Revision 23 as of 2005-07-12 09:52:02

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Handling Exceptions

The simplest way to handle exceptions is with a "try-except" block:

   1 (x,y) = (5,0)
   2 try:
   3   z = x/y
   4 except ZeroDivisionError:
   5   print "divide by zero"

If you wanted to examine the exception from code, you could have:

   1 (x,y) = (5,0)
   2 try:
   3   z = x/y
   4 except ZeroDivisionError, e:
   5   z = e # representation: "<exceptions.ZeroDivisionError instance at 0x817426c>"
   6 print z # output: "integer division or modulo by zero"

General Error Catching

Sometimes, you want to catch all errors that could possibly be generated, but usually you don't.In most cases, you want to be as specific as possible (CatchWhatYouCanHandle). In the first example above, if you were using a catch-all exception clause and a user presses Ctrl-C, generating a KeyboardInterrupt, you don't want the program to print "divide by zero".

However, there are some situations where it's best to catch all errors.

For example, suppose you are writing an extension module to a web service. You want the error information to output the output web page, and the server to continue to run, if at all possible. But you have no idea what kind of errors you might have put in your code.

In situations like these, you may want to code something like this:

   1 import sys
   2 try:
   3   untrusted.execute()
   4 except: # catch *all* exceptions
   5   e = sys.exc_info()[1]
   6   write_to_page( "<p>Error: %s</p>" % e )

MoinMoin software is a good example of where general error catching is good. If you write MoinMoin extension macros, and trigger an error, MoinMoin will give you a detailed report of your error and the chain of events leading up to it. Python software needs to be able to catch all errors, and deliver them to the recipient of the web page.

Finding Specific Exception Names

Standard exceptions that can be raised are detailed at:

Look to class documentation to find out what exceptions a given class can raise.

See Also:

On this wiki: WritingExceptionClasses, TracebackModule.

For general (non-Python specific) ideas about exceptions, consult ExceptionPatterns.

To Write About...


General Error Handling

In the "general error handling" section above, it says to catch all exceptions, you use the following code:

   1 import sys
   2 try:
   3   untrusted.execute()
   4 except: # catch *all* exceptions
   5   e = sys.exc_info()[1]
   6   write_to_page( "<p>Error: %s</p>" % e )

However, it originally was:

   1 try:
   2   untrusted.execute()
   3 except Exception, e:
   4   write_to_page( "<p>Error: %s</p>" % str(e) )

Someone pointed out that "except" catches more than just "except Exception, e."

Why is that the case? What is the difference?-- LionKimbro

For now (version 2.3) exception doesn't have to be inherited from Exception. Thus plain 'except:' catches all exceptions, not only system. -- MikeRovner DateTime(2004-01-19T05:49:19Z)

Getting Useful Information from an Exception

So, I've got something like:

   1 (a,b,c) = d

...and Python spits back:

ValueError: unpack list of wrong size

...and so, you naturally wonder, "Well, what was in d?"

You know- you can put a print d in there, and that works. But is there a better, more interesting way to get at that information that people know of?

Isn't it better to prevent then to remediate?


Joel Spolsky might be a great C++ programmer, and his advice on user interface design is invaluable, but Python is not C++ or Java, and his arguments about exceptions do not hold in Python.

Joel argues:

"They are invisible in the source code. Looking at a block of code, including functions which may or may not throw exceptions, there is no way to see which exceptions might be thrown and from where. This means that even careful code inspection doesn't reveal potential bugs."

I don't quiet get this argument. In a random piece of source code, there is no way to tell whether or not it will fail just by inspection. If you look at:

x = 1 result = myfunction(x)

you can't tell whether or not myfunction will fail at runtime just by inspection, so why should it matter whether it fails by crashing at runtime or fails by raising an exception?

Joel's argument that raising exceptions is just a goto in disguise is partly correct. But so are for loops, while loops, functions and methods! Like those other constructs, exceptions are gotos tamed and put to work for you, instead of wild and dangerous. You can't jump *anywhere*, only highly constrained places.

Joel also writes:

"They create too many possible exit points for a function. To write correct code, you really have to think about every possible code path through your function. Every time you call a function that can raise an exception and don't catch it on the spot, you create opportunities for surprise bugs caused by functions that terminated abruptly, leaving data in an inconsistent state, or other code paths that you didn't think about."

This is a better argument for *careful* use of exceptions, not an argument to avoid them. Or better still, it is an argument for writing code which doesn't has side-effects and implements data transactions. That's a good idea regardless of whether you use exceptions or not.

Joel's concern about multiple exit points is good advice, but it can be taken too far. Consider the following code snippet:

def myfunc(x=None):

There is no benefit in deferring returning value as myfunc does, just for the sake of having a single exit point. "Have a single exit point" is a good heuristic for many functions, but it is pointless make-work for this one. (In fact, it increases, not decreases, the chances of a bug. If you look carefully, myfunc above has such a bug.

Used correctly, exceptions in Python have more advantages than disadvantages. They aren't just for errors either: exceptions can be triggered for exceptional cases (hence the name) without needing to track (and debug) multiple special cases.

Lastly, let me argue against one of Joel's comments:

"A better alternative is to have your functions return error values when things go wrong, and to deal with these explicitly, no matter how verbose it might be. It is true that what should be a simple 3 line program often blossoms to 48 lines when you put in good error checking, but that's life, and papering it over with exceptions does not make your program more robust."

Maybe that holds true for C++. I don't know the language, and wouldn't like to guess. But it doesn't hold true for Python. This is how Joel might write a function as a C programmer:

def joels_function(args):

and then call it with:

status, msg = joels_function(args) if status == False:


This is how I would write it in Python:

def my_function(args):

and call it with:


except SomeError, msg:

# and now continue safely here...

In the case of Python, calling a function that may raise an exception is no more difficult or unsafe than calling a function that returns a status flag and a result, but writing the function itself is much easier, with fewer places for the programmer to make a mistake.

In effect, exceptions allow the Python programmer to concentrate on his actual program, rather than be responsible for building error-handling infrastructure into every function. Python supplies that infrastructure for you, in the form of exceptions.

See also: Italian translation at ManutenereLeEccezioni.

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