エンジニア向けのBIツール、QuaryをBigQueryに接続して使ってみた（CLI編）

quary -h

# Usage: quary.exe [OPTIONS] <COMMAND>
#
# Commands:
#   init                 Initialize demo project with sample seeds & models inside current directory
#   compile              Validate the project structure and model references without database
#   build                Build and execute the model views/seeds against target database
#   test                 Run defined tests against target database
#   convert-dbt-project  Convert a dbt core project to a quary project and place in the specified path
#   snapshot             Execute snapshots to capture data changes over time
#   generate-sources
#   help                 Print this message or the help of the given subcommand(s)
#
# Options:
#   -p, --project-file <PROJECT_FILE>  Project file location [default: quary.yaml]
#   -e, --env-files <ENV_FILES>        .env file locations to pull env vars from [default: .env]
#   -h, --help                         Print help
#   -V, --version                      Print version

GOOGLE_APPLICATION_CREDENTIALS="./{キーファイル名}"

quary build

#   ========================================       2/2       done
# Created 1 model in the database

models:
- name: rating_mean_per_user_selected
  columns:
  - name: rating_mean
    description: rating mean per userId
  - name: userId
    description: user identifier
    tests:
    - type: unique # ここがテスト

$ quary test

# BigQuery { project_id: "{Google Cloudのプロジェクト名}", dataset_id: "ml_latest_small" }
# running tests 1
# all tests (1) were run and passed.