Trustpilot Python API Docs | dltHub

Trustpilot is a consumer review platform and API provider that lets businesses access and manage reviews, invitations, business-units and related review metadata. The REST API base URL is https://api.trustpilot.com/v1 and public APIs use apikey header; private APIs require OAuth2 Bearer tokens..

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 Trustpilot data in under 10 minutes.

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What data can I load from Trustpilot?

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

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How do I authenticate with the Trustpilot API?

Public API endpoints accept an API key (Client ID) via an HTTP header apikey:{key}. Private/business endpoints require OAuth2 (Bearer access token) using Trustpilot's OAuth token endpoints; access tokens expire (~100 hours) and can be refreshed with refresh tokens.

1. Get your credentials

1. Sign in to Trustpilot Business and navigate to the developer/API settings page.
2. Create a new application; the system will provide a Client ID (API key) and a Client Secret.
3. For private APIs, configure an OAuth grant (e.g., client_credentials or authorization_code).
4. Use the token endpoint to exchange the client credentials for an access token (and refresh token if applicable).
5. Store the API key, secret, and any tokens securely for use in API calls.

2. Add them to .dlt/secrets.toml

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[sources.trustpilot_source]
api_key = "your_client_id_here"
api_secret = "your_client_secret_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 Trustpilot 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 trustpilot_pipeline.py

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

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Pipeline trustpilot_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset trustpilot_data
The duckdb destination used duckdb:/trustpilot.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 trustpilot_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 reviews_latest and review from the Trustpilot 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 trustpilot_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.trustpilot.com/v1",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "reviews_latest", "endpoint": {"path": "reviews/latest", "data_selector": "reviews"}},
            {"name": "review", "endpoint": {"path": "reviews/{reviewId}"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="trustpilot_pipeline",
        destination="duckdb",
        dataset_name="trustpilot_data",
    )
    load_info = pipeline.run(trustpilot_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("trustpilot_pipeline").dataset()
sessions_df = data.reviews_latest.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM trustpilot_data.reviews_latest LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("trustpilot_pipeline").dataset()
data.reviews_latest.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 Trustpilot 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 call public endpoints without apikey header or private endpoints without a valid Bearer token you'll receive 401/403. For OAuth flows, use Basic auth (Base64 client_id:client_secret) when requesting/refreshing tokens and include Authorization: Bearer <token> on private requests. Access tokens expire (~100 hours); refresh tokens expire in ~30 days.

Rate limiting and token refresh (429)

Trustpilot returns 429 for excessive requests and also when refreshing tokens too often. Back off and reuse tokens until near expiry; avoid frequent refresh calls.

Pagination and result selectors

Some endpoints (e.g., reviews/latest) return an object with a reviews array — use that key as the data selector. Single‑review endpoints return a single JSON object (no list key).

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