Medium Link
- git
- Python 3.9 or higher
- Docker Desktop
- Clone this repository
git clone https://github.com/snhou/jaffle-shop-dbt-demo.git
- Change into the
jaffle_shop
directory
- Install virtual environment
- Enter into venv
- Update pip
python3 -m pip install --upgrade pip
- Install dependencies
python3 -m pip install -r requirements.txt
- Open Docker Desktop and run docker-compose.yaml
- Set up a
profiles.yml
called jaffle_shop
to connect to a data warehouse
jaffle_shop:
target: dev
outputs:
dev:
type: postgres
host: localhost
user: dbt
password: dbt
port: 5432
dbname: dbt
schema: jaffle-shop-classic
threads: 4
- Ensure your profile is setup correctly from the command line:
- it will generate a
.user.yml
file
- Load the CSVs with the demo data set. This materializes the CSVs as tables in your target schema. Note that a typical dbt project does not require this step since dbt assumes your raw data is already in your warehouse.
- Run the models:
- Test the output of the models:
- Generate documentation for the project:
- View the documentation for the project: