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is None or == None ?

 
 
Carl Banks
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      11-06-2009
On Nov 6, 11:41*am, "Alf P. Steinbach" <(E-Mail Removed)> wrote:
> Note that the object implementation's complexity doesn't have to affect to any
> other code since it's trivial to provide abstract accessors (even macros), i.e.,
> this isn't part of a trade-off except if the original developer(s) had limited
> resources *-- *and if so then it wasn't a trade-off at the language design level
> but a trade-off of getting things done then and there.


I totally disagree with this; it would be like squaring the
implementation complexity. It is far from "trivial" as you claim.
Even if it were just a matter of accessor macros (and it isn't) they
don't write themselves, especially when you focused on speed, so
that's a non-trivial complexity increase already. But you besides
writing code you now have reading code (which is now cluttered with
all kinds of ugly accessor macros, as if the Python API wasn't ugly
enough), debugging code, maintaining code, understanding semantics and
nuances, handling all the extra corner cases. To say it's trivial is
absurd.


> > *C# made a
> > different trade-off, choosing a more complex implementation, a
> > language with two starkly different object semantic behaviors, so as
> > to allow better performance.

>
> Don't know about the implementation of C#, but whatever it is, if it's bad in
> some respect then that has nothing to do with Python.


C# is a prototypical example of a language that does what you were
suggesting (also it draws upon frameworks like COM, which you
mentioned) so it is a basis of comparison of the benefits versus
drawbacks of the two approaches.


Carl Banks
 
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Stefan Behnel
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      11-07-2009
mk, 06.11.2009 15:32:
> Stefan Behnel wrote:
>> class Test(object):
>> def __eq__(self, other):
>> return other == None
>>
>> print Test() == None, Test() is None

>
> Err, I don't want to sound daft, but what is wrong in this example? It
> should work as expected:
>
> >>> class Test(object):

> ... def __eq__(self, other):
> ... return other == None
> ...
> >>> Test() is None

> False
> >>> Test() == None

> True


Yes, and it shows you that things can compare equal to None without being None.


> Or perhaps your example was supposed to show that I should test for
> identity with None, not for value with None?


Instead of "value" you mean "equality" here, I suppose. While there are
certain rare use cases where evaluating non-None objects as equal to None
makes sense, in normal use, you almost always want to know if a value is
exactly None, not just something that happens to return True when
calculating its equality to None, be it because of a programmer's concious
consideration or buggy implementation.

Stefan
 
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Steven D'Aprano
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      11-07-2009
On Fri, 06 Nov 2009 16:51:18 +0100, Marco Mariani wrote:

> Using "x is y" with integers
> makes no sense and has no guaranteed behaviour AFAIK


Of course it makes sense. `x is y` means *exactly the same thing* for
ints as it does with any other object: it tests for object identity.
That's all it does, and it does it perfectly.

Python makes no promise whether x = 3; y = 3 will use the same object for
both x and y or not. That's an implementation detail. That's not a
problem with `is`, it is a problem with developers who make unjustified
assumptions.


--
Steven
 
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Terry Reedy
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      11-07-2009
Steven D'Aprano wrote:
> On Fri, 06 Nov 2009 16:51:18 +0100, Marco Mariani wrote:
>
>> Using "x is y" with integers
>> makes no sense and has no guaranteed behaviour AFAIK

>
> Of course it makes sense. `x is y` means *exactly the same thing* for
> ints as it does with any other object: it tests for object identity.
> That's all it does, and it does it perfectly.
>
> Python makes no promise whether x = 3; y = 3 will use the same object for
> both x and y or not. That's an implementation detail. That's not a
> problem with `is`, it is a problem with developers who make unjustified
> assumptions.


Which is to say, it normally makes no sense to write 'm is n' for m, n ints.

The *exception* is when one is exploring implementation details, either
to discover them or to test that they are as intended. So, last I
looked, the test suite for ints makes such tests. If the implementation
changes, the test should change also.

The problem comes when newbies use 'is' without realizing that they are
doing black-box exploration of otherwise irrelevant internals.
(White-box exploration would be reading the code, which makes it plain
what is going on .

Terry Jan Reedy


 
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sturlamolden
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      11-07-2009
On 6 Nov, 14:35, "Alf P. Steinbach" <(E-Mail Removed)> wrote:

> As I understand it, 'is' will always work and will always be efficient (it just
> checks the variable's type), while '==' can depend on the implementation of
> equality checking for the other operand's class.


'==' checks for logical equality. 'is' checks for object identity.

None is a singleton of type NoneType. Since None evaluates to True
only when compared against itself, it is safe to use both operators.









 
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sturlamolden
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      11-07-2009
On 6 Nov, 18:28, "Alf P. Steinbach" <(E-Mail Removed)> wrote:

> Dynamic allocation isn't hare-brained, but doing it for every stored integer
> value outside a very small range is, because dynamic allocation is (relatively
> speaking, in the context of integer operations) very costly even with a
> (relatively speaking, in the context of general dynamic allocation) very
> efficient small-objects allocator - here talking order(s) of magnitude.


When it matters, we use NumPy and/or Cython.

 
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sturlamolden
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      11-07-2009
On 6 Nov, 17:54, "Alf P. Steinbach" <(E-Mail Removed)> wrote:

> But wow. That's pretty hare-brained: dynamic allocation for every stored value
> outside the cache range, needless extra indirection for every operation.


First, integers are not used the same way in Python as they are in C+
+. E.g. you typically don't iterate over them in a for loop, but
rather iterate on the container itself. Second, if you need an array
of integers or floats, that is usually not done with a list: you would
use numpy.ndarray or array.array, and values are stored compactly.

A Python list is a list, it is not an array. If you were to put
integers in dynamic data structures in other languages (Java, C++),
you would use dynamic allocation as well. Yes a list is implemented as
an array of pointers, amortized to O(1) for appends, but that is an
implementation detail.

Python is not the only language that works like this. There are also
MATLAB and Lisp. I know you have a strong background in C++, but when
you are using Python you must unlearn that way of thinking.

Finally: if none of these helps, we can always resort to Cython.

In 99% of cases where integers are bottlenecks in Python, it is
indicative of bad style. We very often see this from people coming
form C++ and Java background, and subsequent claims that "Python is
slow". Python is not an untyped Java. If you use it as such, it will
hurt. Languages like Python, Perl, Common Lisp, and MATLAB require a
different mindset from the programmer.

















 
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Steven D'Aprano
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      11-07-2009
On Sat, 07 Nov 2009 14:22:28 -0800, sturlamolden wrote:

> On 6 Nov, 14:35, "Alf P. Steinbach" <(E-Mail Removed)> wrote:
>
>> As I understand it, 'is' will always work and will always be efficient
>> (it just checks the variable's type), while '==' can depend on the
>> implementation of equality checking for the other operand's class.

>
> '==' checks for logical equality. 'is' checks for object identity.


So far so good, although technically == merely calls __eq__, which can be
over-ridden to do (nearly) anything you like:

>>> class Funny(object):

.... def __eq__(self, other):
.... return self.payload + other
....
>>> f = Funny()
>>> f.payload = 5
>>> f == 10

15


> None is a singleton of type NoneType. Since None evaluates to True only
> when compared against itself,


That's wrong. None never evaluates to True, it always evaluates as None,
in the same way that 42 evaluates as 42 and [1,2,3] evaluates as [1,2,3].
Python literals evaluate as themselves, always.

Perhaps you mean that *comparisons* of None evaluate to True only if both
operands are None. That's incorrect too:

>>> None > None

False

You have to specify the comparison. It would be a pretty strange language
if both None==None and None!=None returned True.



> it is safe to use both operators.


Only if you want unexpected results if somebody passes the wrong sort of
object to your code.


>>> class NoneProxy:

.... def __eq__(self, other):
.... if other is None: return True
.... return False
....
>>> o = NoneProxy()
>>> o is None

False
>>> o == None

True

You should use == *only* if you want to test for objects which are equal
to None, *whatever that object may be*, and is if you want to test for
None itself.



--
Steven
 
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Hrvoje Niksic
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      11-08-2009
"Alf P. Steinbach" <(E-Mail Removed)> writes:

> Speedup would likely be more realistic with normal implementation (not
> fiddling with bit-fields and stuff)


I'm not sure I understand this. How would you implement tagged integers
without encoding type information in bits of the pointer value?
 
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Alf P. Steinbach
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      11-08-2009
* Hrvoje Niksic:
> "Alf P. Steinbach" <(E-Mail Removed)> writes:
>
>> Speedup would likely be more realistic with normal implementation (not
>> fiddling with bit-fields and stuff)

>
> I'm not sure I understand this. How would you implement tagged integers
> without encoding type information in bits of the pointer value?


A normal tag field, as illustrated in code earlier in the thread.


Cheers & hth.,

- Alf
 
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