weekly-working-hours

What problem does it solve?

It ensures your working-hours dbt models build successfully on a fixed cadence and that a specific error-detection view returns zero rows, preventing broken pipelines and silent data quality regressions.

Core Features & Use Cases

• Weekly build verification: Syncs main, recreates an isolated worktree for the scheduled branch, resets the BigQuery sandbox, then runs targeted dbt model builds for the tenant.
• Custom error-detection enforcement: Executes a dedicated dbt run to materialize an error-detection view and validates that the resulting BigQuery view has row_count = 0 (not just SQL compilation).
• Safe failure handling & optional teardown: Stops immediately on build/test failures, keeps the worktree for debugging when needed, and removes the worktree on completion.

Quick Start

Run the weekly routine for weekly-working-hours (scheduled for Tuesdays at 08:00) and review the routine output for build status and the zero-row error-detection verdict.