Code Quality Analyzer

A comprehensive Python code quality analysis tool that detects code smells, architectural smells, and structural issues in Python projects. This tool helps developers identify potential maintainability issues and technical debt early in the development process.

Features

Code Smell Detection

• Long methods and large classes
• Primitive obsession and data clumps
• Feature envy and inappropriate intimacy
• Message chains and middle man classes
• Duplicate code and speculative generality
• Temporary fields and lazy classes
• Switch statements and cyclic dependencies

Architectural Smell Detection

• Hub-like dependencies
• Scattered functionality
• Cyclic dependencies
• God objects
• Unstable dependencies
• Improper API usage
• Redundant abstractions

Structural Smell Detection

• High cyclomatic complexity
• Deep inheritance trees
• High coupling (CBO)
• Low cohesion (LCOM)
• Excessive fan-in/fan-out
• Large file sizes
• Complex conditional structures

Installation

Prerequisites

• Python 3.7 or higher
• pip package manager

Install from source

Download the repository
cd  "the_repository"
pip install -e .

Usage

Command Line Interface

Basic usage:

analyze_code_quality /path/to/project --config code_quality_config.yaml

Analyze specific smell types:

# Analyze only code smells
analyze_code_quality /path/to/project --type code

# Analyze only architectural smells
analyze_code_quality /path/to/project --type architectural

# Analyze only structural smells
analyze_code_quality /path/to/project --type structural

Additional options:

analyze_code_quality /path/to/project \
    --config custom_config.yaml \
    --output report \
    --debug

Configuration

The tool uses a YAML configuration file to set thresholds for various metrics. You can customize these thresholds by creating your own configuration file based on the provided template:

code_smells:
  LONG_METHOD_LINES:
    value: 45
    explanation: "Methods longer than this many lines may be too complex"
  LARGE_CLASS_METHODS:
    value: 15
    explanation: "Classes with more than this many methods may have too many responsibilities"
  # ... other thresholds

Output Formats

The tool generates reports in multiple formats:

• Text report (default): Detailed human-readable analysis
• CSV report: Structured data for further processing
• Log file: Detailed analysis process and any errors encountered

Example Output

Code Quality Analysis Report
============================

Structural Smells:
-------------------
- High Cyclomatic Complexity: Method 'process_data' has complexity of 15
  Line: 45
  File: src/processor.py
  Severity: high

Code Smells:
------------
- Large Class: Class 'DataManager' has 20 methods
- Feature Envy: Method 'calculate_metrics' makes 5 calls to 'Statistics' class

Architectural Smells:
---------------------
- Cyclic Dependency: Detected cycle between modules: module_a -> module_b -> module_c -> module_a

Summary:
--------
Total Structural Smells: 5
Total Code Smells: 8
Total Architectural Smells: 3

Contributing

Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.

Development Setup

1. Clone the repository
2. Create a virtual environment:

   python -m venv venv
   source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install development dependencies:

   pip install -e ".[dev]"

4. Run tests:

   pytest tests/

License

This project is licensed under the MIT License - see the LICENSE file for details.

Acknowledgments

• Based on Martin Fowler's work on code smells and refactoring
• Inspired by various software quality metrics and best practices
• Uses abstract syntax tree analysis for Python code

Troubleshooting

Common Issues

1. ParseError in Python Files

   • Ensure the Python files being analyzed are valid Python syntax
   • Check file encoding (tool supports utf-8, utf-8-sig, latin1, cp1252)

2. Missing Dependencies

   • Ensure all required packages are installed:

     pip install -r requirements.txt

Debug Mode

Enable debug mode for detailed logging:

analyze_code_quality /path/to/project --debug

Support

For bug reports and feature requests, please use the GitHub issue tracker.

Documentation

The documentation is built using Sphinx and hosted on Read the Docs.

Building the Documentation Locally

1. Install the documentation requirements:

pip install -r docs/requirements.txt