Younium Python API Docs | dltHub

Younium API is a RESTful API designed for transactional integrations and automation, suitable for managing accounts, products, subscription lifecycles, and invoice flows. The REST API base URL is https://api.younium.com and All requests require a Bearer JWT token in the Authorization header and an 'api-version' header (v2.1 default)..

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 Younium data in under 10 minutes.

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What data can I load from Younium?

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

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How do I authenticate with the Younium API?

The Younium API uses an OAuth-like flow to issue JWT tokens. All requests require an Authorization header with 'Bearer <jwt_token>' and an 'api-version: 2.1' header.

1. Get your credentials

1. Generate API token and client credentials in Younium dashboard. 2. Use client credentials to request/construct a JWT token. 3. Use the JWT as a Bearer token in the Authorization header for subsequent API requests. (See provider dashboard 'Get started / Generate API Token' documentation for exact steps.)

2. Add them to .dlt/secrets.toml

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[sources.younium_financial_management_source]
api_token = "YOUR_JWT_TOKEN_HERE"

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 Younium 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 younium_financial_management_pipeline.py

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

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Pipeline younium_financial_management_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset younium_financial_management_data
The duckdb destination used duckdb:/younium_financial_management.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 younium_financial_management_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 subscriptions and accounts from the Younium 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 younium_financial_management_source(api_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.younium.com",
            "auth": {
                "type": "bearer",
                "token": api_token,
            },
        },
        "resources": [
            {"name": "subscriptions", "endpoint": {"path": "Subscriptions"}},
            {"name": "accounts", "endpoint": {"path": "Accounts"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="younium_financial_management_pipeline",
        destination="duckdb",
        dataset_name="younium_financial_management_data",
    )
    load_info = pipeline.run(younium_financial_management_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("younium_financial_management_pipeline").dataset()
sessions_df = data.subscriptions.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM younium_financial_management_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("younium_financial_management_pipeline").dataset()
data.subscriptions.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 Younium 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

If the Authorization Bearer token is missing or invalid, the API will return an authentication error. Ensure you include 'Authorization: Bearer ' and 'api-version: 2.1'. Re-generate the JWT if expired.

Pagination and empty results

Use pageNumber and pageSize (max pageSize 100). If a GET request returns no records, the API may respond with a 400 Bad Request — handle this as an empty result set in your pipeline.

Filtering and type formatting

When filtering on datetime or guid values, use the required wrappers: datetime'YYYY-MM-DD' and guid'<uuid>'. Incorrect formatting will cause Bad Request errors.

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