What's the difference between raise and raise from in Python?

In Python, both raise and raise from are used to throw exceptions, but they serve distinct purposes when it comes to exception chaining and preserving traceback details. Here’s what you need to know:

1. raise

try:
    # some code that might fail
    1 / 0
except ZeroDivisionError:
    raise ValueError("Invalid operation")

• Basic Exception: raise simply throws the specified exception.
• Traceback: Using raise in an except block preserves the stack trace of the newly raised exception, but it doesn’t explicitly link it to the original exception (though Python does show both exceptions if you don’t suppress the original).

2. raise ... from ...

try:
    1 / 0
except ZeroDivisionError as e:
    raise ValueError("Invalid operation") from e

• Explicit Exception Chaining: raise ... from ... is used to indicate that one exception was the direct cause of another. This is especially helpful if you want to clarify or transform the original exception into a more descriptive one.
• Traceback: Python’s traceback clearly shows both exceptions and labels the original one as the “cause.” This can be invaluable for debugging complex error scenarios.

Practical Example of Exception Chaining

Consider a scenario where you catch a KeyError and convert it into a CustomDataError, preserving the original details:

class CustomDataError(Exception):
    pass

data = {"foo": "bar"}

try:
    value = data["non_existent_key"]
except KeyError as original_exc:
    raise CustomDataError("Data key not found") from original_exc

In the traceback, Python will display both CustomDataError and the underlying KeyError, making the debugging process more transparent.

When to Use Which?

1. Use raise ... from ...:

   • When you want explicit chaining to show that a second exception was triggered by a particular original exception.
   • In libraries or large codebases where clarity in error handling is crucial.

2. Use raise:

   • When you simply want to pass the exception up the call stack without additional context.
   • For quick error handling where the cause is already clear or doesn’t need extra explanation.

Leveling Up Your Python Knowledge

Understanding exception handling patterns is just one piece of the puzzle. To become truly proficient in Python, check out these recommended courses from DesignGurus.io:

• Grokking Python Fundamentals
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  Ideal if you’re preparing for coding interviews and need a solid grasp of problem-solving strategies in Python.

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Final Thoughts

• raise throws an exception but doesn’t explicitly link it to a previous one.
• raise ... from ... chains exceptions, clearly showing how one exception caused another.

By making use of explicit exception chaining where it matters, you’ll write code that’s far easier to debug and maintain. Happy coding!