock_payment_api_source]
client_id = "your_client_id"
client_secret = "your_client_secret"
refresh_token = "your_refresh_token"
salesforce_domain_url = "https://your-salesforce-domain.my.salesforce.com"

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 FinDock 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 findock_payment_api_pipeline.py

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

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Pipeline findock_payment_api_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset findock_payment_api_data
The duckdb destination used duckdb:/findock_payment_api.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 findock_payment_api_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 payment_methods and package_actions from the FinDock 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 findock_payment_api_source(client_secret=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://<SALESFORCE_DOMAIN_URL>/services/apexrest/cpm/v2/",
            "auth": {
                "type": "oauth2",
                "client_secret": client_secret,
            },
        },
        "resources": [
            {"name": "payment_methods", "endpoint": {"path": "PaymentMethods"}},
            {"name": "package_actions", "endpoint": {"path": "PackageActions"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="findock_payment_api_pipeline",
        destination="duckdb",
        dataset_name="findock_payment_api_data",
    )
    load_info = pipeline.run(findock_payment_api_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("findock_payment_api_pipeline").dataset()
sessions_df = data.payment_methods.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM findock_payment_api_data.payment_methods LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("findock_payment_api_pipeline").dataset()
data.payment_methods.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 FinDock 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

API Error Handling

When an API call is not successful, the FinDock Payment API returns an HTTP Status Code (4xx or 500) and an array of Errors in the response body. Each error object contains an error_code and an error_message.

Generic Error Code 999

If the API is unable to determine the nature of a problem, it may return error code 999 with a generic error message. In such cases, adding a header parameter verbose with the value true can provide the original status code and error thrown by Salesforce, offering more detailed insights.

Salesforce INVALID_SESSION_ID Error

An INVALID_SESSION_ID error from Salesforce (error code 040) indicates an authentication issue. This typically means the OAuth2 token has expired or is invalid. Ensure your OAuth2 flow is correctly refreshing tokens and that the connected app has the necessary 'Manage user data via APIs (api)' scope.

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