Python Try-Except: When to Avoid It

Python’s try-except block is a powerful tool for handling exceptions and preventing a program from crashing due to runtime errors. However, if try-except blocks are used excessively or inappropriately, they can create more issues than they resolve.
This blog mentions some situations when they should be avoided to maintain good coding practices.

Hiding Bugs

One of the major risks of using try-except blocks is that they can hide serious bugs. Using broad try blocks might catch unexpected exceptions, masking critical issues in your code. This makes debugging difficult by obscuring the true source of errors, which delays problem-solving.

try:
    process_data(data)
except Exception:
    pass     # Dangerous: As it Hides any error that might occur

Best Practice
Instead of a generic catch-all, specify the exceptions you expect, which clarifies intent and reduces the risk of overlooking important errors.

try:
    process_data(data)
except ValueError:  # Handling a specific exception type.
    print("Invalid value")
except TypeError:
    print("Type mismatch")

Reducing Code Clarity and Quality

Another risk of using try-except blocks is that they can make code hard to read and maintain. If you frequently expect exceptions, it's usually a sign that your code could be improved by adding precise checks before attempting operations that might fail.

try:
    value = dictionary['key']
except KeyError:
    value = default_value

Best Practice
A more readable approach would be to check for the key's presence before attempting to access it:

value = dictionary.get('key', default_value)

Performance Concerns

Using try-except blocks can be costly in terms of performance, especially if the try block covers a significant portion of your code or is placed inside a loop. In performance-critical applications, relying too much on exceptions rather than proper condition checks can degrade the program’s efficiency.

for i in range(10000):
    try:
        process_data(i)
    except Exception:
        continue

Best Practice
Handle checks outside the exception mechanism whenever possible. This practice minimizes the reliance on exception handling for control flow and focuses on managing specific, less frequent exceptions. This approach enhances performance and code clarity by distinguishing between normal processing and error handling.

for i in range(10000):
    if can_process(i):  # Pre-check to ensure it can be processed
        try:
            process_data(i)
        except SpecificException as e:  # Catch only specific, less frequent exceptions
            print(f"Error processing item: {e}")
    else:
        print("It cannot be processed")  # Handle cases where the item shouldn't be processed