[Python-Dev] About adding a new iterator method called "shuffled"
I know that Python has iterator methods called "sorted" and "reversed" and these are handy shortcuts. Why not add a new iterator method called "shuffled"? >>> for x in shuffled(range(5)): >>>print x >>> 3 >>> 1 >>> 2 >>> 0 >>> 4 Currently, a person has to do the following because random.shuffle() does not return the actual shuffled list. It is verbose. >>> import random >>> x = range(5) >>> random.shuffle(x) >>> for x in x: >>> print x ___ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
[Python-Dev] Splitting something into two steps produces different behavior from doing it in one fell swoop in Python 2.6.2
While debugging a network algorithm in Python 2.6.2, I encountered
some strange behavior and was wondering whether it has to do with some
sort of code optimization that Python does behind the scenes.
After initialization: defaultdict(, {1: set([1])})
Popping and updating in two steps: defaultdict(, {1: set([1])})
After initialization: defaultdict(, {1: set([1])})
Popping and updating in one step: defaultdict(, {})
import collections
print ''
x = collections.defaultdict(set)
x[1].update([1])
print 'After initialization: %s' % x
items = x.pop(1)
x[1].update(items)
print 'Popping and updating in two steps: %s' % x
print ''
y = collections.defaultdict(set)
y[1].update([1])
print 'After initialization: %s' % y
y[1].update(y.pop(1))
print 'Popping and updating in one step: %s' % y
inOneStepVSTwoSteps.py
Description: Binary data
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Re: [Python-Dev] Splitting something into two steps produces different behavior from doing it in one fell swoop in Python 2.6.2
On Fri, Dec 11, 2009 at 2:43 PM, MRAB wrote:
> John Arbash Meinel wrote:
>>
>> Roy Hyunjin Han wrote:
>>>
>>> While debugging a network algorithm in Python 2.6.2, I encountered
>>> some strange behavior and was wondering whether it has to do with some
>>> sort of code optimization that Python does behind the scenes.
>>>
>>>
>>>
>>> After initialization: defaultdict(, {1: set([1])})
>>> Popping and updating in two steps: defaultdict(, {1:
>>> set([1])})
>>>
>>> After initialization: defaultdict(, {1: set([1])})
>>> Popping and updating in one step: defaultdict(, {})
>>>
>>>
>>> import collections
>>> print ''
>>> x = collections.defaultdict(set)
>>> x[1].update([1])
>>> print 'After initialization: %s' % x
>>> items = x.pop(1)
>>> x[1].update(items)
>>> print 'Popping and updating in two steps: %s' % x
>>> print ''
>>> y = collections.defaultdict(set)
>>> y[1].update([1])
>>> print 'After initialization: %s' % y
>>> y[1].update(y.pop(1))
>>> print 'Popping and updating in one step: %s' % y
>>>
>>
>> y[1].update(y.pop(1))
>>
>> is going to be evaluating y[1] before it evaluates y.pop(1).
>> Which means that it has the original set returned, which is then removed
>> by y.pop, and updated.
>>
>> You probably get the same behavior without using a defaultdict:
>> y.setdefault(1, set()).update(y.pop(1))
>> ^^- evaluated first
>>
>>
>> Oh and I should probably give the standard: "This list is for the
>> development *of* python, not development *with* python."
>>
> To me the question was whether Python was behaving correctly; the
> behaviour was more subtle than the legendary mutable default argument.
Thanks, John and MRAB. I was pointing it out on this list because I
felt like it was counterintuitive and that the result should be the
same whether the developer decides to do it in two steps or in one
step.
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Re: [Python-Dev] Splitting something into two steps produces different behavior from doing it in one fell swoop in Python 2.6.2
On Fri, Dec 11, 2009 at 7:59 PM, Nick Coghlan wrote: > It follows the standard left-to-right evaluation order within an expression: > > () > > (i.e. a function call always determines which function is going to be > called before determining any arguments to be passed) > > Splitting it into two lines then clearly changes the evaluation order: > > temp = > (temp) > > I'm not sure what behaviour could be suggested as being more intuitive - > the problem in this case arose due to both referencing and mutating the > same object in a single statement, which is always going to be > problematic from an ordering point of view, since it depends on subtle > details of statement definitions that people often won't know. Better to > split the mutation and the reference into separate statements so the > intended order is clear regardless of how well the reader knows the > subtleties of Python's evaluation order. > > Cheers, > Nick. > Thanks for the explanation, Nick. I understand what is happening now. y[1].update resolves to the update() method of the old set referenced by y[1], but this set is then popped so that the update() manages to change the old set, but not the new one that is returned by any subsequent reference to y[1]. I suppose I will have to keep this in two statements. A similar thing happened with the SWIG extensions for GDAL, in which one had to separate statements so that SWIG objects were not destroyed prematurely, i.e. no more one-liners. ___ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
[Python-Dev] What if replacing items in a dictionary returns the new dictionary?
It would be convenient if replacing items in a dictionary returns the
new dictionary, in a manner analogous to str.replace(). What do you
think?
::
# Current behavior
x = {'key1': 1}
x.update(key1=3) == None
x == {'key1': 3} # Original variable has changed
# Possible behavior
x = {'key1': 1}
x.replace(key1=3) == {'key1': 3}
x == {'key1': 1} # Original variable is unchanged
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Re: [Python-Dev] What if replacing items in a dictionary returns the new dictionary?
2011/4/29 R. David Murray : > 2011/4/29 Roy Hyunjin Han : >> It would be convenient if replacing items in a dictionary returns the >> new dictionary, in a manner analogous to str.replace() > > This belongs on python-ideas, but the short answer is no. The > general language design principle (as I understand it) is that > mutable object do not return themselves upon mutation, while > immutable objects do return the new object. Thanks for the responses. Sorry for the mispost, I'll post things like this on python-ideas from now on. RHH ___ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
Re: [Python-Dev] What if replacing items in a dictionary returns the new dictionary?
> You can implement this in your own subclass of dict, no? Yes, I just thought it would be convenient to have in the language itself, but the responses to my post seem to indicate that [not returning the updated object] is an intended language feature for mutable types like dict or list. class ReplaceableDict(dict): def replace(self, **kw): 'Works for replacing string-based keys' return dict(self.items() + kw.items()) ___ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
Re: [Python-Dev] What if replacing items in a dictionary returns the new dictionary?
>> 2011/4/29 Roy Hyunjin Han :
>> It would be convenient if replacing items in a dictionary returns the
>> new dictionary, in a manner analogous to str.replace(). What do you
>> think?
>>
>># Current behavior
>>x = {'key1': 1}
>>x.update(key1=3) == None
>>x == {'key1': 3} # Original variable has changed
>>
>># Possible behavior
>>x = {'key1': 1}
>>x.replace(key1=3) == {'key1': 3}
>>x == {'key1': 1} # Original variable is unchanged
>>
> 2011/5/5 Giuseppe Ottaviano :
> In general nothing stops you to use a proxy object that returns itself
> after each method call, something like
>
> class using(object):
>def __init__(self, obj):
>self._wrappee = obj
>
>def unwrap(self):
>return self._wrappee
>
>def __getattr__(self, attr):
>def wrapper(*args, **kwargs):
>getattr(self._wrappee, attr)(*args, **kwargs)
>return self
>return wrapper
>
>
> d = dict()
> print using(d).update(dict(a=1)).update(dict(b=2)).unwrap()
> # prints {'a': 1, 'b': 2}
> l = list()
> print using(l).append(1).append(2).unwrap()
> # prints [1, 2]
Cool! I never thought of that. That's a great snippet.
I'll forward this to the python-ideas list. I don't think the
python-dev people want this discussion to continue on their mailing
list.
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