I have some code below that is meant to check if a list of lists contains an empty string. In context, the user of my application will fill out survey questions, but if they leave one of the survey questions empty, then I want to alert them that they need to go back and fill out the survey. I need to perform this check in a bunch of different places, so I thought that a class would be a good use-case to improve the readability and portability of my program.
However, I have come to learn of try-except blocks and thought maybe it would be a better place for the essence of my code. But I am having some issues converting my simple class into a try-except block, and would like to try and implement it this way if I can. However, I think what I want to do might not be appropriate for a try-test block, so I was hoping to get some feedback.
class ErrorCheck():
def __init__(self, survey_responses):
self.survey_responses = survey_responses
def check_empty(self):
for item in self.survey_responses:
if '' in item:
print('One of these is empty')
x = ErrorCheck([['abc'],[2],['apples'],['']])
x.check_empty()
The code that you're trying to implement is pretty much correct. Except for the fact that if you want to highlight an error, instead of just using a print function, use raise Exception() and in the parentheses insert a string, in your case 'One of these is empty'.
This will result in output like this:
Exception: One of these is empty
which is probably what you're looking for.
As others already pointed out, what you want do is probably raise an exception, after you raise it you can catch it in a try...except block and do something about it:
survey_responses = ['a','','c']
def check_empty(responses):
for response in responses:
if response == '':
raise Exception('Missing Answer: One or more answers are empty')
try:
check_empty(survey_responses)
except Exception as exc:
print(exc)
From time to time in Python, I see the block:
try:
try_this(whatever)
except SomeException as exception:
#Handle exception
else:
return something
What is the reason for the try-except-else to exist?
I do not like that kind of programming, as it is using exceptions to perform flow control. However, if it is included in the language, there must be a good reason for it, isn't it?
It is my understanding that exceptions are not errors, and that they should only be used for exceptional conditions (e.g. I try to write a file into disk and there is no more space, or maybe I do not have permission), and not for flow control.
Normally I handle exceptions as:
something = some_default_value
try:
something = try_this(whatever)
except SomeException as exception:
#Handle exception
finally:
return something
Or if I really do not want to return anything if an exception happens, then:
try:
something = try_this(whatever)
return something
except SomeException as exception:
#Handle exception
"I do not know if it is out of ignorance, but I do not like that
kind of programming, as it is using exceptions to perform flow control."
In the Python world, using exceptions for flow control is common and normal.
Even the Python core developers use exceptions for flow-control and that style is heavily baked into the language (i.e. the iterator protocol uses StopIteration to signal loop termination).
In addition, the try-except-style is used to prevent the race-conditions inherent in some of the "look-before-you-leap" constructs. For example, testing os.path.exists results in information that may be out-of-date by the time you use it. Likewise, Queue.full returns information that may be stale. The try-except-else style will produce more reliable code in these cases.
"It my understanding that exceptions are not errors, they should only
be used for exceptional conditions"
In some other languages, that rule reflects their cultural norms as reflected in their libraries. The "rule" is also based in-part on performance considerations for those languages.
The Python cultural norm is somewhat different. In many cases, you must use exceptions for control-flow. Also, the use of exceptions in Python does not slow the surrounding code and calling code as it does in some compiled languages (i.e. CPython already implements code for exception checking at every step, regardless of whether you actually use exceptions or not).
In other words, your understanding that "exceptions are for the exceptional" is a rule that makes sense in some other languages, but not for Python.
"However, if it is included in the language itself, there must be a
good reason for it, isn't it?"
Besides helping to avoid race-conditions, exceptions are also very useful for pulling error-handling outside loops. This is a necessary optimization in interpreted languages which do not tend to have automatic loop invariant code motion.
Also, exceptions can simplify code quite a bit in common situations where the ability to handle an issue is far removed from where the issue arose. For example, it is common to have top level user-interface code calling code for business logic which in turn calls low-level routines. Situations arising in the low-level routines (such as duplicate records for unique keys in database accesses) can only be handled in top-level code (such as asking the user for a new key that doesn't conflict with existing keys). The use of exceptions for this kind of control-flow allows the mid-level routines to completely ignore the issue and be nicely decoupled from that aspect of flow-control.
There is a nice blog post on the indispensibility of exceptions here.
Also, see this Stack Overflow answer: Are exceptions really for exceptional errors?
"What is the reason for the try-except-else to exist?"
The else-clause itself is interesting. It runs when there is no exception but before the finally-clause. That is its primary purpose.
Without the else-clause, the only option to run additional code before finalization would be the clumsy practice of adding the code to the try-clause. That is clumsy because it risks
raising exceptions in code that wasn't intended to be protected by the try-block.
The use-case of running additional unprotected code prior to finalization doesn't arise very often. So, don't expect to see many examples in published code. It is somewhat rare.
Another use-case for the else-clause is to perform actions that must occur when no exception occurs and that do not occur when exceptions are handled. For example:
recip = float('Inf')
try:
recip = 1 / f(x)
except ZeroDivisionError:
logging.info('Infinite result')
else:
logging.info('Finite result')
Another example occurs in unittest runners:
try:
tests_run += 1
run_testcase(case)
except Exception:
tests_failed += 1
logging.exception('Failing test case: %r', case)
print('F', end='')
else:
logging.info('Successful test case: %r', case)
print('.', end='')
Lastly, the most common use of an else-clause in a try-block is for a bit of beautification (aligning the exceptional outcomes and non-exceptional outcomes at the same level of indentation). This use is always optional and isn't strictly necessary.
What is the reason for the try-except-else to exist?
A try block allows you to handle an expected error. The except block should only catch exceptions you are prepared to handle. If you handle an unexpected error, your code may do the wrong thing and hide bugs.
An else clause will execute if there were no errors, and by not executing that code in the try block, you avoid catching an unexpected error. Again, catching an unexpected error can hide bugs.
Example
For example:
try:
try_this(whatever)
except SomeException as the_exception:
handle(the_exception)
else:
return something
The "try, except" suite has two optional clauses, else and finally. So it's actually try-except-else-finally.
else will evaluate only if there is no exception from the try block. It allows us to simplify the more complicated code below:
no_error = None
try:
try_this(whatever)
no_error = True
except SomeException as the_exception:
handle(the_exception)
if no_error:
return something
so if we compare an else to the alternative (which might create bugs) we see that it reduces the lines of code and we can have a more readable, maintainable, and less buggy code-base.
finally
finally will execute no matter what, even if another line is being evaluated with a return statement.
Broken down with pseudo-code
It might help to break this down, in the smallest possible form that demonstrates all features, with comments. Assume this syntactically correct (but not runnable unless the names are defined) pseudo-code is in a function.
For example:
try:
try_this(whatever)
except SomeException as the_exception:
handle_SomeException(the_exception)
# Handle a instance of SomeException or a subclass of it.
except Exception as the_exception:
generic_handle(the_exception)
# Handle any other exception that inherits from Exception
# - doesn't include GeneratorExit, KeyboardInterrupt, SystemExit
# Avoid bare `except:`
else: # there was no exception whatsoever
return something()
# if no exception, the "something()" gets evaluated,
# but the return will not be executed due to the return in the
# finally block below.
finally:
# this block will execute no matter what, even if no exception,
# after "something" is eval'd but before that value is returned
# but even if there is an exception.
# a return here will hijack the return functionality. e.g.:
return True # hijacks the return in the else clause above
It is true that we could include the code in the else block in the try block instead, where it would run if there were no exceptions, but what if that code itself raises an exception of the kind we're catching? Leaving it in the try block would hide that bug.
We want to minimize lines of code in the try block to avoid catching exceptions we did not expect, under the principle that if our code fails, we want it to fail loudly. This is a best practice.
It is my understanding that exceptions are not errors
In Python, most exceptions are errors.
We can view the exception hierarchy by using pydoc. For example, in Python 2:
$ python -m pydoc exceptions
or Python 3:
$ python -m pydoc builtins
Will give us the hierarchy. We can see that most kinds of Exception are errors, although Python uses some of them for things like ending for loops (StopIteration). This is Python 3's hierarchy:
BaseException
Exception
ArithmeticError
FloatingPointError
OverflowError
ZeroDivisionError
AssertionError
AttributeError
BufferError
EOFError
ImportError
ModuleNotFoundError
LookupError
IndexError
KeyError
MemoryError
NameError
UnboundLocalError
OSError
BlockingIOError
ChildProcessError
ConnectionError
BrokenPipeError
ConnectionAbortedError
ConnectionRefusedError
ConnectionResetError
FileExistsError
FileNotFoundError
InterruptedError
IsADirectoryError
NotADirectoryError
PermissionError
ProcessLookupError
TimeoutError
ReferenceError
RuntimeError
NotImplementedError
RecursionError
StopAsyncIteration
StopIteration
SyntaxError
IndentationError
TabError
SystemError
TypeError
ValueError
UnicodeError
UnicodeDecodeError
UnicodeEncodeError
UnicodeTranslateError
Warning
BytesWarning
DeprecationWarning
FutureWarning
ImportWarning
PendingDeprecationWarning
ResourceWarning
RuntimeWarning
SyntaxWarning
UnicodeWarning
UserWarning
GeneratorExit
KeyboardInterrupt
SystemExit
A commenter asked:
Say you have a method which pings an external API and you want to handle the exception at a class outside the API wrapper, do you simply return e from the method under the except clause where e is the exception object?
No, you don't return the exception, just reraise it with a bare raise to preserve the stacktrace.
try:
try_this(whatever)
except SomeException as the_exception:
handle(the_exception)
raise
Or, in Python 3, you can raise a new exception and preserve the backtrace with exception chaining:
try:
try_this(whatever)
except SomeException as the_exception:
handle(the_exception)
raise DifferentException from the_exception
I elaborate in my answer here.
Python doesn't subscribe to the idea that exceptions should only be used for exceptional cases, in fact the idiom is 'ask for forgiveness, not permission'. This means that using exceptions as a routine part of your flow control is perfectly acceptable, and in fact, encouraged.
This is generally a good thing, as working this way helps avoid some issues (as an obvious example, race conditions are often avoided), and it tends to make code a little more readable.
Imagine you have a situation where you take some user input which needs to be processed, but have a default which is already processed. The try: ... except: ... else: ... structure makes for very readable code:
try:
raw_value = int(input())
except ValueError:
value = some_processed_value
else: # no error occured
value = process_value(raw_value)
Compare to how it might work in other languages:
raw_value = input()
if valid_number(raw_value):
value = process_value(int(raw_value))
else:
value = some_processed_value
Note the advantages. There is no need to check the value is valid and parse it separately, they are done once. The code also follows a more logical progression, the main code path is first, followed by 'if it doesn't work, do this'.
The example is naturally a little contrived, but it shows there are cases for this structure.
See the following example which illustrate everything about try-except-else-finally:
for i in range(3):
try:
y = 1 / i
except ZeroDivisionError:
print(f"\ti = {i}")
print("\tError report: ZeroDivisionError")
else:
print(f"\ti = {i}")
print(f"\tNo error report and y equals {y}")
finally:
print("Try block is run.")
Implement it and come by:
i = 0
Error report: ZeroDivisionError
Try block is run.
i = 1
No error report and y equals 1.0
Try block is run.
i = 2
No error report and y equals 0.5
Try block is run.
Is it a good practice to use try-except-else in python?
The answer to this is that it is context dependent. If you do this:
d = dict()
try:
item = d['item']
except KeyError:
item = 'default'
It demonstrates that you don't know Python very well. This functionality is encapsulated in the dict.get method:
item = d.get('item', 'default')
The try/except block is a much more visually cluttered and verbose way of writing what can be efficiently executing in a single line with an atomic method. There are other cases where this is true.
However, that does not mean that we should avoid all exception handling. In some cases it is preferred to avoid race conditions. Don't check if a file exists, just attempt to open it, and catch the appropriate IOError. For the sake of simplicity and readability, try to encapsulate this or factor it out as apropos.
Read the Zen of Python, understanding that there are principles that are in tension, and be wary of dogma that relies too heavily on any one of the statements in it.
You should be careful about using the finally block, as it is not the same thing as using an else block in the try, except. The finally block will be run regardless of the outcome of the try except.
In [10]: dict_ = {"a": 1}
In [11]: try:
....: dict_["b"]
....: except KeyError:
....: pass
....: finally:
....: print "something"
....:
something
As everyone has noted using the else block causes your code to be more readable, and only runs when an exception is not thrown
In [14]: try:
dict_["b"]
except KeyError:
pass
else:
print "something"
....:
Just because no-one else has posted this opinion, I would say
avoid else clauses in try/excepts because they're unfamiliar to most people
Unlike the keywords try, except, and finally, the meaning of the else clause isn't self-evident; it's less readable. Because it's not used very often, it'll cause people that read your code to want to double-check the docs to be sure they understand what's going on.
(I'm writing this answer precisely because I found a try/except/else in my codebase and it caused a wtf moment and forced me to do some googling).
So, wherever I see code like the OP example:
try:
try_this(whatever)
except SomeException as the_exception:
handle(the_exception)
else:
# do some more processing in non-exception case
return something
I would prefer to refactor to
try:
try_this(whatever)
except SomeException as the_exception:
handle(the_exception)
return # <1>
# do some more processing in non-exception case <2>
return something
<1> explicit return, clearly shows that, in the exception case, we are finished working
<2> as a nice minor side-effect, the code that used to be in the else block is dedented by one level.
Whenever you see this:
try:
y = 1 / x
except ZeroDivisionError:
pass
else:
return y
Or even this:
try:
return 1 / x
except ZeroDivisionError:
return None
Consider this instead:
import contextlib
with contextlib.suppress(ZeroDivisionError):
return 1 / x
This is my simple snippet on howto understand try-except-else-finally block in Python:
def div(a, b):
try:
a/b
except ZeroDivisionError:
print("Zero Division Error detected")
else:
print("No Zero Division Error")
finally:
print("Finally the division of %d/%d is done" % (a, b))
Let's try div 1/1:
div(1, 1)
No Zero Division Error
Finally the division of 1/1 is done
Let's try div 1/0
div(1, 0)
Zero Division Error detected
Finally the division of 1/0 is done
I'm attempting to answer this question in a slightly different angle.
There were 2 parts of the OP's question, and I add the 3rd one, too.
What is the reason for the try-except-else to exist?
Does the try-except-else pattern, or the Python in general, encourage using exceptions for flow control?
When to use exceptions, anyway?
Question 1: What is the reason for the try-except-else to exist?
It can be answered from a tactical standpoint. There is of course reason for try...except... to exist. The only new addition here is the else... clause, whose usefulness boils down to its uniqueness:
It runs an extra code block ONLY WHEN there was no exception happened in the try... block.
It runs that extra code block, OUTSIDE of the try... block (meaning any potential exceptions happen inside the else... block would NOT be caught).
It runs that extra code block BEFORE the final... finalization.
db = open(...)
try:
db.insert(something)
except Exception:
db.rollback()
logging.exception('Failing: %s, db is ROLLED BACK', something)
else:
db.commit()
logging.info(
'Successful: %d', # <-- For the sake of demonstration,
# there is a typo %d here to trigger an exception.
# If you move this section into the try... block,
# the flow would unnecessarily go to the rollback path.
something)
finally:
db.close()
In the example above, you can't move that successful log line into behind the finally... block. You can't quite move it into inside the try... block, either, due to the potential exception inside the else... block.
Question 2: does Python encourage using exceptions for flow control?
I found no official written documentation to support that claim. (To readers who would disagree: please leave comments with links to evidences you found.) The only vaguely-relevant paragraph that I found, is this EAFP term:
EAFP
Easier to ask for forgiveness than permission. This common Python coding style assumes the existence of valid keys or attributes and catches exceptions if the assumption proves false. This clean and fast style is characterized by the presence of many try and except statements. The technique contrasts with the LBYL style common to many other languages such as C.
Such paragraph merely described that, rather than doing this:
def make_some_noise(speaker):
if hasattr(speaker, "quack"):
speaker.quack()
we would prefer this:
def make_some_noise(speaker):
try:
speaker.quack()
except AttributeError:
logger.warning("This speaker is not a duck")
make_some_noise(DonaldDuck()) # This would work
make_some_noise(DonaldTrump()) # This would trigger exception
or potentially even omitting the try...except:
def make_some_noise(duck):
duck.quack()
So, the EAFP encourages duck-typing. But it does not encourage using exceptions for flow control.
Question 3: In what situation you should design your program to emit exceptions?
It is a moot conversation on whether it is anti-pattern to use exception as control flow. Because, once a design decision is made for a given function, its usage pattern would also be determined, and then the caller would have no choice but to use it that way.
So, let's go back to the fundamentals to see when a function would better produce its outcome via returning a value or via emitting exception(s).
What is the difference between the return value and the exception?
Their "blast radius" are different. Return value is only available to the immediate caller; exception can be automatically relayed for unlimited distance until it is caught.
Their distribution patterns are different. Return value is by definition one piece of data (even though you could return a compound data type such as a dictionary or a container object, it is still technically one value).
The exception mechanism, on the contrary, allows multiple values (one at a time) to be returned via their respective dedicate channel. Here, each except FooError: ... and except BarError: ... block is considered as its own dedicate channel.
Therefore, it is up to each different scenario to use one mechanism that fits well.
All normal cases should better be returned via return value, because the callers would most likely need to use that return value immediately. The return-value approach also allows nesting layers of callers in a functional programming style. The exception mechanism's long blast radius and multiple channels do not help here.
For example, it would be unintuitive if any function named get_something(...) produces its happy path result as an exception. (This is not really a contrived example. There is one practice to implement BinaryTree.Search(value) to use exception to ship the value back in the middle of a deep recursion.)
If the caller would likely forget to handle the error sentinel from the return value, it is probably a good idea to use exception's characterist #2 to save caller from its hidden bug. A typical non-example would be the position = find_string(haystack, needle), unfortunately its return value of -1 or null would tend to cause a bug in the caller.
If the error sentinel would collide with a normal value in the result namespace, it is almost certain to use an exception, because you'd have to use a different channel to convey that error.
If the normal channel i.e. the return value is already used in the happy-path, AND the happy-path does NOT have sophisicated flow control, you have no choice but to use exception for flow control. People keep talking about how Python uses StopIteration exception for iteration termination, and use it to kind of justify "using exception for flow control". But IMHO this is only a practical choice in a particular situation, it does not generalize and glorify "using exception for flow control".
At this point, if you already make a sound decision on whether your function get_stock_price() would produce only return-value or also raise exceptions, or if that function is provided by an existing library so that its behavior has long be decided, you do not have much choice in writing its caller calculate_market_trend(). Whether to use get_stock_price()'s exception to control the flow in your calculate_market_trend() is merely a matter of whether your business logic requires you to do so. If yes, do it; otherwise, let the exception bubble up to a higher level (this utilizes the characteristic #1 "long blast radius" of exception).
In particular, if you are implementing a middle-layer library Foo and you happen to be making a dependency on lower-level library Bar, you would probably want to hide your implementation detail, by catching all Bar.ThisError, Bar.ThatError, ..., and map them into Foo.GenericError. In this case, the long blast radius is actually working against us, so you might hope "only if library Bar were returning its errors via return values". But then again, that decision has long been made in Bar, so you can just live with it.
All in all, I think whether to use exception as control flow is a moot point.
OP, YOU ARE CORRECT. The else after try/except in Python is ugly. it leads to another flow-control object where none is needed:
try:
x = blah()
except:
print "failed at blah()"
else:
print "just succeeded with blah"
A totally clear equivalent is:
try:
x = blah()
print "just succeeded with blah"
except:
print "failed at blah()"
This is far clearer than an else clause. The else after try/except is not frequently written, so it takes a moment to figure what the implications are.
Just because you CAN do a thing, doesn't mean you SHOULD do a thing.
Lots of features have been added to languages because someone thought it might come in handy. Trouble is, the more features, the less clear and obvious things are because people don't usually use those bells and whistles.
Just my 5 cents here. I have to come along behind and clean up a lot of code written by 1st-year out of college developers who think they're smart and want to write code in some uber-tight, uber-efficient way when that just makes it a mess to try and read / modify later. I vote for readability every day and twice on Sundays.
This question already has answers here:
`if key in dict` vs. `try/except` - which is more readable idiom?
(11 answers)
Closed 6 years ago.
Often, I come across cases where I find both if-else and try-except clauses can be used to solve a problem. As a result, I have some confusion deciding(and justifying) the use of a particular clause to accomplish the task at hand.
For example, let us consider a trivial situation:
In []: user = {"name": "Kshitij", "age": 20 }
# My motive is to print the user's email if it is available.
# In all other cases, a warning message needs to be printed
# Method-01 : Using try clause
In []: try:
...: print(a["email"])
...: except KeyError:
...: print("No EMAIL given")
...:
No EMAIL given
# Method-02 : Using if-else clause
In []: if "email" in a:
print(a["email"])
...: else:
...: print("No EMAIL given")
...:
No EMAIL given
I would like to know how can I decide a more Pythonic method among the two and justify it. Also, some pointers to how can one differentiate among several methods to solve similar scenarios would be really helpful.
try/catch and if/else are not interchangeable. the former is for catching errors that might be thrown. no if statement can do that. if/else is for checking if a condition is true or false. errors thrown in an if/else block will not be caught and the program will crash.
You should use exceptions if this case is an exception and not the normal case.
if/then: for internal application flow control. Errors are unlikely to be fatal
vs
try/except: for system calls and API calls where the state of the receiver is external to the code. Failures are likely to be fatal and need to handled explicitly
If you're looking for "Pythonic", neither of those is.
print a["email"] if "email" in a else "No EMAIL given"
Now that's Pythonic. But, back to the question: First of all, you decide what to do - I'm not aware of any writing conventions between those two. But, as I see it:
if-else is used mainly for detecting expectable behaviour - I mean, if "email" is not in a, it's excpectable. So we will use if-else.
An example would be your code.
But, for example, if we want to check if a string contains a numeric value, we will try to convert it to a number. If it failed, well, it's a bit harder to predict it using an if statement, so we will use try-except.
Here's a short example for that:
def is_numeric(string):
try:
a = float(string)
return True
except:
return False
of course there is a better way to check if a string is numeric, that was just an example use of try-except.
This question already has answers here:
Closed 12 years ago.
Possible Duplicate:
Does a exception with just a raise have any use?
Is there any value to re-raising an exception with no other code in between?
try:
#code
except Exception:
raise
I was recently looking through some code and saw a few blocks like these with nothing extra in the except block but another raise. I assume this was a mistake and poor decision making, am I right?
I've seen similar code before in a (set of) horrible VB.NET projects. Either the intent was to catch and log exceptions, without ever coming back to finish the logging, or they heard "you must catch exceptions", implemented this functionality, and someone else decided it should just re-raise.
There is no benefit to the above code.
I am not able to come up with something useful, other than to keep it as a placeholder for later insertion to catch useful exceptions.
It kind of avoids re-indenting the code, when you want to include the "try .. except.." blocks later on.
Example built on this question. If there's some other except's in the try block, it can be used to filter the exceptions, but alone it's pointless.
class FruitException(Exception): pass
try:
raise FruitException
except FruitException:
print "we got a bad fruit"
raise
except Exception:
print "not fruit related, irrelevant."
Yes, this is usually a bad practice. The only (somewhat) correct usage I've seen of this pattern was before VB.NET had a Using construct available. Usage looked something like:
Dim myResource As DisposableService
Try
myResource = New DisposableService()
' This might throw an exception....
myResource.DoSomething()
Catch
Throw
Finally
' Perform cleanup on resource
If Not myResource Is Nothing Then
myResource.Dispose()
End If
End Try
Other than that, I really can't think of a good use case for this sort of thing.
sometimes it useful let me give you a real example that i did i my work :
this was is in a decorator that wrap func : so basically what i have wanted is to re-raise the error that i catched when i called the function func so that the decorator don't change the behavior of the function func, because when func raise an exception the exception are send to the GUI so that an error message can pop up to the user,
and for the try except i use it because i want to execute the code in finally even if an exception is raised
try:
result = func(self, *args, **kws)
return result
except Exception, ex:
# If an exception is raised save it also.
logging_data['message'] = str(ex)
logging_data['type'] = 'exception'
# Raise the error catched here so that we could have
# the same behavior as the decorated method.
raise
finally:
# Save logging data in the database
....
hope this will help to understand the use of re-raise
Typically in a try-catch model, any uncaught exception will automatically be thrown (raised?). Catching the exception only to re-throw it may be in the spirit Allman style coding, but serves no functional purpose.
Uh, Imagine
def something(a,b):
try:
// do stuff
except SomethingSpecificToThisFunction:
//handle
except: //Everything else, should likely be handled somewhere else
raise
try:
something("a","b")
except e:
Log(e)
Then again its default behaviour anyways, so might just want to leave it out
There are some approaches with such technics in multithread enviroment. For example to throw something to upper stack level.
This question already has answers here:
Is it better to use an exception or a return code in Python?
(6 answers)
Python: Throw Exception or return None? [closed]
(3 answers)
Closed 1 year ago.
What's better practice in a user-defined function in Python: raise an exception or return None? For example, I have a function that finds the most recent file in a folder.
def latestpdf(folder):
# list the files and sort them
try:
latest = files[-1]
except IndexError:
# Folder is empty.
return None # One possibility
raise FileNotFoundError() # Alternative
else:
return somefunc(latest) # In my case, somefunc parses the filename
Another option is leave the exception and handle it in the caller code, but I figure it's more clear to deal with a FileNotFoundError than an IndexError. Or is it bad form to re-raise an exception with a different name?
It's really a matter of semantics. What does foo = latestpdf(d) mean?
Is it perfectly reasonable that there's no latest file? Then sure, just return None.
Are you expecting to always find a latest file? Raise an exception. And yes, re-raising a more appropriate exception is fine.
If this is just a general function that's supposed to apply to any directory, I'd do the former and return None. If the directory is, e.g., meant to be a specific data directory that contains an application's known set of files, I'd raise an exception.
I would make a couple suggestions before answering your question as it may answer the question for you.
Always name your functions descriptive. latestpdf means very little to anyone but looking over your function latestpdf() gets the latest pdf. I would suggest that you name it getLatestPdfFromFolder(folder).
As soon as I did this it became clear what it should return.. If there isn't a pdf raise an exception. But wait there more..
Keep the functions clearly defined. Since it's not apparent what somefuc is supposed to do and it's not (apparently) obvious how it relates to getting the latest pdf I would suggest you move it out. This makes the code much more readable.
for folder in folders:
try:
latest = getLatestPdfFromFolder(folder)
results = somefuc(latest)
except IOError: pass
Hope this helps!
I usually prefer to handle exceptions internally (i.e. try/except inside the called function, possibly returning a None) because python is dynamically typed. In general, I consider it a judgment call one way or the other, but in a dynamically typed language, there are small factors that tip the scales in favor of not passing the exception to the caller:
Anyone calling your function is not notified of the exceptions that can be thrown. It becomes a bit of an art form to know what kind of exception you are hunting for (and generic except blocks ought to be avoided).
if val is None is a little easier than except ComplicatedCustomExceptionThatHadToBeImportedFromSomeNameSpace. Seriously, I hate having to remember to type from django.core.exceptions import ObjectDoesNotExist at the top of all my django files just to handle a really common use case. In a statically typed world, let the editor do it for you.
Honestly, though, it's always a judgment call, and the situation you're describing, where the called function receives an error it can't help, is an excellent reason to re-raise an exception that is meaningful. You have the exact right idea, but unless you're exception is going to provide more meaningful information in a stack trace than
AttributeError: 'NoneType' object has no attribute 'foo'
which, nine times out of ten, is what the caller will see if you return an unhandled None, don't bother.
(All this kind of makes me wish that python exceptions had the cause attributes by default, as in java, which lets you pass exceptions into new exceptions so that you can rethrow all you want and never lose the original source of the problem.)
with python 3.5's typing:
example function when returning None will be:
def latestpdf(folder: str) -> Union[str, None]
and when raising an exception will be:
def latestpdf(folder: str) -> str
option 2 seem more readable and pythonic
(+option to add comment to exception as stated earlier.)
In general, I'd say an exception should be thrown if something catastrophic has occured that cannot be recovered from (i.e. your function deals with some internet resource that cannot be connected to), and you should return None if your function should really return something but nothing would be appropriate to return (i.e. "None" if your function tries to match a substring in a string for example).