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Features:

  • Real-time BigQuery dataset and table monitoring
  • Interactive visualizations (time series, histograms, box plots)
  • Sample data viewing and CSV export
  • Comprehensive data profiling using ydata-profiling
  • Auto-refresh capability
  • Data freshness indicators

Features:
- Real-time BigQuery dataset and table monitoring
- Interactive visualizations (time series, histograms, box plots)
- Sample data viewing and CSV export
- Comprehensive data profiling using ydata-profiling
- Auto-refresh capability
- Data freshness indicators

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
@SIVerilyDP SIVerilyDP requested review from a team as code owners January 15, 2026 22:52
@SIVerilyDP SIVerilyDP marked this pull request as draft January 15, 2026 22:52
Sowmya Ingarsal and others added 5 commits January 15, 2026 23:08
The volume mount needs to point to the repository root (../..) so that
the startup scripts at ./startupscript/ are accessible to the container.

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
Changes:
- Set build context to repository root for proper volume mounting
- Remove user switching to match remoteUser: root in devcontainer.json
- Add sudo for streamlit user
- Update CMD to reference app from /workspace path
- Fix requirements.txt copy path for new build context

This should resolve permission issues and path resolution problems.

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
This version uses python:3.11-slim pre-built image and installs
dependencies at runtime to help debug build issues.

Use this version if bq-monitoring-dashboard fails to build.

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
Simple BigQuery SQL interface for executing queries in Workbench.

Features:
- Text editor for SQL queries
- Execute SELECT statements
- View results in interactive table
- Query statistics (bytes processed, slot time)
- CSV download
- Schema viewer
- Helper queries to list datasets and tables
- Support for cross-project queries (shared datasets)

Uses runtime dependency installation to avoid build issues.
Simple configuration based on working example app.

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
This app uses the EXACT structure of the working 'example' app but
runs a SQL query interface instead of Jupyter.

Key points:
- Copied from src/example/ (proven to work in Workbench)
- Same port (8888), same network config, same startup scripts
- Only change: runs Streamlit SQL app instead of Jupyter
- Runtime dependency installation (no Dockerfile build)

Since the example app deploys successfully, this should too.

Co-Authored-By: Claude Sonnet 4.5 <[email protected]>
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