Python type() or __class__, == or is

Question

I want to test whether an object is an instance of a class, and only this class (no subclasses). I could do it either with:

obj.__class__ == Foo obj.__class__ is Foo type(obj) == Foo type(obj) is Foo 

Are there reasons to choose one over another? (performance differences, pitfalls, etc)

In other words: a) is there any practical difference between using __class__ and type(x)? b) are class objects always safe for comparison using is?

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Update: Thanks all for the feedback. I'm still puzzled by whether or not class objects are singletons, my common sense says they are, but it's been really hard to get a confirmation (try googling for "python", "class" and "unique" or "singleton").

I'd also like to clarify that, for my particular needs, the "cheaper" solution that just works is the best, since I'm trying to optimize the most out of a few, specialized classes (almost reaching the point where the sensible thing to do is to drop Python and develop that particular module in C). But the reason behind the question was to understand better the language, since some of its features are a bit too obscure for me to find that information easily. That's why I'm letting the discussion extend a little instead of settling for __class__ is, so I can hear the opinion of more experienced people. So far it's been very fruitful!

I ran a small test to benchmark the performance of the 4 alternatives. The profiler results were:

               Python  PyPy (4x) type()    is   2.138   2.594 __class__ is   2.185   2.437 type()    ==   2.213   2.625 __class__ ==   2.271   2.453 

Unsurprisingly, is performed better than == for all cases. type() performed better in Python (2% faster) and __class__ performed better in PyPy (6% faster). Interesting to note that __class__ == performed better in PyPy than type() is.

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Update 2: many people don't seem to understand what I mean with "a class is a singleton", so I'll ilustrate with an example:

>>> class Foo(object): pass ... >>> X = Foo >>> class Foo(object): pass ... >>> X == Foo False >>> isinstance(X(), Foo) False >>> isinstance(Foo(), X) False  >>> x = type('Foo', (object,), dict()) >>> y = type('Foo', (object,), dict()) >>> x == y False >>> isinstance(x(), y) False  >>> y = copy.copy(x) >>> x == y True >>> x is y True >>> isinstance(x(), y) True >>> y = copy.deepcopy(x) >>> x == y True >>> x is y True >>> isinstance(x(), y) True 

It doesn't matter if there are N objects of type type, given an object, only one will be its class, hence it's safe to compare for reference in this case. And since reference comparison will always be cheaper than value comparison, I wanted to know whether or not my assertion above holds. I'm reaching the conclusion that it does, unless someone presents evidence in contrary.

Answer 1

For old-style classes, there is a difference:

>>> class X: pass ...  >>> type(X) <type 'classobj'> >>> X.__class__ Traceback (most recent call last):   File "<stdin>", line 1, in <module> AttributeError: class X has no attribute '__class__' >>> x = X() >>> x.__class__ <class __main__.X at 0x171b5d50> >>> type(x) <type 'instance'> 

The point of new-style classes was to unify class and type. Technically speaking, __class__ is the only solution that will work both for new and old-style class instances, but it will also throw an exception on old-style class objects themselves. You can call type() on any object, but not every object has __class__. Also, you can muck with __class__ in a way you can't muck with type().

>>> class Z(object): ...     def __getattribute__(self, name): ...             return "ham" ...  >>> z = Z() >>> z.__class__ 'ham' >>> type(z) <class '__main__.Z'> 

Personally, I usually have an environment with new-style classes only, and as a matter of style prefer to use type() as I generally prefer built-in functions when they exist to using magic attributes. For example, I would also prefer bool(x) to x.__nonzero__().