Recharge Payments Python API Docs | dltHub

Recharge is a subscription commerce platform providing a REST API to manage subscriptions, customers, orders, charges, products, and related resources. The REST API base URL is https://api.rechargeapps.com and all requests require an X-Recharge-Access-Token header (store API 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 Recharge Payments data in under 10 minutes.

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What data can I load from Recharge Payments?

Here are some of the endpoints you can load from Recharge Payments:

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How do I authenticate with the Recharge Payments API?

Authentication uses an API token provided in the X-Recharge-Access-Token header; also include X-Recharge-Version to select API version (e.g. 2021-11).

1. Get your credentials

1. Sign into your Recharge store admin (or partner dashboard).
2. Go to Developers / API or Generate API tokens (see Recharge docs).
3. Create a store API token and copy the token value.
4. Use the token in the X-Recharge-Access-Token header for API calls.

2. Add them to .dlt/secrets.toml

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[sources.recharge_payments_source]
api_key = "your_recharge_store_api_token"

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 Recharge Payments 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 recharge_payments_pipeline.py

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

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Pipeline recharge_payments_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset recharge_payments_data
The duckdb destination used duckdb:/recharge_payments.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 recharge_payments_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 customers from the Recharge Payments 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 recharge_payments_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.rechargeapps.com",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "subscriptions", "endpoint": {"path": "subscriptions", "data_selector": "subscriptions"}},
            {"name": "customers", "endpoint": {"path": "customers", "data_selector": "customers"}}
        ],
    }
    yield from rest_api_resources(config)


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

SQL (DuckDB example):

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SELECT * FROM recharge_payments_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("recharge_payments_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 Recharge Payments 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 get 401/403, verify X-Recharge-Access-Token header contains the store API token and that requests are over HTTPS. Include X-Recharge-Version if required by your implementation.

Pagination and missing total count

Use cursor pagination (next_cursor / previous_cursor fields returned on list responses). As of 2021-11 the API does not provide total record counts; do not rely on page numbers for deep pagination.

Rate limits and errors

The API uses standard HTTP status codes. 422 is returned for invalid filter values (e.g. non-integer ids). Handle 429/5xx with exponential backoff. Validate query params (limit max 250).

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