Younium Python API Docs | dltHub

Build a Younium-to-database pipeline in Python using dlt with AI harness support for Claude Code, Cursor, and Codex.

Last updated:

Younium is a subscription management and billing platform providing a REST API for managing accounts, products, subscriptions, and invoice flows. The REST API base URL is https://api.younium.com and all requests require a Bearer token 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 add "dlt[hub]" and start loading Younium data in under 10 minutes.


What data can I load from Younium?

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

ResourceEndpointMethodData selectorDescription
accounts/AccountsGETitemsRetrieve a list of accounts
subscriptions/SubscriptionsGETitemsRetrieve a list of subscriptions
invoices/InvoicesGETitemsRetrieve a list of invoices
products/ProductsGETitemsRetrieve a list of products
journals/JournalsGETitemsRetrieve a list of journals

How do I authenticate with the Younium API?

All requests must include an Authorization header with a Bearer JWT token, as well as a Content-Type: application/json header. If your tenant has multiple legal entities, you must also provide the legal-entity header.

1. Get your credentials

  1. Log in to your Younium instance. 2. Click your user profile name in the top-right corner. 3. Navigate to 'Privacy & Security' in the dropdown menu. 4. Select 'Personal Tokens' from the left-hand panel. 5. Click 'Generate Token'. 6. Enter a descriptive name for the token and click 'Create'. 7. Copy the displayed 'Client ID' and 'Secret Key' immediately; these values will not be shown again. 8. Use these credentials to authenticate against the '/auth/v2/token' endpoint to retrieve a JWT access token for API requests.

2. Add them to .dlt/secrets.toml

[sources.younium_source] client_id = "YOUR_CLIENT_ID" secret = "YOUR_SECRET_KEY" # Optional: if using multiple legal entities # legal_entity = "YOUR_ENTITY_ID_OR_NAME"

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.


How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

uv init uv add "dlt[hub]"

1. Install the dlt AI harness:

uv run dlthub 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:

uv run dlthub ai toolkit install rest-api-pipeline

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:

uv run python younium_pipeline.py

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

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

Inspect your pipeline and data:

uv run dlthub show

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


Python pipeline example

This example loads /auth/v2/token and /accounts from the Younium API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def younium_source(api_token=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.younium.com", "auth": {"type": "bearer", "token": api_token}, }, "resources": [ {"name": "accounts", "endpoint": {"path": "Accounts", "data_selector": "items"}}, {"name": "subscriptions", "endpoint": {"path": "Subscriptions", "data_selector": "items"}} ], } yield from rest_api_resources(config) def get_data() -> None: pipeline = dlt.pipeline( pipeline_name="younium_pipeline", destination="duckdb", dataset_name="younium_data", ) load_info = pipeline.run(younium_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.


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):

import dlt data = dlt.pipeline("younium_pipeline").dataset() sessions_df = data.subscriptions.df() print(sessions_df.head())

SQL (DuckDB example):

SELECT * FROM younium_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

import dlt data = dlt.pipeline("younium_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.


What destinations can I load Younium data to?

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

DestinationExample value
DuckDB (local, default)"duckdb"
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

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


Next steps

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

  • data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
  • dlthub-platform — Deploy, schedule, and monitor your pipeline in production.
uv run dlthub ai toolkit install data-exploration uv run dlthub ai toolkit install dlthub-platform

Was this page helpful?

Community Hub

Need more dlt context for Younium?

Request dlt skills, commands, AGENT.md files, and AI-native context.