jaffle_shop

Jaffle shop example

This example is taken from the jaffle_shop example from dbt. Here is the views file structure:

views
├── core
│   ├── customers.sql
│   └── orders.sql.jinja
├── staging
│   ├── customers.py
│   ├── orders.py
│   └── payments.py
└── tests
    └── orders_are_dated.sql

The first thing to do is create an .env file, as so:

echo "
LEA_USERNAME=max
LEA_WAREHOUSE=duckdb
LEA_DUCKDB_PATH=jaffle_shop.db
" > .env

This example uses DuckDB as the data warehouse. With lea, the convention when using DuckDB is to use a separate .db file per environment. For instance, in production, the file would be called jaffle_shop.db. In development, the file would be called jaffle_shop_max.db. The max suffix is the username from the .env file.

The following command creates the jaffle_shop_max.db file and the necessary schemas:

lea prepare

Created schema analytics
Created schema core
Created schema staging

Now you can run the views:

lea run

There are a couple of cool things:

1. The staging schema is populated using Python scripts. Each one outputs a pandas DataFrame, which lea automcatically writes to DuckDB.
2. The core.orders table is created using a Jinja SQL script. lea will automatically run the script through Jinja, and then execute the resulting SQL.

You can then run some tests:

lea test

You can also generate documentation:

lea docs

This generates a docs folder with the following structure:

docs
├── README.md
├── core
│   └── README.md
└── staging
    └── README.md

Now, if you were running in production and not in development mode, you would add a --production flag to each command:

lea prepare --production
lea run --production
lea test --production
lea docs --production