I know that I can do:
try:
# do something that may fail
except:
# do this if ANYTHING goes wrong
I can also do this:
try:
# do something that may fail
except IDontLikeYouException:
# say please
except YouAreTooShortException:
# stand on a ladder
But if I want to do the same thing inside two different exceptions, the best I can think of right now is to do this:
try:
# do something that may fail
except IDontLikeYouException:
# say please
except YouAreBeingMeanException:
# say please
Is there any way that I can do something like this (since the action to take in both exceptions is to say please):
try:
# do something that may fail
except IDontLikeYouException, YouAreBeingMeanException:
# say please
Now this really won't work, as it matches the syntax for:
try:
# do something that may fail
except Exception, e:
# say please
So, my effort to catch the two distinct exceptions doesn't exactly come through.
Is there a way to do this?
From Python Documentation:
An except clause may name multiple exceptions as a parenthesized tuple, for example
except (IDontLikeYouException, YouAreBeingMeanException) as e:
pass
Or, for Python 2 only:
except (IDontLikeYouException, YouAreBeingMeanException), e:
pass
Separating the exception from the variable with a comma will still work in Python 2.6 and 2.7, but is now deprecated and does not work in Python 3; now you should be using as.
How do I catch multiple exceptions in one line (except block)
Do this:
try:
may_raise_specific_errors():
except (SpecificErrorOne, SpecificErrorTwo) as error:
handle(error) # might log or have some other default behavior...
The parentheses are required due to older syntax that used the commas to assign the error object to a name. The as keyword is used for the assignment. You can use any name for the error object, I prefer error personally.
Best Practice
To do this in a manner currently and forward compatible with Python, you need to separate the Exceptions with commas and wrap them with parentheses to differentiate from earlier syntax that assigned the exception instance to a variable name by following the Exception type to be caught with a comma.
Here's an example of simple usage:
import sys
try:
mainstuff()
except (KeyboardInterrupt, EOFError): # the parens are necessary
sys.exit(0)
I'm specifying only these exceptions to avoid hiding bugs, which if I encounter I expect the full stack trace from.
This is documented here: https://docs.python.org/tutorial/errors.html
You can assign the exception to a variable, (e is common, but you might prefer a more verbose variable if you have long exception handling or your IDE only highlights selections larger than that, as mine does.) The instance has an args attribute. Here is an example:
import sys
try:
mainstuff()
except (KeyboardInterrupt, EOFError) as err:
print(err)
print(err.args)
sys.exit(0)
Note that in Python 3, the err object falls out of scope when the except block is concluded.
Deprecated
You may see code that assigns the error with a comma. This usage, the only form available in Python 2.5 and earlier, is deprecated, and if you wish your code to be forward compatible in Python 3, you should update the syntax to use the new form:
import sys
try:
mainstuff()
except (KeyboardInterrupt, EOFError), err: # don't do this in Python 2.6+
print err
print err.args
sys.exit(0)
If you see the comma name assignment in your codebase, and you're using Python 2.5 or higher, switch to the new way of doing it so your code remains compatible when you upgrade.
The suppress context manager
The accepted answer is really 4 lines of code, minimum:
try:
do_something()
except (IDontLikeYouException, YouAreBeingMeanException) as e:
pass
The try, except, pass lines can be handled in a single line with the suppress context manager, available in Python 3.4:
from contextlib import suppress
with suppress(IDontLikeYouException, YouAreBeingMeanException):
do_something()
So when you want to pass on certain exceptions, use suppress.
From Python documentation -> 8.3 Handling Exceptions:
A try statement may have more than one except clause, to specify
handlers for different exceptions. At most one handler will be
executed. Handlers only handle exceptions that occur in the
corresponding try clause, not in other handlers of the same try
statement. An except clause may name multiple exceptions as a
parenthesized tuple, for example:
except (RuntimeError, TypeError, NameError):
pass
Note that the parentheses around this tuple are required, because
except ValueError, e: was the syntax used for what is normally
written as except ValueError as e: in modern Python (described
below). The old syntax is still supported for backwards compatibility.
This means except RuntimeError, TypeError is not equivalent to
except (RuntimeError, TypeError): but to except RuntimeError as
TypeError: which is not what you want.
If you frequently use a large number of exceptions, you can pre-define a tuple, so you don't have to re-type them many times.
#This example code is a technique I use in a library that connects with websites to gather data
ConnectErrs = (URLError, SSLError, SocketTimeoutError, BadStatusLine, ConnectionResetError)
def connect(url, data):
#do connection and return some data
return(received_data)
def some_function(var_a, var_b, ...):
try: o = connect(url, data)
except ConnectErrs as e:
#do the recovery stuff
blah #do normal stuff you would do if no exception occurred
NOTES:
If you, also, need to catch other exceptions than those in the
pre-defined tuple, you will need to define another except block.
If you just cannot tolerate a global variable, define it in main()
and pass it around where needed...
One of the way to do this is..
try:
You do your operations here;
......................
except(Exception1[, Exception2[,...ExceptionN]]]):
If there is any exception from the given exception list,
then execute this block.
......................
else:
If there is no exception then execute this block.
and another way is to create method which performs task executed by except block and call it through all of the except block that you write..
try:
You do your operations here;
......................
except Exception1:
functionname(parameterList)
except Exception2:
functionname(parameterList)
except Exception3:
functionname(parameterList)
else:
If there is no exception then execute this block.
def functionname( parameters ):
//your task..
return [expression]
I know that second one is not the best way to do this, but i'm just showing number of ways to do this thing.
As of Python 3.11 you can take advantage of the except* clause that is used to handle multiple exceptions.
PEP-654 introduced a new standard exception type called ExceptionGroup that corresponds to a group of exceptions that are being propagated together. The ExceptionGroup can be handled using a new except* syntax. The * symbol indicates that multiple exceptions can be handled by each except* clause.
For example, you can handle multiple exceptions
try:
raise ExceptionGroup('Example ExceptionGroup', (
TypeError('Example TypeError'),
ValueError('Example ValueError'),
KeyError('Example KeyError'),
AttributeError('Example AttributeError')
))
except* TypeError:
...
except* ValueError as e:
...
except* (KeyError, AttributeError) as e:
...
For more details see PEP-654.
There is a simple scenario that I seem to encounter quite often: I invoke a function that can raise any number of exceptions. I won't do anything different if it is one exception versus another, I just want to log the exception information and either re-raise the exception or indicate in some other way that something didn't go as planned (such as returning None), otherwise proceed normally. So I use some form of the exception handling shown below.
Please note:
Imagine his code is running in a daemon that processes messages, so it needs to keep running, even if one of the messages causes some kind of exception.
I am aware that there is a rule of thumb that it is not generally advisable to catch a generic Exception because that may hide specfic errors that should be handled differently. (This is true in other languages as well.) This case is different because I don't care what exception is raised, the handling is the same.
Is there a better way?
def my_func(p1):
retval = None
try:
valx = other_func1(p1)
except Exception as ex:
log.error('other_func1 failed. {}: {}'.format(type(ex).__name__, ex))
else:
retval = ...
return retval
Is there a better way?
Doubt it, Python has these built-in Base Exception Classes so creating something on your own is really just being redundant. If you handle everything in the same way, generalizing in your except with Exception is most likely the best way to tackle this.
Small caveat here: Exception isn't the most general you can get, from the documentation:
All built-in, non-system-exiting exceptions are derived from this class. All user-defined exceptions should also be derived from this class.
So, it won't catch all exceptions:
In [4]: try:
...: raise SystemExit
...: except Exception as b:
...: print("Catch All")
To exit: use 'exit', 'quit', or Ctrl-D.
An exception has occurred, use %tb to see the full traceback.
SystemExit
Which, do note, is of course something you should want. A SystemExit should exit. But, if some edge case requires it, to also catch system-exiting exceptions you can use BaseException which is as loose as you can get with exception matching:
In [2]: try:
...: raise SystemExit
...: except BaseException as b:
...: print("Catch All")
Catch All
Use it at your own discretion but, it probably makes zero sense to actually use it, and this case does not seem to require it. I just mentioned it because it is the most general you can get. I believe the way you have done it is more than sufficient.
That looks like a fine way to catch them if you're handling them all the same way. If you want to check what kind of exception was raised, you can use the built-in function type and compare the result to an exception class (for example, one from the list of built-in exception types):
try:
f()
except Exception as ex:
if type(ex)==ValueError:
handle_valueerror()
else:
handle_other_exception()
If you're handling them differently, use except <SpecificExceptionClass>. I'm not sure what I was thinking before.
I am writing a class in Python and part of the code deals with a server. Therefore I need to deal with exceptions like ExpiredSession or ConnectionError.
Instead of writing exception handling code for every try/except block, I have a single function in the class to deal with the exceptions. something like this (inside the class definition)
def job_a(self):
try:
do something
except Exception as e:
#maybe print the error on screen.
self.exception_handling(e)
def job_b(self):
try:
do something else
except Exception as e:
#maybe print the error on screen.
self.exception_handling(e)
def exception_handling(self,e):
if isInstanceOf(e,ExpiredSession):
#deal with expired session.
self.reconnect()
if isInstanceOf(e,ConnectionError):
#deal with connection error
else:
#other exceptions
I am not sure if this kind of code would cause any problem because I haven't seen code do this. like, possible memory leak? (Now I notice the memory usage grows(though slowly) when I have more and more error/exception and eventually I have to restart the process before it eats all my memories). Not sure this is the cause.
Is it a good practice to pass exceptions to a single function?
This is a good use case for a context manager. You can see some examples of using context managers for error handling here. The contextmanager decorator allows you to write context managers concisely in the form of a single function. Here's a simple example:
class Foo(object):
def meth1(self):
with self.errorHandler():
1/0
def meth2(self):
with self.errorHandler():
2 + ""
def meth3(self):
with self.errorHandler():
# an unhandled ("unexpected") kind of exception
""[3]
#contextlib.contextmanager
def errorHandler(self):
try:
yield
except TypeError:
print "A TypeError occurred"
except ZeroDivisionError:
print "Divide by zero occurred"
Then:
>>> x = Foo()
>>> x.meth1()
Divide by zero occurred
>>> x.meth2()
A TypeError occurred
The with statement allows you to "offload" the error handling into a separate function where you catch the exceptions and do what you like with them. In your "real" functions (i.e., the functions that do the work but may raise the exceptions), you just need a with statement instead of an entire block of complicated try/except statements.
An additional advantage of this approach is that if an unforeseen exception is raised, it will propagate up normally with no extra effort:
>>> x.meth3()
Traceback (most recent call last):
File "<pyshell#394>", line 1, in <module>
x.meth3()
File "<pyshell#389>", line 12, in meth3
""[3]
IndexError: string index out of range
In your proposed solution, on the other hand, the exception is already caught in each function and the actual exception object is passed the handler. If the handler gets an unexpected error, it would have to manually reraise it (and can't even use a bare raise to do so). Using a context manager, unexpected exceptions have their ordinary behavior with no extra work required.
I have a python module containing functions and a few classes. This module is basically used as a tool-set by several of my co-workers.
I want to set-up a sort of bug reporting system where anytime someone generates an exception that I don't handle, an email will be sent with information on the exception. This way I can continually improve the robustness of my code and the help-fullness of my own error messages. Is the best way to do this to just put a try/except block around the entire module?
There are several reasons I think your approach might not be the best.
Sometimes exceptions should be thrown. For example, if I pass some stupid argument to a function, it should complain by throwing an exception. You don't want to get an email every time someone passes a string instead of an integer, etc. do you?
Besides, wrapping the entire thing in a try...except won't work, as that will only be catching exceptions that would occur during the definition of the classes/functions (when your module is loaded/imported). For example,
# Your python library
try:
def foo():
raise Exception('foo exception')
return 42
except Exception as e:
print 'Handled: ', e
# A consumer of your library
foo()
The exception is still uncaught.
I guess you can make your own SelfMailingException and subclass it. Not that I would recommend this approach.
another option:
def raises(*exception_list):
def wrap(f):
def wrapped_f(*x, **y):
try:
f(*x, **y)
except Exception as e:
if not isinstance(e, tuple(exception_list)):
print('send mail')
# send mail
raise
return wrapped_f
return wrap
usage:
#raises(MyException)
def foo():
...
I have a code for a function which is called inside another function.(Result of refactoring).
So in the called function I have a huge block of try-catch statements as.
def Called():
try:
#All statements for the function in the try block.
except A:
# Exception handler.
except B:
# Exception handler.
except A:
# Exception handler.
The problem I have is that I need to catch two exceptions of the same type (At different locations in the Called function). Which then are handled by the Calling function.
One way would be to define two try-except blocks within the Called function. But I am not understanding how the Calling function can handle two exceptions of the same type differently.
This won't work as advertised; only the first except A clause will ever get executed. What you need is either some logic inside the clause to further inspect the exception, or (if the code inside the try block permits) several try-except blocks.
Example of the former approach:
try:
something_that_might_fail()
except A as e:
if e.is_harmless():
pass
elif e.is_something_we_can_handle():
handle_it()
else:
raise # re-raise in the hope it gets handled further up the stack
I think this will work
def Called():
try:
#All statements for the function in the try block.
except A:
try:
do_someting()
except B:
try:
do_somthing_else()
except:
except A:
# Exception handler.