Improve Code Readability and Understanding Facilitate Code Reusability Across Projects Simplify Debugging and Testing Processes Enable Modularity and Team Collaboration Reduce Duplication (DRY Principle).pptx
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Improve Code Readability and Understanding Facilitate Code Reusability Across Projects Simplify Debugging and Testing Processes Enable Modularity and Team Collaboration Reduce Duplication (DRY Principle).pptx
2. Presentation Agenda
Why Good Functions Matter
Core Principles of Design
Documentation & Type Hinting
Testing for Reliability
Best Practices Summary
3. Why Good Functions Matter
• Improve Code Readability and Understanding
• Facilitate Code Reusability Across Projects
• Simplify Debugging and Testing Processes
• Enable Modularity and Team Collaboration
• Reduce Duplication (DRY Principle)
4. Core Principles of Design
• Single Responsibility Principle (SRP)
• Each function should do one thing and do it well.
• Clarity and Simplicity
• Easy to understand at a glance, avoid unnecessary complexity.
• Pure Functions (where applicable)
• For same inputs, always produce same outputs and no side effects.
• Appropriate Naming
• Names should clearly convey purpose and behavior.
• Parameter Management
• Limit parameters, use meaningful names, consider default values.
5. Documentation & Type Hinting
• Docstrings
• Explain what the function does, its arguments, and
what it returns.
• Essential for understanding public APIs.
• Type Hinting (PEP 484)
• Specify expected types for arguments and return
values.
• Improves readability and enables static analysis
tools.
• Catches potential bugs before runtime.
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6. Testing for Reliability
• Unit Tests
• Test individual functions in isolation.
• Ensure each function behaves as expected for various inputs.
• Use frameworks like `unittest` or `pytest`.
• Edge Cases
• Test functions with unusual or boundary inputs (e.g., empty lists, zero, negative numbers).
• Regression Testing
• Rerun tests after code changes to ensure existing functionality isn't broken.
7. Best Practices Summary
• Keep functions short and focused.
• Avoid global variables within functions.
• Handle errors gracefully (e.g., using exceptions).
• Return values rather than printing directly (unless the function's purpose is I/O).
• Refactor complex logic into smaller, simpler functions.
8. Conclusion & Q&A
• Well-designed functions are the bedrock of robust and scalable Python applications.
• Invest time in planning and documenting your functions.
• Continuous testing ensures reliability and eases future development.
• "The art of programming is the art of organizing complexity." - Edsger W. Dijkstra
