This example demonstrates how to analyze the cyclomatic complexity of Python codebases using Codegen. The script provides detailed insights into code complexity by analyzing control flow structures and providing a comprehensive report.

The script (run.py) performs the complexity analysis in several key steps:

1. Codebase Loading

   codebase = Codebase.from_repo("fastapi/fastapi")

   • Loads any Python codebase into Codegen's analysis engine
   • Works with local or remote Git repositories
   • Supports analyzing specific commits

2. Complexity Calculation

   def calculate_cyclomatic_complexity(code_block):
       complexity = 1  # Base complexity
       for statement in code_block.statements:
           if isinstance(statement, IfBlockStatement):
               complexity += 1 + len(statement.elif_statements)

   • Analyzes control flow structures (if/elif/else, loops, try/except)
   • Calculates complexity based on decision points
   • Handles nested structures appropriately

3. Function Analysis

   callables = codebase.functions + [m for c in codebase.classes for m in c.methods]
   for function in callables:
       complexity = calculate_cyclomatic_complexity(function.code_block)

   • Processes both standalone functions and class methods
   • Calculates complexity for each callable
   • Tracks file locations and function names

4. Report Generation

   print("\n📊 Cyclomatic Complexity Analysis")
   print(f"  • Total Functions: {total_functions}")
   print(f"  • Average Complexity: {average:.2f}")

   • Provides comprehensive complexity statistics
   • Shows distribution of complexity across functions
   • Identifies the most complex functions

📊 Cyclomatic Complexity Analysis
============================================================

📈 Overall Stats:
  • Total Functions: 3538
  • Average Complexity: 1.27
  • Total Complexity: 4478

🔍 Top 10 Most Complex Functions:
------------------------------------------------------------
  • jsonable_encoder                16 | fastapi/encoders.py
  • get_openapi                     13 | fastapi/openapi/utils.py
  • __init__                        12 | fastapi/routing.py
  • solve_dependencies              10 | fastapi/dependencies/utils.py
  • main                             9 | scripts/notify_translations.py
  • analyze_param                    9 | fastapi/dependencies/utils.py
  • __init__                         8 | fastapi/params.py
  • __init__                         8 | fastapi/params.py
  • main                             7 | scripts/deploy_docs_status.py
  • create_model_field               7 | fastapi/utils.py

📉 Complexity Distribution:
  • Low (1-5): 3514 functions (99.3%)
  • Medium (6-10): 21 functions (0.6%)
  • High (>10): 3 functions (0.1%)

The analyzer tracks several key metrics:

• If statements (+1)
• Elif statements (+1 each)
• Else statements (+1)
• Loops (while/for) (+1)
• Try-except blocks (+1 per except)

• Low (1-5): Generally clean and maintainable code
• Medium (6-10): Moderate complexity, may need attention
• High (>10): Complex code that should be reviewed

# Install Codegen
pip install codegen

# Run the analysis
python run.py

📊 Cyclomatic Complexity Analysis
============================================================

📈 Overall Stats:
  • Total Functions: 150
  • Average Complexity: 3.45
  • Total Complexity: 518

🔍 Top 10 Most Complex Functions:
------------------------------------------------------------
  • validate_response               12 | ...api/endpoints/auth.py
  • process_request                 10 | ...core/middleware.py
  • handle_exception                 9 | ...utils/error_handlers.py

📉 Complexity Distribution:
  • Low (1-5): 105 functions (70.0%)
  • Medium (6-10): 35 functions (23.3%)
  • High (>10): 10 functions (6.7%)

• About Cyclomatic Complexity
• Codegen Documentation

Feel free to submit issues and enhancement requests!