Yotpo Python API Docs | dltHub

Build a Yotpo-to-database pipeline in Python using dlt with AI harness support for Claude Code, Cursor, and Codex.

Last updated:

Yotpo is a marketing and eCommerce retention platform providing APIs to sync store activity, product catalogs, and review data. The REST API base URL is https://api.yotpo.com and all requests require an X-Yotpo-Token header with a generated access 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 add "dlt[hub]" and start loading Yotpo data in under 10 minutes.


What data can I load from Yotpo?

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

ResourceEndpointMethodData selectorDescription
products/core/v3/stores/{store_id}/productsGETRetrieves a list of all store products.
orders/core/v3/stores/{store_id}/ordersGETRetrieves a list of orders for the store.
collections/core/v3/stores/{store_id}/collectionsGETRetrieves a list of all store collections.
customers/core/v3/stores/{store_id}/customersGETRetrieves a list of store customers.
reviews/v1/apps/{app_key}/reviewsGETRetrieves product reviews.

How do I authenticate with the Yotpo API?

Yotpo uses access tokens generated via an OAuth-style endpoint. Authenticated requests require the 'X-Yotpo-Token' header with the generated token as its value.

1. Get your credentials

  1. Log into your Yotpo account (Reviews, Loyalty, or Visual UGC). 2. Navigate to the account menu in the bottom-left corner and select Account Settings. 3. Click on General Settings. 4. Retrieve your App Key (Store ID) from the bottom of the General Settings section. 5. To obtain your API Secret, click on the Get secret key button within the same section. A verification code will be sent to your account email. 6. Enter this code on the verification screen to reveal your API Secret. Store these credentials securely.

2. Add them to .dlt/secrets.toml

[sources.yotpo_source] secret = "REPLACE_ME"

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:

uv init uv add "dlt[hub]"

1. Install the dlt AI harness:

uv run dlthub 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:

uv run dlthub ai toolkit install rest-api-pipeline

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 Yotpo 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:

uv run python yotpo_pipeline.py

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

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

Inspect your pipeline and data:

uv run dlthub 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 /oauth/token and /v3/stores/{store_id}/products from the Yotpo API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

import dlt from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources @dlt.source def yotpo_source(secret=dlt.secrets.value): config: RESTAPIConfig = { "client": { "base_url": "https://api.yotpo.com", "auth": {"type": "api_key", "api_key": secret, "name": "X-Yotpo-Token", "location": "header"}, }, "resources": [ {"name": "products", "endpoint": {"path": "core/v3/stores/{store_id}/products", "data_selector": "products"}}, {"name": "orders", "endpoint": {"path": "core/v3/stores/{store_id}/orders", "data_selector": "orders"}} ], } yield from rest_api_resources(config) def get_data() -> None: pipeline = dlt.pipeline( pipeline_name="yotpo_pipeline", destination="duckdb", dataset_name="yotpo_data", ) load_info = pipeline.run(yotpo_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):

import dlt data = dlt.pipeline("yotpo_pipeline").dataset() sessions_df = data.products.df() print(sessions_df.head())

SQL (DuckDB example):

SELECT * FROM yotpo_data.products LIMIT 10;

In a marimo or Jupyter notebook:

import dlt data = dlt.pipeline("yotpo_pipeline").dataset() data.products.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 Yotpo data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

DestinationExample value
DuckDB (local, default)"duckdb"
PostgreSQL"postgres"
BigQuery"bigquery"
Snowflake"snowflake"
Redshift"redshift"
Databricks"databricks"
Filesystem (S3, GCS, Azure)"filesystem"

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.


Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI harness:

  • data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
  • dlthub-platform — Deploy, schedule, and monitor your pipeline in production.
uv run dlthub ai toolkit install data-exploration uv run dlthub ai toolkit install dlthub-platform

Was this page helpful?

Community Hub

Need more dlt context for Yotpo?

Request dlt skills, commands, AGENT.md files, and AI-native context.