What are code debts and how to work with them?

Code debts are a metaphor for technical solutions or development practices that are an "借用" approach – they speed up development in the short term but create additional difficulties and require effort to fix in the long term.

Examples of code debts:

• Insufficient test coverage.
• Poorly designed architecture.
• Code duplication (DRY - Don't Repeat Yourself).
• Unreadable, poorly documented code.
• Use of outdated libraries or technologies.

Working with code debts:

1. Identification: Detect problematic code areas using static analysis tools, code reviews, and feedback from the team.

   // Example of using Pylint for static analysis
   // pip install pylint
   # pylint your_module.py
   

2. Prioritization: Determine the most critical debts for business and development that require immediate fixing.

3. Refactoring: Sequentially improve the code structure without changing its functionality.

   // Example of simple refactoring: extracting a function
   # Original code
   # total = 0
   # for item in items:
   #     total += calculate_price(item)
   # print(f"Total price: {total}")
   
   # After refactoring
   def calculate_total_price(items):
       total = 0
       for item in items:
           total += calculate_price(item)
       return total
   
   # print(f"Total price: {calculate_total_price(items)}")
   

4. Planning: Incorporate debt elimination tasks into regular sprints or allocate separate "refactoring sprints".

5. Automation: Use tools for automatic formatting (e.g., Black, yapf), static analysis (Pylint, flake8), and continuous integration to prevent the accumulation of new debt.

6. Creating a culture: Encourage writing quality code, conduct regular code reviews, and implement coding standards.

Managing code debts is an ongoing process that helps keep the codebase healthy and ensures sustainable project development.