Smartsuite Python API Docs | dltHub

SmartSuite is a REST API platform for retrieving and managing workspace metadata and table (app) records (CRUD) and files. The REST API base URL is https://app.smartsuite.com/api/v1 and All requests require an API key (Token) and workspace Account‑Id 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 Smartsuite data in under 10 minutes.

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What data can I load from Smartsuite?

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

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How do I authenticate with the Smartsuite API?

Authenticate by sending header "Authorization: Token YOUR_API_KEY" and header "Account-Id: YOUR_WORKSPACE_ID" on every request.

1. Get your credentials

1. Log in to SmartSuite. 2) Click your profile and go to "API Keys" or follow "Generating an API Key" in the Help Center. 3) Create/generate an API Key for your user. 4) Note your Workspace ID (the 8‑character segment in the app URL after login, e.g. https://app.smartsuite.com/{WORKSPACE_ID}/). 5) Store the API key and Account‑Id securely.

2. Add them to .dlt/secrets.toml

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[sources.smartsuite_source]
api_key = "your_api_key_here"
account_id = "your_workspace_id"

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 Smartsuite 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 smartsuite_pipeline.py

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

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Pipeline smartsuite_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset smartsuite_data
The duckdb destination used duckdb:/smartsuite.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 smartsuite_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 records_list and applications from the Smartsuite 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 smartsuite_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://app.smartsuite.com/api/v1",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "records_list", "endpoint": {"path": "applications/{app_id}/records/list/", "data_selector": "records"}},
            {"name": "tables", "endpoint": {"path": "applications/", "data_selector": "items"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="smartsuite_pipeline",
        destination="duckdb",
        dataset_name="smartsuite_data",
    )
    load_info = pipeline.run(smartsuite_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("smartsuite_pipeline").dataset()
sessions_df = data.records_list.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM smartsuite_data.records_list LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("smartsuite_pipeline").dataset()
data.records_list.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 Smartsuite 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 403 responses, verify the header format is exactly: Authorization: Token YOUR_API_KEY and Account-Id: YOUR_WORKSPACE_ID. API keys inherit the generating user's permissions; ensure the key is active and the user has access to the workspace.

Rate limits and throttling

Standard rate is 5 requests/sec per user. Overage drops to 2 req/sec; excessive monthly usage may be denied (hard limit). On 429 or reduced throughput, back off and retry with exponential backoff.

Pagination notes

Metadata endpoints and list endpoints use pagination with parameters limit and offset. Responses commonly return: { "total":..., "offset":..., "limit":..., "items": [...] } for metadata. Record list endpoints (POST records/list/) return a top‑level records key for the returned records.

File upload/download quirks

File endpoints require multipart/form-data for uploads and use the same token + Account-Id headers. File downloads may return binary data and metadata in headers (X-File-Name, Content-Type, Content-Length).

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