Welcome to ML Code Smell Detector’s documentation!

ML Code Smell Detector is a Python package that helps identify potential issues and bad practices in machine learning code. It includes detectors for framework-specific smells, Hugging Face-related smells, and general machine learning smells.

Contents:

• Installation
  • Requirements
• Usage
  • Command-line Interface
  • Options
  • Output
  • Use Cases
  • CI/CD Integration
• Features
  • Framework-Specific Smells
  • General ML Smells
  • Hugging Face-Specific Smells
• API Reference
  • Detectors
• Detectors
  • Framework-Specific Smell Detector
  • Hugging Face Smell Detector
  • General ML Smell Detector
• Contributing
  • Setting Up
  • Running Tests
  • Building Docs
  • Adding a Detector
  • Code Style
  • Submitting Changes
• Changelog
  • 0.1.2 (2026)
  • 0.1.1 (2026)
  • 0.1.0 (2024)

Features

• Framework-Specific Smell Detector: Detects smells related to Pandas, NumPy, Scikit-learn, TensorFlow, and PyTorch

• Hugging Face Smell Detector: Identifies best practices for using the Hugging Face Transformers library

• General ML Smell Detector: Detects common machine learning code smells

For a detailed list of all features, please see the Features page.

Quick Start

Install the package:

pip install ml-code-smell-detector

Analyze a Python file:

ml_smell_detector analyze path/to/your/file.py

For more detailed usage instructions, see the Usage page.

Indices and tables

• Index

• Module Index

• Search Page