Stripe - Crypto Onramp Sessions Python API Docs | dltHub

Stripe is a payments platform that provides a Crypto Onramp Sessions API to create, retrieve, and list customer crypto onramp sessions. The REST API base URL is https://api.stripe.com and All requests require the secret API key using HTTP Basic authentication (key as username) or as a Bearer token..

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 - Crypto Onramp Sessions data in under 10 minutes.

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What data can I load from Stripe - Crypto Onramp Sessions?

Here are some of the endpoints you can load from Stripe - Crypto Onramp Sessions:

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How do I authenticate with the Stripe - Crypto Onramp Sessions API?

Stripe uses HTTP Basic authentication where the API secret key is provided as the username (no password) or as a Bearer token in the Authorization header.

1. Get your credentials

1. Sign in to your Stripe Dashboard.
2. Navigate to Developers → API keys.
3. Locate the Secret Key (prefixed with sk_). You may create a new restricted key if needed.
4. Copy the secret key; it will be used as the username in HTTP Basic auth or as a Bearer token.

2. Add them to .dlt/secrets.toml

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[sources.stripe_crypto_onramp_sessions_source]
api_key = "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 - Crypto Onramp Sessions 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_crypto_onramp_sessions_pipeline.py

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

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Pipeline stripe_crypto_onramp_sessions_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset stripe_crypto_onramp_sessions_data
The duckdb destination used duckdb:/stripe_crypto_onramp_sessions.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_crypto_onramp_sessions_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 crypto_onramp_sessions and crypto_onramp_session from the Stripe - Crypto Onramp Sessions 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_crypto_onramp_sessions_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.stripe.com",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "crypto_onramp_sessions", "endpoint": {"path": "v1/crypto/onramp_sessions", "data_selector": "data"}},
            {"name": "crypto_onramp_session", "endpoint": {"path": "v1/crypto/onramp_sessions/:id"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="stripe_crypto_onramp_sessions_pipeline",
        destination="duckdb",
        dataset_name="stripe_crypto_onramp_sessions_data",
    )
    load_info = pipeline.run(stripe_crypto_onramp_sessions_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_crypto_onramp_sessions_pipeline").dataset()
sessions_df = data.crypto_onramp_sessions.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM stripe_crypto_onramp_sessions_data.crypto_onramp_sessions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("stripe_crypto_onramp_sessions_pipeline").dataset()
data.crypto_onramp_sessions.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 - Crypto Onramp Sessions 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 or invalid_api_key errors, ensure you are using a valid secret key (sk_…) and that it is sent correctly via HTTP Basic auth (as the username) or in the Authorization: Bearer <secret> header. Do not use a publishable key (pk_…).

Pagination and list responses

List endpoints return an object with object: "list", a has_more boolean, and a data array. Use the starting_after, ending_before, and limit parameters (limit 1‑100) to paginate through results.

Common errors

Stripe returns structured error objects for 4xx/5xx responses. Typical codes include:

• 400: invalid parameters (e.g., unsupported region based on customer_ip_address).
• 401: invalid API key.
• 402: payment required (e.g., requires_payment).
• 429: rate limit exceeded. Check the code and message fields in the error response for details.

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