Lightspeed Retail Python API Docs | dltHub

Lightspeed Retail (X-Series) API is a RESTful interface for accessing retail data like products, sales, customers, and inventory. The REST API base URL is https://{domain_prefix}.retail.lightspeed.app/api/2.0/ and all requests require a Bearer token for authentication.

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 Lightspeed Retail data in under 10 minutes.

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What data can I load from Lightspeed Retail?

Here are some of the endpoints you can load from Lightspeed Retail:

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How do I authenticate with the Lightspeed Retail API?

Use OAuth 2.0 Authorization Code Grant or a Personal Token; include the token in every request with the header 'Authorization: Bearer '.

1. Get your credentials

1. Log in to the Lightspeed Retail developer portal (https://developers.retail.lightspeed.app/).
2. Register a new application to obtain a client ID and client secret.
3. Configure the redirect URI in the app settings.
4. Direct the user to the Authorization URL (https://secure.retail.lightspeed.app/connect) to authorize the app.
5. After the user authorizes, capture the authorization code from the redirect.
6. POST the code to the token endpoint (https://{domain_prefix}.retail.lightspeed.app/api/1.0/token) with client ID/secret to receive an access_token and refresh_token.
7. Store the access_token for use in the Authorization header of API calls.

Alternatively, generate a Personal Token from the account settings and use it directly as a Bearer token.

2. Add them to .dlt/secrets.toml

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[sources.lightspeed_retail_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 Lightspeed Retail 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 lightspeed_retail_pipeline.py

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

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Pipeline lightspeed_retail_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset lightspeed_retail_data
The duckdb destination used duckdb:/lightspeed_retail.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 lightspeed_retail_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 retailer and products from the Lightspeed Retail 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 lightspeed_retail_source(access_token=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://{domain_prefix}.retail.lightspeed.app/api/2.0/",
            "auth": {
                "type": "bearer",
                "access_token": access_token,
            },
        },
        "resources": [
            {"name": "retailer", "endpoint": {"path": "retailer"}},
            {"name": "products", "endpoint": {"path": "products/{id}"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="lightspeed_retail_pipeline",
        destination="duckdb",
        dataset_name="lightspeed_retail_data",
    )
    load_info = pipeline.run(lightspeed_retail_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("lightspeed_retail_pipeline").dataset()
sessions_df = data.retailer.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM lightspeed_retail_data.retailer LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("lightspeed_retail_pipeline").dataset()
data.retailer.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 Lightspeed Retail 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 Errors

• 401 Unauthorized – Occurs when the Bearer token is missing, malformed, or expired. Refresh the token using the token endpoint.

Rate Limiting

• The token endpoint returns X-RateLimit-Limit, X-RateLimit-Remaining, and X-RateLimit-Reset headers.
• Exceeding the limit results in a 429 Too Many Requests response.

Pagination

• Endpoints that return collections support page and limit query parameters. Use them to paginate through large result sets.
• The response includes total, page, and limit fields to help navigate pages.

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