Yelp-leads Python API Docs | dltHub

Yelp Leads API is a partner API that provides access to Yelp-generated leads (conversations) and their interaction events so partners can read, respond to, and manage leads for subscribed businesses. The REST API base URL is https://api.yelp.com/v3 and all requests require an OAuth2 Bearer token (partner OAuth 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 Yelp-leads data in under 10 minutes.

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What data can I load from Yelp-leads?

Here are some of the endpoints you can load from Yelp-leads:

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How do I authenticate with the Yelp-leads API?

The Leads API uses OAuth2 bearer tokens. Include the partner OAuth access token in the Authorization header as: Authorization: Bearer <OAUTH_TOKEN>. Some partner flows may use business-user OAuth tokens in combination with partner credentials for business-scoped access.

1. Get your credentials

1. Become a Yelp advertising or listing-management reseller partner (contact business.yelp.com/partners or data/listings pages). 2) Request Leads API access via Yelp partner onboarding (access is disabled by default). 3) Once approved, create/manage API credentials in Yelp Developer/Manage API Access (https://www.yelp.com/developers or the Manage API Access link in the docs). 4) Obtain an OAuth2 access token for your partner application (authorization code or other OAuth flow described in Yelp docs). 5) Use the token as the Bearer token in requests. Note: access is restricted—non-partners will not be granted credentials; Zapier integration is recommended for non-partners.

2. Add them to .dlt/secrets.toml

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[sources.yelp_leads_source]
oauth_token = "your_oauth_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 Yelp-leads 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 yelp_leads_pipeline.py

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

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Pipeline yelp_leads_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset yelp_leads_data
The duckdb destination used duckdb:/yelp_leads.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 yelp_leads_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 leads_get and lead_events from the Yelp-leads 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 yelp_leads_source(oauth_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.yelp.com/v3",
            "auth": {
                "type": "bearer",
                "token": oauth_token,
            },
        },
        "resources": [
            {"name": "leads_get", "endpoint": {"path": "v3/leads/{lead_id}"}},
            {"name": "lead_events", "endpoint": {"path": "v3/leads/{lead_id}/events"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="yelp_leads_pipeline",
        destination="duckdb",
        dataset_name="yelp_leads_data",
    )
    load_info = pipeline.run(yelp_leads_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("yelp_leads_pipeline").dataset()
sessions_df = data.lead_events.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM yelp_leads_data.lead_events LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("yelp_leads_pipeline").dataset()
data.lead_events.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 Yelp-leads 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 Unauthorized, verify the Authorization header: Authorization: Bearer <OAUTH_TOKEN>. Ensure the OAuth token is valid and not expired and that your partner credentials include Leads API access. Business-user OAuth tokens grant access only to businesses that the business user can manage; subscribing with partner API-key and using a business user's token can result in 403/404 if the user lacks access.

Access and 404 errors

The Leads API is restricted to Yelp partner accounts. Requests to endpoints you don't have access to will return 403/404. A 404 when fetching a lead may indicate the lead doesn't exist or the current OAuth user/token does not have access to that business's leads.

Rate limiting (429)

Default rate limit: 5 requests per second per client per endpoint. Exceeding limits returns 429. Contact Yelp to request configurable higher limits for approved partners.

Pagination and ordering quirks

Lead events are returned ordered as they appear on Yelp (the latest event is the last item). Use query parameters limit (default 20), older_than_cursor, and newer_than_cursor to paginate through event arrays. Initial calls return recent events and provide cursor values to page.

Common HTTP errors

400 Bad Request — malformed parameters. 401 Unauthorized — invalid/expired token. 403 Forbidden — token lacks required access. 404 Not Found — resource doesn't exist or token lacks access. 429 Too Many Requests — rate limit exceeded. 500/502/503 — server errors; retry with backoff.

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