code-complexity-analyzer 1.0.0

A comprehensive Python code complexity analyzer

====================

4. README.md

====================

Code Complexity Analyzer

A comprehensive Python package for analyzing code complexity, performance metrics, and code quality without external dependencies.

Features

🔍 Comprehensive Analysis

• Time and Space Complexity estimation
• Cyclomatic Complexity calculation
• Halstead Metrics
• Maintainability Index
• Code smell detection
• Security issue identification

⚡ Easy to Use

• Simple file-based analysis
• Directory analysis for entire projects
• No external dependencies
• Rich formatted output

🛠️ Detailed Metrics

• Function-level analysis
• Class-level analysis
• Import dependency tracking
• Line counting (logical, comments, blank)

Installation

pip install code-complexity-analyzer

Quick Start

Basic Usage

import code_analyzer

# Analyze a single file
code_analyzer.analyze_file('main.py')

# Quick analysis with minimal output
code_analyzer.quick_analyze('main.py')

# Analyze entire directory
code_analyzer.analyze_directory('src/')

Advanced Usage

from code_analyzer import CodeAnalyzer

# Create analyzer instance
analyzer = CodeAnalyzer()

# Analyze file and get metrics object
metrics = analyzer.analyze_file('main.py', print_report=False)

# Access specific metrics
print(f"Time Complexity: {metrics.time_complexity}")
print(f"Space Complexity: {metrics.space_complexity}")
print(f"Maintainability Index: {metrics.maintainability_index}")

# Check for issues
if metrics.code_smells:
    print("Code smells detected:", metrics.code_smells)

Usage Examples

In your config.py or analysis script:

# config.py
import code_analyzer

# Analyze your main application file
code_analyzer.analyze_file('main.py')

# Analyze specific modules
code_analyzer.analyze_file('utils.py')
code_analyzer.analyze_file('models.py')

# Or analyze entire project
code_analyzer.analyze_directory('src/')

For project quality assessment:

# quality_check.py
import code_analyzer

# List of files to analyze
files_to_analyze = [
    'main.py',
    'database.py',
    'api.py',
    'utils.py'
]

print("🔍 Running code quality analysis...")
for file_path in files_to_analyze:
    print(f"\n📁 Analyzing: {file_path}")
    code_analyzer.analyze_file(file_path)

Metrics Explained

Complexity Metrics

• Time Complexity: Estimated Big O notation for algorithm performance
• Space Complexity: Estimated memory usage complexity
• Cyclomatic Complexity: Measures code branching and decision points
• Maintainability Index: Overall code maintainability score (0-100)

Halstead Metrics

• Vocabulary: Number of distinct operators and operands
• Length: Total number of operators and operands
• Volume: Information content of the code
• Difficulty: How difficult the code is to understand
• Effort: Mental effort required to understand the code

Code Quality Indicators

• Code Smells: Common anti-patterns and issues
• Security Issues: Potential security vulnerabilities
• Function Metrics: Per-function analysis including complexity and parameters
• Class Metrics: Per-class analysis including methods and attributes

Output Example

🔍 ======================================================================
📊 PYTHON CODE COMPLEXITY ANALYSIS REPORT
🔍 ======================================================================
📁 File: main.py
📂 Path: /path/to/main.py

📈 BASIC METRICS:
  📏 Lines of Code: 150
  💻 Logical Lines: 120
  💬 Comment Lines: 20
  📄 Blank Lines: 10

⚡ COMPLEXITY METRICS:
  ⏱️  Time Complexity: O(n²)
  💾 Space Complexity: O(n)
  🔄 Cyclomatic Complexity: 8
  🛠️  Maintainability Index: 65.5

🔧 FUNCTION ANALYSIS:
  📝 bubble_sort:
    📏 Lines: 8
    ⚙️  Parameters: 1
    🔄 Complexity: 3
    🔁 Recursive: No
    📚 Has Docstring: Yes

💡 RECOMMENDATIONS:
  💡 Code quality looks good! 🎉

Requirements

• Python 3.7+
• No external dependencies (uses only built-in Python libraries)

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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

Support

If you encounter any issues or have questions, please file an issue on the GitHub repository.

---

Made with ❤️ for better code quality