Sendy Python API Docs | dltHub

Sendy is a self‑hosted email marketing platform exposing REST endpoints for subscriber, lists, brands, campaigns and (Sendy 3.0) shipping/webhook management. The REST API base URL is http://<your_sendy_installation> , https://app.sendy.nl/api and Classic Sendy uses API key in POST parameters; Sendy 3.0 hosted uses Bearer token via 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 Sendy data in under 10 minutes.

---

What data can I load from Sendy?

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

---

How do I authenticate with the Sendy API?

Classic Sendy (pre‑3.0) uses an account API key passed in POST body parameters. Sendy 3.0 (hosted) uses a Bearer token sent in the Authorization header.

1. Get your credentials

1. Classic/self‑hosted: Log into Sendy admin → Settings → copy API key.
2. Sendy 3.0 hosted: Log into https://app.sendy.nl → My Sendy → Create OAuth app for OAuth credentials or generate a Personal Access Token in account settings; follow OAuth flow to obtain access_token.

2. Add them to .dlt/secrets.toml

Copy
[sources.sendy_source]
api_key = "your_sendy_api_key_here"
# for hosted OAuth/bearer use:
# token = "your_bearer_token_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 Sendy 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 sendy_pipeline.py

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

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

Inspect your pipeline and data:

Copy
dlt pipeline sendy_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 lists and subscribe from the Sendy 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 sendy_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "http://<your_sendy_installation> , https://app.sendy.nl/api",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "lists", "endpoint": {"path": "api/lists", "data_selector": "data"}},
            {"name": "subscribe", "endpoint": {"path": "subscribe"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="sendy_pipeline",
        destination="duckdb",
        dataset_name="sendy_data",
    )
    load_info = pipeline.run(sendy_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("sendy_pipeline").dataset()
sessions_df = data.lists.df()
print(sessions_df.head())

SQL (DuckDB example):

Copy
SELECT * FROM sendy_data.lists LIMIT 10;

In a marimo or Jupyter notebook:

Copy
import dlt

data = dlt.pipeline("sendy_pipeline").dataset()
data.lists.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 Sendy 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

Authentication failures

Classic API: missing or invalid api_key returns plain‑text errors like "API key not passed" or "Invalid API key". Hosted API returns HTTP 401 with a JSON error when the Bearer token is invalid.

Response formats & selectors

Classic endpoints often return plain‑text (e.g., "true" or error strings) for subscribe/unsubscribe; they should not be treated as JSON. Sendy 3.0 responses for list‑style endpoints wrap results in a top‑level data array and include pagination fields (links, meta, current_page, total).

Rate limiting & errors

Sendy 3.0 can return 429 Too Many Requests. Hosted endpoints also return standard 4xx/5xx codes (401, 403, 404, 422, 500). Classic endpoints return plain‑text error messages such as "Some fields are missing.", "Invalid list ID.", "Email does not exist.".

Pagination

Sendy 3.0 uses paginated JSON responses with data and pagination keys (links, meta, current_page, last_page, per_page, total). Classic APIs generally return full collections without standard pagination.

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