Recurly Python API Docs | dltHub

Recurly is a subscription management and billing platform providing a REST API for managing accounts, subscriptions, invoices, transactions, plans, coupons, and related billing resources. The REST API base URL is https://v3.recurly.com and All requests require HTTP Basic authentication using a private API key (API key as username, blank password)..

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 Recurly data in under 10 minutes.

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What data can I load from Recurly?

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

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How do I authenticate with the Recurly API?

Recurly uses HTTP Basic Auth where the API key is provided as the username and the password is left blank. Requests must include Accept: application/json and Content-Type: application/json headers. The Authorization header will be 'Basic <base64(api_key:)>'.

1. Get your credentials

1. Sign in to your Recurly admin console.
2. Navigate to Configuration (or Account Settings) → API Credentials (or Developers → API keys / REST API keys).
3. Create a new REST API key if none exists.
4. Copy the private API key; use it as the HTTP Basic Auth username and leave the password empty.

2. Add them to .dlt/secrets.toml

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[sources.recurly_source]
api_key = "your_recurly_private_api_key_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 Recurly 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 recurly_pipeline.py

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

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Pipeline recurly_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset recurly_data
The duckdb destination used duckdb:/recurly.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 recurly_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 accounts and subscriptions from the Recurly 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 recurly_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://v3.recurly.com",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "accounts", "endpoint": {"path": "accounts"}},
            {"name": "subscriptions", "endpoint": {"path": "subscriptions"}}
        ],
    }
    yield from rest_api_resources(config)


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

SQL (DuckDB example):

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SELECT * FROM recurly_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("recurly_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 Recurly 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 you receive 401 Unauthorized, verify the API key is correct and included using HTTP Basic auth where the API key is the username and the password is empty. Ensure the Authorization header is 'Basic <base64(api_key:)>'.

Rate limiting

Recurly may return 429 Too Many Requests when rate limits are exceeded. Respect the Retry-After header and implement exponential backoff.

Pagination

Many list endpoints use cursor‑based pagination with Link headers or query parameters (limit, cursor). Follow 'next' links in response headers to page through results.

Validation and 4xx errors

For invalid requests, Recurly returns 4xx responses (422 Unprocessable Entity for validation errors, 404 for not found). Inspect the JSON error body for 'error' or 'details' fields describing validation failures.

Server errors

For 5xx responses, retry with backoff and contact Recurly support if persistent.

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