Exception Handling Examples

Python Error Handling Best Practices

These notes cover best practices for handling errors in Python. The goal is to write robust and user-friendly code that gracefully handles unexpected situations.

Key Concepts:

try...except blocks: The fundamental mechanism for handling exceptions.

try:
    # Code that might raise an exception
    result = 10 / 0
except ZeroDivisionError:
    print("Error: Cannot divide by zero.")
except TypeError:
    print("Error: Invalid data type.")
except Exception as e: #Catch all other exceptions
    print(f"An unexpected error occurred: {e}")
else: #Executes if no exception is raised
    print(f"Result: {result}")
finally: #Always executes, regardless of exceptions
    print("This always runs.")

Specific vs. General Exceptions: It’s best to catch specific exceptions first, then use a general Exception clause to catch anything you haven’t explicitly handled. This improves code readability and helps pinpoint the source of errors. Avoid bare except: blocks, as they can mask unexpected problems.
Logging Errors: Instead of just printing error messages to the console (which might be missed or unhelpful in production environments), use a logging library (like the built-in logging module) to record errors with timestamps, severity levels, and other relevant information. Python Logging
Raising Custom Exceptions: Create custom exceptions to handle application-specific error conditions. This improves code clarity and maintainability.

class InvalidInputError(Exception):
    pass

def process_data(data):
    if not isinstance(data, int):
        raise InvalidInputError("Input must be an integer.")
    # ... rest of the function ...

Context Managers (with statement): Useful for managing resources that need to be properly released (e.g., files, network connections). The with statement ensures that resources are cleaned up even if exceptions occur.

with open("myfile.txt", "r") as f:
    contents = f.read()
    # Process file contents

Defensive Programming: Write code that anticipates potential problems and handles them gracefully. This includes input validation, checking for null values, and handling edge cases.
Testing: Thorough testing is crucial for identifying and addressing potential error handling issues. Unit tests should include scenarios that trigger various exceptions to ensure your error handling logic works as expected. Python Unit Testing

Related Notes:

Python Error Handling Best Practices

Carson West

Exception Handling Examples

Python Error Handling Best Practices