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Sibi Toolkit: A collection of tools for Data Analysis/Engineering.

Project description

SibiFlux

Production-grade Data Engineering & Agentic AI Ecosystem.

SibiFlux is a unified engine for hybrid data loading, self-healing distributed operations, and native AI agent interfaces via the Model Context Protocol (MCP).

🚀 Quick Start

Quick Start Workflow

  1. Initialize Project

    uv run sibi-flux init my-project --app
    
  2. Configure Environment

    uv run sibi-flux env --env-file .env
    
  3. Enter Project

    cd my-project
    
  4. Create Application

    uv run sibi-flux create-app my-app
    
  5. Run Global Data Workflow

    uv run sibi-flux dc workflow --force
    
  6. Propose App Datacubes

    uv run sibi-flux propose-cubes <db_domain> my-app
    
  7. Generate App Datacubes

    uv run sibi-flux create-cubes my-app
    

🔥 Key Features

  • Automated Workflow: One command (dc workflow) to introspect DBs, map schemas, whitelisting, and generate Python Datacubes.
  • Hybrid Loading: Seamlessly merge partitioned Parquet archives with live SQL data.
  • Agent Native: Expose any Datacube as an MCP resource for AI agents.
  • Resilient: Self-healing Dask clusters and robust artifact orchestration.

📚 Documentation

Full docs in src/docs/index.md.

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