Python에서 예외 처리를 구현하는 모범 사례

Writing effective exception handling code is essential for creating robust and maintainable applications.
Below are some best practices for writing exception handling code in Python:

1. Catch Only What You Can Handle

Be specific:

• Catch specific exceptions rather than using a broad except clause.
• This ensures that only the exceptions you expect and know how to handle are caught.

try: # Code that might raise an exception except ValueError as e: print(f"Value error occurred: {e}")

2. Avoid Bare except: Clauses

Catch specific exceptions:

• Avoid using except: without specifying an exception type.
• This can catch unexpected errors and make debugging difficult.

try: # Code that might raise an exception except Exception as e: # Catch all exceptions if necessary print(f"An error occurred: {e}")

3. Use try-except-else-finally Blocks

• try: Place the code that might raise an exception here.
• except: Handle exceptions in this block.
• else: Execute this block if no exception was raised in the try block.
• finally: Execute this block regardless of whether an exception was raised, often used for cleanup.

try: # Code that might raise an exception except ValueError as e: print(f"Value error: {e}") else: print("No exceptions occurred.") finally: print("This will always be executed.")

4. Log Exceptions

• Use the logging module to log exceptions.
• Logging helps diagnose issues in production without revealing errors to end users.

import logging logging.basicConfig(level=logging.ERROR) try: # Code that might raise an exception except Exception as e: logging.error(f"An error occurred: {e}")

5. Re-raise Exceptions When Necessary

• If you catch an exception but can't fully handle it, consider re-raising it so that it can be handled elsewhere.

try: # Code that might raise an exception except ValueError as e: logging.error(f"Value error: {e}") raise # Re-raise the exception

6. Use Context Managers for Resource Management

• Use context managers (with statement) to manage resources like files, sockets, or database connections.
• This ensures that resources are properly released even if an exception is raised.

with open('file.txt', 'r') as file: content = file.read()

7. Graceful Degradation

-Instead of allowing your application to crash, provide fallback mechanisms or user-friendly error messages.

• For example, if a configuration file is missing, you might use default settings instead.

try: with open('config.json', 'r') as file: config = json.load(file) except FileNotFoundError: print("Config file not found, using defaults.") config = {"default": "value"}

8. Avoid Swallowing Exceptions

• Don't catch exceptions without taking any action.
• Ignoring exceptions can hide bugs and make the application behave unpredictably.

try: # Code that might raise an exception except Exception as e: pass # Bad practice - you're ignoring the error

9. Document Exceptions

• Use docstrings to document the exceptions that your functions can raise.
• This helps other developers understand what exceptions to expect and how to handle them.

def divide(a, b): """ Divides two numbers. :param a: Numerator. :param b: Denominator. :return: The result of the division. :raises ZeroDivisionError: If the denominator is zero. """ if b == 0: raise ZeroDivisionError("Cannot divide by zero.") return a / b

10. Use Custom Exceptions When Appropriate

• Create custom exceptions to represent specific error conditions in your application.
• This can make your code more readable and easier to maintain.

class InvalidInputError(Exception): """Exception raised for invalid inputs.""" pass def process_input(value): if not isinstance(value, int): raise InvalidInputError("Input must be an integer.") return value * 2

11. Test Exception Handling

• Write tests to ensure that your exception handling works as expected.
• Use frameworks like unittest or pytest to test both normal and exceptional cases.

def test_divide(): assert divide(10, 2) == 5 with pytest.raises(ZeroDivisionError): divide(10, 0)

12. Avoid Overusing Exceptions

Use exceptions for exceptional cases:

• Exceptions should be used for unexpected conditions, not as a regular control flow mechanism.
• For example, avoid using exceptions to handle predictable conditions like the end of a loop.

# Bad practice: using exceptions for control flow try: while True: value = next(iterator) except StopIteration: pass # End of iteration

13. Chain Exceptions for Context

• Python allows you to chain exceptions to preserve the original context when raising a new exception.
• Use from to link related exceptions.

try: result = process_input(input_value) except InvalidInputError as e: raise ValueError("Failed to process input") from e

By following these best practices, you can write more robust, maintainable, and readable exception handling code that gracefully manages errors and enhances your application's reliability.

Resoures

• Python's Official Documentation on Exception Handling
• Python's logging Module Documentation
• PEP 8 - Style Guide for Python Code (for general coding practices including exceptions)
• Real Python - Exception Handling

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