Wasabi Python API Docs | dltHub

Wasabi Account Control API is a RESTful JSON API that enables partners to create and manage sub‑accounts, generate S3 key sets, query utilization and invoices, and manage account profiles. The REST API base URL is https://api.wasabi.com and All requests require the Wasabi Account Control API secret key in the Authorization header..

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 Wasabi data in under 10 minutes.

---

What data can I load from Wasabi?

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

---

How do I authenticate with the Wasabi API?

Authentication uses a Wasabi Account Control API secret key provided by Wasabi. Include the secret API key in the Authorization HTTP header for each request.

1. Get your credentials

1. Sign in to the Wasabi Control Account (partner portal). 2) Navigate to the Account Control / API Keys section or contact Wasabi support to generate a new API keyset (primary and secondary keys). 3) Save the secret API key securely and use it in the Authorization header. Rotate keys via the rotation endpoints when needed.

2. Add them to .dlt/secrets.toml

Copy
[sources.wasabi_account_control_source]
api_key = "your_wac_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.

---

How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

Copy
uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

Copy
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:

Copy
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 Wasabi 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:

Copy
python wasabi_account_control_pipeline.py

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

Copy
Pipeline wasabi_account_control_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset wasabi_account_control_data
The duckdb destination used duckdb:/wasabi_account_control.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

Copy
dlt pipeline wasabi_account_control_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.

---

Python pipeline example

This example loads accounts and utilizations from the Wasabi API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

Copy
import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def wasabi_account_control_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.wasabi.com",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "accounts", "endpoint": {"path": "v1/accounts", "data_selector": "accounts"}},
            {"name": "utilizations", "endpoint": {"path": "v1/accounts/{account_number}/utilizations", "data_selector": "utilizations"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="wasabi_account_control_pipeline",
        destination="duckdb",
        dataset_name="wasabi_account_control_data",
    )
    load_info = pipeline.run(wasabi_account_control_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.

---

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):

Copy
import dlt

data = dlt.pipeline("wasabi_account_control_pipeline").dataset()
sessions_df = data.accounts.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM wasabi_account_control_data.accounts LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("wasabi_account_control_pipeline").dataset()
data.accounts.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

---

What destinations can I load Wasabi 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.

---

Troubleshooting

Authorization failures

If you receive 401 Unauthorized or 403 Forbidden, verify that the Authorization header contains the correct Wasabi Account Control API key and that the key has not been revoked. Check for accidental whitespace or missing header. If compromised, rotate keys and contact Wasabi support.

Rate limits and throttling

The API may enforce rate limits; if you receive 429 Too Many Requests, implement exponential backoff and retry. Check response headers for rate‑limit related metadata if available.

Pagination and date filters

Many list endpoints support query parameters (for example utilizations accept ?from=YYYY-MM-DD&to=YYYY-MM-DD). If responses are paginated, inspect the response object for common pagination keys (e.g., next, limit, offset) and iterate accordingly. Use date filters to narrow large result sets.

Key rotation and overlapping keys

Wasabi supports rolling‑key management (primary/secondary). When rotating keys, ensure both old and new keys are valid during transition. Use the rotation endpoints documented to rotate keys safely.

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

---

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.

Copy
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