README.md

sample-dbt

A starter for setting up dbt test cases.

Requirements:

• Docker
• dbt
• Python

Getting started

Unless otherwise specified, run all commands from the repo root.

1. Set up Postgres. We use the pagila database.

   docker pull postgres
   
   # start (add -d before the last 'postgres' to run in background)
   docker run --name postgres -p 5432:5432 -e POSTGRES_PASSWORD=secret postgres

2. Ingest sample data into the database

   # enter psql shell
   docker exec -it postgres psql -U postgres

   Once in shell, run

   CREATE DATABASE pagila;
   \q # quit

   Now, run the ingestion SQL scripts:

   # schema objects
   cat ./db/pagila-schema.sql | docker exec -i postgres psql -U postgres -d pagila
   # data
   cat ./db/pagila-data.sql | docker exec -i postgres psql -U postgres -d pagila

   To confirm ingestion, enter psql shell again (same command as before) and run

   # connect to database
   \c pagila
   # list tables
   \dt

3. Set up dbt (order matters!):

   # create ~/.dbt directory to copy profiles.yml 
   mkdir ~/.dbt
   # copy profiles.yml to ~/.dbt/
   cp profiles.yml ~/.dbt/
   # execute transforms
   dbt run --profiles-dir .
   
   # generate ./target/sources.json
   dbt source snapshot-freshness
   
   # generate ./target/catalog.json and ./target/manifest.json
   dbt docs generate

4. Post-process generated files (so diffs are manageable).

   python process_generated.py