Template to create self-contained dev container demos of transforming data with dbt. Useful for interviews.

1. Install Docker.
2. Install VS Code and install the Dev Containers extension.
3. Open this folder in a container in VS Code.
4. Open a VS Code terminal. You should see the following prompt:

   vscode ➜ /workspace (main) $
   

   If you see it, you're now in a development container with dbt pre-installed and pre-configured!

1. Copy your CSV file into seeds/ to use it as a dbt seed.
2. Run dbt seed
3. Generate dbt schema for your seed using the following command (be sure to replace "test" with the basename of your CSV file):

   dbt run-operation generate_model_yaml --args '{"model_name": "test"}'
   

   Copy and paste the output to a new file seeds/schema.yml, replacing 'models:' with 'seeds:'. Re-generate the docs with dbt docs generate and you should now be able to see your source declaration when you refresh http://localhost:8081
4. Code your transformations as usual. Some useful references:
   • dbt Labs recommended project structure
   • dbt Labs recommended SQL style guide
5. To update docs, run dbt docs generate. The updated documentation will be available on refresh at http://localhost:8081.
6. Run the transformations with dbt run and tests with dbt test as usual.
7. Query your table data in Adminer at http://localhost:8080. Choose "PostgreSQL" as the system, leave "warehouse" as the server, and enter "postgres" as both the username and password.

Based on Microsoft's python3-postgres example.