I usually want to keep my code as generic as possible. I\'m currently writing a simple library and being able to use different types with my library feels extra important th
First of all, the code in your question is not ideal:
try:
obj.wag_tail()
except AttributeError:
...
You don't know whether the AttributeError
is from the lookup of wag_tail
or whether it happened inside the function. What you are trying to do is:
try:
f = getattr(obj, 'wag_tail')
except AttributeError:
...
finally:
f()
Edit: kindall rightly points out that if you are going to check this, you should also check that f
is callable.
In general, this is not Pythonic. Just call and let the exception filter down, and the stack trace is informative enough to fix the problem. I think you should ask yourself whether your rethrown exceptions are useful enough to justify all of this error-checking code.
The case of sorting a list is a great example.
If those three criteria apply to your problem (especially the third), I agree with building pretty exception rethrower.
You have to balance with the fact that throwing these pretty errors is going to make your code harder to read, which statistically means more bugs in your code. It's a question of balancing the pros and the cons.
If you ever need to check for behaviours (like __real__
and __contains__
), don't forget to use the Python abstract base classes found in collections
, io
, and numbers
.
Good question, and quite open-ended. I believe typical Python style is not to check, either with isinstance or catching individual exceptions. Cerainly, using isinstance is quite bad style, as it defeats the whole point of duck typing (though using isinstance on primitives can be OK -- be sure to check for both int and long for integer inputs, and check for basestring for strings (base class of str and unicode). If you do check, you hould raise a TypeError.
Not checking is generally OK, as it typically raises either a TypeError or AttributeError anyway, which is what you want. (Though it can delay those errors making client code hard to debug).
The reason you see TypeErrors is that primitive code raises it, effectively because it does an isinstance. The for loop is hard-coded to raise a TypeError if something is not iterable.
If you just want the unimplemented methods to do nothing, you can try something like this, rather than the multi-line try/except
construction:
getattr(obj, "sleep", lambda: None)()
However, this isn't necessarily obvious as a function call, so maybe:
hasattr(obj, "sleep") and obj.sleep()
or if you want to be a little more sure before calling something that it can in fact be called:
hasattr(obj, "sleep") and callable(obj.sleep) and obj.sleep()
This "look-before-you-leap" pattern is generally not the preferred way to do it in Python, but it is perfectly readable and fits on a single line.
Another option of course is to abstract the try/except
into a separate function.
I'm not a python pro but I believe that unless you can try an alternative for when the parameter doesn't implement a given method, you shoudn't prevent exceptions from being thrown. Let the caller handle these exceptions. This way, you would be hidding problems from the developers.
As I have read in Clean Code, if you want to search for an item in a collection, don't test your parameters with ìssubclass
(of a list) but prefer to call getattr(l, "__contains__")
. This will give someone who is using your code a chance to pass a parameter that isn't a list but which has a __contains__
method defined and things should work equally well.
So, I think that you should code in an abstract, generic way, imposing as few restrictions as you can. For that, you'll have to make the fewest assumptions possible. However, when you face something that you can't handle, raise an exception and let the programmer know what mistake he made!
If your code requires a particular interface, and the user passes an object without that interface, then nine times out of ten, it's inappropriate to catch the exception. Most of the time, an AttributeError
is not only reasonable but expected when it comes to interface mismatches.
Occasionally, it may be appropriate to catch an AttributeError
for one of two reasons. Either you want some aspect of the interface to be optional, or you want to throw a more specific exception, perhaps a package-specific exception subclass. Certainly you should never prevent an exception from being thrown if you haven't honestly handled the error and any aftermath.
So it seems to me that the answer to this question must be problem- and domain- specific. It's fundamentally a question of whether using a Cow
object instead of a Duck
object ought to work. If so, and you handle any necessary interface fudging, then that's fine. On the other hand, there's no reason to explicitly check whether someone has passed you a Frog
object, unless that will cause a disastrous failure (i.e. something much worse than a stack trace).
That said, it's always a good idea to document your interface -- that's what docstrings (among other things) are for. When you think about it, it's much more efficient to throw a general error for most cases and tell users the right way to do it in the docstring, than to try to foresee every possible error a user might make and create a custom error message.
A final caveat -- it's possible that you're thinking about UI here -- I think that's another story. It's good to check the input that an end user gives you to make sure it isn't malicious or horribly malformed, and provide useful feedback instead of a stack trace. But for libraries or things like that, you really have to trust the programmer using your code to use it intelligently and respectfully, and to understand the errors that Python generates.