Musoq: SQL-like Querying for Various Data Sources

Musoq is a tool that lets developers and IT professionals query different data sources using SQL-like syntax, without needing to import data into a database first. It’s designed for scenarios where you need to analyze files, directories, archives, or other data sources quickly and efficiently.

What Musoq Does

  • Provides SQL-like querying capability for files, directories, archives, and other data sources
  • Supports various data formats including CSV, JSON, flat files, and more
  • Enables AI-assisted analysis through integration with models like GPT and Llama
  • Offers both CLI and programmatic access
  • Works on Windows and Linux, with planned MacOS support

Practical Applications

Musoq is particularly useful for:

  • Analyzing source code and solution files
  • Exploring file systems and comparing directories
  • Processing CSV and JSON data
  • Extracting information from archives
  • Analyzing images and text using AI models
  • Querying CAN DBC files
  • Processing system data and logs

Current State

Musoq focuses on handling small to medium-sized datasets efficiently. While it uses SQL-like syntax, it intentionally deviates from strict SQL standards when it benefits user experience. The project prioritizes:

  • Quick, ad-hoc data querying
  • User-friendly syntax over strict standards
  • Read-only operations
  • Continuous improvement based on real-world usage

Getting Started

The fastest way to try Musoq is through the CLI tool. The CLI provides immediate access to Musoq’s querying capabilities and supports multiple output formats including Raw, CSV, JSON, and Interpreted JSON.

For detailed documentation, examples, and implementation details, please visit this GitHub repository.