Chargebee Python API Docs | dltHub

Chargebee is a subscription billing and recurring payments platform providing REST APIs to manage customers, subscriptions, invoices, plans, and related billing resources. The REST API base URL is https://{site}.chargebee.com/api/v2 and all requests require HTTP Basic auth with the API key as username.

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 Chargebee data in under 10 minutes.

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What data can I load from Chargebee?

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

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How do I authenticate with the Chargebee API?

Chargebee uses HTTP Basic authentication where the API key is provided as the username and the password is blank. Requests must include an Authorization header with Basic <base64(api_key:)>.

1. Get your credentials

1. Sign in to the Chargebee dashboard. 2) Navigate to Settings → Configure Chargebee → API Keys (or Site Settings → API Keys). 3) Create a new server‑side API key or reveal an existing one. 4) Copy the key; use it as the Basic auth username for API calls (leave the password empty).

2. Add them to .dlt/secrets.toml

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[sources.chargebee_source]
api_key = "your_chargebee_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 Chargebee 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 chargebee_pipeline.py

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

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Pipeline chargebee_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset chargebee_data
The duckdb destination used duckdb:/chargebee.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 chargebee_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 Chargebee 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 chargebee_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{site}.chargebee.com/api/v2",
            "auth": {
                "type": "http_basic",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "subscriptions", "endpoint": {"path": "subscriptions", "data_selector": "subscriptions"}},
            {"name": "customers", "endpoint": {"path": "customers", "data_selector": "list"}}
        ],
    }
    yield from rest_api_resources(config)


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

SQL (DuckDB example):

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SELECT * FROM chargebee_data.subscriptions LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("chargebee_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 Chargebee 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 you are using HTTP Basic auth with the API key as the username and an empty password, and that the Authorization header is Authorization: Basic <base64(api_key:)>.

Rate limits and throttling

Chargebee enforces rate limits per site; if you receive 429 Too Many Requests, implement exponential backoff and respect the Retry-After header.

Pagination

Many list endpoints use limit and offset parameters (default limit = 10, max = 100). Responses include next_offset or offset for pagination. When a response uses a list wrapper, iterate through the list array and pass the offset to subsequent requests until no more results.

Resource wrapper variations

Some endpoints (e.g., customers when listed) return a list array where each item contains the resource keyed by name ("customer"). Other endpoints return a top‑level resource array (e.g., "subscriptions" or "plans"). Always inspect the specific endpoint response schema in the API docs for the exact JSON selector.

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