Welcome to your new dbt project!

Installation

The following tutorial assumes you're already familiar with git and command line usage.

Getting the code to your local machine

1. Fork this github repository into your local account

2. Copy it to your local machine: git clone https://github.com/your_account_name/econ250_2025.git

gcloud authentication

To run queries from your command line, you'll first need to install gcloud utility.

Follow the instructions here: https://cloud.google.com/sdk/docs/install. After installation you should have gcloud command available for running in the terminal.

Now, try to authenticate with your kse email using the following command:

gcloud auth application-default login \
  --scopes=https://www.googleapis.com/auth/bigquery,\
https://www.googleapis.com/auth/drive.readonly,\
https://www.googleapis.com/auth/iam.test,\
https://www.googleapis.com/auth/cloud-platform

Now, when you run the following commands something similar should be response:

$ gcloud auth list

     Credentialed Accounts
ACTIVE  ACCOUNT
*       o_omelchenko@kse.org.ua

To set the active project, run the following:

gcloud config set project econ250-2025

venv and libraries

Prerequisites: having Python installed on your machine. Following instructions are for Linux or WSL; if you'd like to run Windows - please refer to the documentation below.

# change directory to the one you just copied from github
cd econ250_2025 

# create and activate venv
python3 -m venv env 
source env/bin/activate

pip install -r requirements.txt

If everything is installed correctly, you should run the following commands successfully:

$ dbt --version

Core:
  - installed: 1.9.3
  - latest:    1.9.3 - Up to date!

Plugins:
  - bigquery: 1.9.1 - Up to date!

For more detailed reference, refer to the official documentation here:

• https://docs.getdbt.com/docs/core/pip-install
• https://docs.getdbt.com/docs/core/connect-data-platform/bigquery-setup#local-oauth-gcloud-setup

Adjusting the configuration

You'll need to specify your own dataset to save your models to. To do so, navigate to the profiles.yml in the root directory of the project, and replace o_omelchenko with your bigquery dataset name with which you have been working previously.

Final check

Try running the following command:

• dbt run

If everything is set up well, you will see similar output:

❯ dbt run
01:18:56  Running with dbt=1.9.3
01:18:57  Registered adapter: bigquery=1.9.1
01:18:57  Found 2 models, 4 data tests, 491 macros
01:18:57  
01:18:57  Concurrency: 2 threads (target='dev')
01:18:57  
01:19:00  1 of 2 START sql table model o_omelchenko.my_first_dbt_model ................... [RUN]
01:19:04  1 of 2 OK created sql table model o_omelchenko.my_first_dbt_model .............. [CREATE TABLE (2.0 rows, 0 processed) in 4.44s]
01:19:04  2 of 2 START sql view model o_omelchenko.my_second_dbt_model ................... [RUN]
01:19:06  2 of 2 OK created sql view model o_omelchenko.my_second_dbt_model .............. [CREATE VIEW (0 processed) in 2.13s]
01:19:06  
01:19:06  Finished running 1 table model, 1 view model in 0 hours 0 minutes and 9.64 seconds (9.64s).

If you have any troubles with installation, please contact the course instructor (Oleh Omelchenko) in slack for assist.