Load LoyaltyLion data in Python using dltHub
Build a LoyaltyLion-to-database or-dataframe pipeline in Python using dlt with automatic Cursor support.
In this guide, we'll set up a complete LoyaltyLion data pipeline from API credentials to your first data load in just 10 minutes. You'll end up with a fully declarative Python pipeline based on dlt's REST API connector, like in the partial example code below:
Example code
Why use dltHub Workspace with LLM Context to generate Python pipelines?
- Accelerate pipeline development with AI-native context
- Debug pipelines, validate schemas and data with the integrated Pipeline Dashboard
- Build Python notebooks for end users of your data
- Low maintenance thanks to Schema evolution with type inference, resilience and self documenting REST API connectors. A shallow learning curve makes the pipeline easy to extend by any team member
- dlt is the tool of choice for Pythonic Iceberg Lakehouses, bringing mature data loading to pythonic Iceberg with or without catalogs
What you’ll do
We’ll show you how to generate a readable and easily maintainable Python script that fetches data from loyaltylion_migration’s API and loads it into Iceberg, DataFrames, files, or a database of your choice. Here are some of the endpoints you can load:
- Program Management: Endpoints to manage loyalty programs, including creating pages and managing rewards.
- Cart Management: Endpoints to add or remove items in the cart, and manage cart states.
- WebView Sessions: Endpoints to create and manage webview sessions for the LoyaltyLion interface.
- Email Management: Endpoints to manage customer email subscriptions and rewards.
You will then debug the LoyaltyLion pipeline using our Pipeline Dashboard tool to ensure it is copying the data correctly, before building a Notebook to explore your data and build reports.
Setup & steps to follow
💡Before getting started, let's make sure Cursor is set up correctly:
- We suggest using a model like Claude 3.7 Sonnet or better
- Index the REST API Source tutorial: https://dlthub.com/docs/dlt-ecosystem/verified-sources/rest_api/ and add it to context as @dlt rest api
- Read our full steps on setting up Cursor
Now you're ready to get started!
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⚙️ Set up
dltWorkspaceInstall dlt with duckdb support:
pip install dlt[workspace]Initialize a dlt pipeline with LoyaltyLion support.
dlt init dlthub:loyaltylion_migration duckdbThe
initcommand will setup the necessary files and folders for the next step. -
🤠 Start LLM-assisted coding
Here’s a prompt to get you started:
PromptPlease generate a REST API Source for LoyaltyLion API, as specified in @loyaltylion_migration-docs.yaml Start with endpoints create-page and and skip incremental loading for now. Place the code in loyaltylion_migration_pipeline.py and name the pipeline loyaltylion_migration_pipeline. If the file exists, use it as a starting point. Do not add or modify any other files. Use @dlt rest api as a tutorial. After adding the endpoints, allow the user to run the pipeline with python loyaltylion_migration_pipeline.py and await further instructions. -
🔒 Set up credentials
Authentication can be achieved using an API key linked to a specific program within LoyaltyLion. The API key must have the required scopes to access various endpoints.
To get the appropriate API keys, please visit the original source at https://www.loyaltylion.com/. If you want to protect your environment secrets in a production environment, look into setting up credentials with dlt.
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🏃♀️ Run the pipeline in the Python terminal in Cursor
python loyaltylion_migration_pipeline.pyIf your pipeline runs correctly, you’ll see something like the following:
Pipeline loyaltylion_migration load step completed in 0.26 seconds 1 load package(s) were loaded to destination duckdb and into dataset loyaltylion_migration_data The duckdb destination used duckdb:/loyaltylion_migration.duckdb location to store data Load package 1749667187.541553 is LOADED and contains no failed jobs -
📈 Debug your pipeline and data with the Pipeline Dashboard
Now that you have a running pipeline, you need to make sure it’s correct, so you do not introduce silent failures like misconfigured pagination or incremental loading errors. By launching the dlt Workspace Pipeline Dashboard, you can see various information about the pipeline to enable you to test it. Here you can see:
- Pipeline overview: State, load metrics
- Data’s schema: tables, columns, types, hints
- You can query the data itself
dlt pipeline loyaltylion_migration_pipeline show -
🐍 Build a Notebook with data explorations and reports
With the pipeline and data partially validated, you can continue with custom data explorations and reports. To get started, paste the snippet below into a new marimo Notebook and ask your LLM to go from there. Jupyter Notebooks and regular Python scripts are supported as well.
import dlt data = dlt.pipeline("loyaltylion_migration_pipeline").dataset() # get reate-pag table as Pandas frame data.reate-pag.df().head()
Running into errors?
The Admin API is intended for data movement, while the Headless API is for building custom interfaces. Rate limits apply, and certain endpoints require specific scopes. The SDK must be integrated into your store's template, and the loyaltylion.init method must only be called once per page load.