Add BigQuery Monitoring Dashboard custom app#300
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SIVerilyDP wants to merge 6 commits intoverily-src:masterfrom
Draft
Add BigQuery Monitoring Dashboard custom app#300SIVerilyDP wants to merge 6 commits intoverily-src:masterfrom
SIVerilyDP wants to merge 6 commits intoverily-src:masterfrom
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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 Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
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 <noreply@anthropic.com>
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 <noreply@anthropic.com>
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 <noreply@anthropic.com>
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 <noreply@anthropic.com>
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 <noreply@anthropic.com>
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