Good Practices for User Task Development#

When developing user tasks for KAPPA-Automate, following best practices can help ensure that your tasks are efficient, maintainable, and effective. Here are some good practices to consider:

  1. Modular Code Structure: Organize your code into functions and classes to promote reusability and readability. This makes it easier to maintain and update your user tasks.

  2. Error Handling: Implement robust error handling to manage exceptions gracefully. This ensures that your user tasks can handle unexpected situations without crashing.

  3. Logging: Use logging to track the execution of your user tasks. This can help with debugging and monitoring the performance of your tasks.

  4. Documentation: Document your code thoroughly. Include docstrings for functions and classes, and provide comments where necessary to explain complex logic.

  5. Performance Optimization: Be mindful of the performance of your user tasks, especially when processing large datasets. Optimize algorithms and data handling to improve efficiency. Process 100K points at a time and not the whole data at once. See the programming_patterns for more details.

  6. Use of SDK Features: Leverage the features provided by the KAPPA-Automate SDK to simplify your code and enhance functionality.

  7. Version Control: Use version control systems (like Git) to manage changes to your codebase. This allows you to track changes, collaborate with others, and revert to previous versions if needed.

  8. Security Considerations: Ensure that sensitive information (like API keys or credentials) is handled securely. Avoid hardcoding such information in your code. Use Kubernetes secrets and then it will be accesible as os.environ[‘my_var’].

  9. Code Quality Tools: Use static analysis tools to maintain code quality:

    • mypy: Use mypy for static type checking to catch type-related errors before runtime. Add type hints to your functions and variables to improve code clarity and catch potential bugs early.

    • flake8: Use flake8 to enforce PEP 8 style guidelines and catch common programming errors. This helps maintain consistent code formatting and identifies potential issues like unused imports or undefined variables.

Common Pitfalls and Anti-Patterns#

When developing user tasks, be aware of these common pitfalls and practices to avoid:

  1. Hardcoded Values: Avoid hardcoding configuration values, file paths, or credentials directly in your code. Use Kubernetes secrets and then it will be accesible as os.environ[‘my_var’].

  2. Global Variables: Minimize the use of global variables as they can make code harder to understand, test, and maintain. Use function parameters and return values instead.

  3. Ignoring Exceptions: Don’t use bare except: clauses that catch all exceptions without handling them appropriately. This can hide important errors and make debugging difficult.

  4. Inefficient Data Processing: Don’t load entire large datasets into memory at once. Process data in chunks or use streaming approaches when dealing with large files.

  5. Poor Error Messages: Avoid generic or unclear error messages. Provide specific, actionable error messages that help users understand what went wrong and how to fix it.

  6. Copy-Paste Programming: Resist the urge to copy and paste code blocks. Instead, create reusable functions or classes to avoid code duplication and maintenance issues.

  7. Ignoring Code Style: Don’t ignore PEP 8 style guidelines. Consistent code formatting makes your code more readable and professional.

  8. Infinite Loops: Be cautious with loops to avoid infinite loops that can trigger your user task. Avoid having a user task that is an input of another user task that is also an input of the first one, you will create an infinite loop of executions.

By adhering to these best practices, you can create user tasks that are reliable, efficient, and easy to maintain, ultimately enhancing the overall functionality of KAPPA-Automate.