Stripe - Subscriptions Python API Docs | dltHub

Stripe is a payment processing platform that provides APIs to create and manage recurring subscriptions and billing. The REST API base URL is https://api.stripe.com and All requests require a Bearer secret API key for authentication.

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 Stripe - Subscriptions data in under 10 minutes.

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What data can I load from Stripe - Subscriptions?

Here are some of the endpoints you can load from Stripe - Subscriptions:

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How do I authenticate with the Stripe - Subscriptions API?

Stripe uses HTTP Basic authentication (secret key as username) or an Authorization: Bearer <SECRET_KEY> header for all requests.

1. Get your credentials

1. Sign in to the Stripe Dashboard (https://dashboard.stripe.com).
2. Navigate to Developers → API keys.
3. Copy the Secret key (starts with sk_test_ or sk_live_) for server‑side requests.
4. Keep the secret key private; use test keys in development and live keys in production.

2. Add them to .dlt/secrets.toml

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[sources.stripe_subscriptions_source]
secret = "sk_test_your_secret_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 Stripe - Subscriptions 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 stripe_subscriptions_pipeline.py

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

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Pipeline stripe_subscriptions_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset stripe_subscriptions_data
The duckdb destination used duckdb:/stripe_subscriptions.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 stripe_subscriptions_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 subscription from the Stripe - Subscriptions 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 stripe_subscriptions_source(secret=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.stripe.com",
            "auth": {
                "type": "bearer",
                "token": secret,
            },
        },
        "resources": [
            {"name": "subscriptions", "endpoint": {"path": "v1/subscriptions", "data_selector": "data"}},
            {"name": "subscription", "endpoint": {"path": "v1/subscriptions/:id"}}
        ],
    }
    yield from rest_api_resources(config)


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

SQL (DuckDB example):

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SELECT * FROM stripe_subscriptions_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("stripe_subscriptions_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 Stripe - Subscriptions 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 that you are using a valid Stripe Secret Key (starts with sk_test_ or sk_live_) and that it is sent in the Authorization header as Bearer <SECRET_KEY> or via HTTP Basic with the secret as the username. Do not use publishable keys (pk_…) for server‑side calls.

Rate limits and 429 responses

Stripe may return 429 Too Many Requests when request limits are exceeded. Implement exponential back‑off and retries for idempotent GET requests. Respect the Retry-After header when present.

Pagination

List endpoints (e.g., GET /v1/subscriptions) return an object with object: "list", has_more (boolean) and data (array). Use starting_after / ending_before cursor parameters and limit to paginate through results.

Common error responses

• 400 Bad Request – invalid parameters or malformed request.
• 401 Unauthorized – missing or invalid API key.
• 403 Forbidden – insufficient permissions for the provided key.
• 404 Not Found – resource ID does not exist.
• 429 Too Many Requests – rate limited; back off and retry.

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