Fivestars Python API Docs | dltHub

Fivestar is a Drupal module that provides a five‑star rating widget and related rating fields for entities. The REST API base URL is https://{your_drupal_site} and Authentication is configured per Drupal site; common methods include session cookie, HTTP Basic, or OAuth2 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 Fivestars data in under 10 minutes.

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What data can I load from Fivestars?

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

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How do I authenticate with the Fivestars API?

Requests must include whichever authentication the Drupal site requires—session cookie, HTTP Basic credentials, or an OAuth2 Bearer token. The appropriate header (Cookie, Authorization) is sent with each request.

1. Get your credentials

1. Log into the Drupal admin UI as an administrator.
2. Enable the core REST module (and optionally REST UI for UI configuration).
3. Install and enable an authentication plugin such as Basic Auth (rest_basic_auth) or OAuth2 (simple_oauth).
4. Navigate to Configuration → Web services → REST and enable the desired resources (e.g., node, comment) and select the authentication method.
5. Create a user account that will be used for API access and assign it the required permissions (e.g., "Access content via REST").
6. For Basic Auth, note the username and password. For OAuth2, generate a client ID/secret and obtain an access token via the token endpoint.
7. Use the obtained credentials in your dlt pipeline configuration.

2. Add them to .dlt/secrets.toml

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[sources.fivestars_source]
token = "your_access_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.

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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 Fivestars 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 fivestars_pipeline.py

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

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Pipeline fivestars_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset fivestars_data
The duckdb destination used duckdb:/fivestars.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 fivestars_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 node and comment from the Fivestars 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 fivestars_source(token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{your_drupal_site}",
            "auth": {
                "type": "bearer",
                "token": token,
            },
        },
        "resources": [
            {"name": "node", "endpoint": {"path": "node"}},
            {"name": "comment", "endpoint": {"path": "comment"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="fivestars_pipeline",
        destination="duckdb",
        dataset_name="fivestars_data",
    )
    load_info = pipeline.run(fivestars_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("fivestars_pipeline").dataset()
sessions_df = data.node.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM fivestars_data.node LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("fivestars_pipeline").dataset()
data.node.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 Fivestars 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

403 Forbidden – Authentication failure

When the request lacks valid credentials or uses an unsupported auth method, Drupal returns a 403 response.

404 Not Found – Resource not enabled

If the requested endpoint has not been enabled in the REST configuration, Drupal responds with 404.

CSRF token required for state‑changing methods

POST, PATCH, DELETE requests require a valid CSRF token header (X-CSRF-Token).

Pagination

Large collections can be paginated using ?page= and ?pagesize= query parameters.

Rate limiting

Drupal sites may impose rate limits via contributed modules; exceeding limits results in a 429 response.

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