Problem of Readability of Python
Licheng Fang
a while I find my Python programs can be more obfuscated than their C/C
++ counterparts sometimes. Part of the reason is that with
heterogeneous lists/tuples at hand, I tend to stuff many things into
the list and *assume* a structure of the list or tuple, instead of
declaring them explicitly as one will do with C structs. So, what used
to be
struct nameval {
char * name;
int val;
} a;
a.name = ...
a.val = ...
becomes cryptic
a[0] = ...
a[1] = ...
Python Tutorial says an empty class can be used to do this. But if
namespaces are implemented as dicts, wouldn't it incur much overhead
if one defines empty classes as such for some very frequently used
data structures of the program?
Any elegant solutions?
Steven Bethard
You can use __slots__ to make objects consume less memory and have
slightly better attribute-access performance. Classes for objects that
need such performance tweaks should start like::
class A(object):
__slots__ = 'name', 'val'
The recipe below fills in the obvious __init__ method for such classes
so that the above is pretty much all you need to write:
http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/502237
STeVe
Bruno Desthuilliers
> Python is supposed to be readable, but after programming in Python for
> a while I find my Python programs can be more obfuscated than their C/C
> ++ counterparts sometimes. Part of the reason is that with
> heterogeneous lists/tuples at hand, I tend to stuff many things into
> the list and *assume* a structure of the list or tuple, instead of
> declaring them explicitly as one will do with C structs. So, what used
> to be
>
> struct nameval {
> char * name;
> int val;
> } a;
>
> a.name = ...
> a.val = ...
>
> becomes cryptic
>
> a[0] = ...
> a[1] = ...
Use dicts, not lists or tuples:
a = dict(name='yadda', val=42)
print a['name']
print a['val']
> Python Tutorial says an empty class can be used to do this. But if
> namespaces are implemented as dicts, wouldn't it incur much overhead
> if one defines empty classes as such for some very frequently used
> data structures of the program?
If you do worry about overhead, then C is your friend !-)
More seriously: what do you use this 'nameval' struct for ? If you
really have an overhead problem, you may want to use a real class using
__slots__ to minimize this problem, but chances are you don't need it.
Bjoern Schliessmann
> struct nameval {
> char * name;
> int val;
> } a;
>
> a.name = ...
> a.val = ...
>
> becomes cryptic
>
> a[0] = ...
> a[1] = ...
?!
(1)
a = {}
a["name"] = ...
a["val"] = ...
(2)
NAME = 0
VAL = 1
a=[]
a[NAME] = ...
a[VAL] = ...
> Python Tutorial says an empty class can be used to do this. But if
> namespaces are implemented as dicts, wouldn't it incur much
> overhead if one defines empty classes as such for some very
> frequently used data structures of the program?
Measure first, optimize later. How many million of instances and/or
accesses per second do you have?
Regards,
Björn
--
BOFH excuse #20:
divide-by-zero error
George Sakkis
For immutable records, you may also want to check out the named tuples
recipe: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/500261
George
Steven Bethard
> recipe: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/500261
Yep, it's linked in the description of the first recipe.
STeVe
Brian Elmegaard
writes:
> Use dicts, not lists or tuples:
>
> a = dict(name='yadda', val=42)
> print a['name']
> print a['val']
I guess you will then need a list or tuple to store the dicts?
I might have made it with a list of class instances:
class a:
def __init__(self,name,val):
self.name=name
self.val=val
l=list()
l.append(a('yadda',42))
print l[0].name
print l[0].val
Is the dict preferable to a list or tuple of class instances?
--
Brian (remove the sport for mail)
http://www.et.web.mek.dtu.dk/Staff/be/be.html
http://www.rugbyklubben-speed.dk
Alex Martelli
...
> Python Tutorial says an empty class can be used to do this. But if
> namespaces are implemented as dicts, wouldn't it incur much overhead
> if one defines empty classes as such for some very frequently used
> data structures of the program?
Just measure:
$ python -mtimeit -s'class A(object):pass' -s'a=A()' 'a.zop=23'
1000000 loops, best of 3: 0.241 usec per loop
$ python -mtimeit -s'a=[None]' 'a[0]=23'
10000000 loops, best of 3: 0.156 usec per loop
So, the difference, on my 18-months-old laptop, is about 85 nanoseconds
per write-access; if you have a million such accesses in a typical run
of your program, it will slow the program down by about 85 milliseconds.
Is that "much overhead"? If your program does nothing else except those
accesses, maybe, but then why are your writing that program AT ALL?-)
And yes, you CAN save about 1/3 of those 85 nanoseconds by having
'__slots__=["zop"]' in your class A(object)... but that's the kind of
thing one normally does only to tiny parts of one's program that have
been identified by profiling as dramatic bottlenecks, to shave off the
last few nanoseconds in the very last stages of micro-optimization of a
program that's ALMOST, but not QUITE, fast enough... knowing about such
"extreme last-ditch optimization tricks" is of very doubtful value (and
I think I'm qualified to say that, since I _do_ know many of them...:-).
There ARE important performance things to know about Python, but those
worth a few nanoseconds don't matter much.
Alex
Paul McGuire
"""Just use a single empty class (such as the AttributeContainer
below)
and then use different instances of the class for different sets
of name/value pairs. (This type of class also goes by the name
Bag,
but that name is too, um, nondescript for me.) You can see from
the
example that there is no requirement for names to be shared,
unshared,
common, or unique.
-- Paul"""
class AttributeContainer(object):
pass
a = AttributeContainer()
a.name = "Lancelot"
a.favorite_color = "blue"
b = AttributeContainer()
b.name = "European swallow"
b.laden = true
b.airspeed = 20
John Nagle
> Python is supposed to be readable, but after programming in Python for
> a while I find my Python programs can be more obfuscated than their C/C
> ++ counterparts sometimes. Part of the reason is that with
> heterogeneous lists/tuples at hand, I tend to stuff many things into
> the list and *assume* a structure of the list or tuple, instead of
> declaring them explicitly as one will do with C structs.
Comments might help.
It's common to use tuples that way, but slightly bad form to
use lists that way.
Of course, you can create a class and use "slots" to bind
the positions at compile time, so you don't pay for a dictionary
lookup on every feature.
(Someday I need to overhaul BeautifulSoup to use "slots".
That might speed it up.)
John Nagle
John Machin
If not needing/wanting __slots__, something simpler (no metaclasses!)
like the following helps the legibility/utility:
<file record.py>
class BaseRecord(object):
def __init__(self, **kwargs):
for k, v in kwargs.iteritems():
setattr(self, k, v)
def dump(self, text=''):
print '== dumping %s instance: %s' % (self.__class__.__name__,
text)
for k, v in sorted(self.__dict__.iteritems()):
print ' %s: %r' % (k, v)
</file record.py>
Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit
(Intel)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from record import BaseRecord
>>> class A(BaseRecord):
... pass
...
>>> class B(BaseRecord):
... pass
...
>>> a1 = A(foo=1, bar='rab', zot=(1, 2))
>>> a2 = A(foo=2, bar='xxx', zot=(42, 666))
>>> a1.dump()
== dumping A instance:
bar: 'rab'
foo: 1
zot: (1, 2)
>>> a2.dump('more of the same')
== dumping A instance: more of the same
bar: 'xxx'
foo: 2
zot: (42, 666)
>>> a1.ugh = 'poked in'
>>> a1.dump('after poking')
== dumping A instance: after poking
bar: 'rab'
foo: 1
ugh: 'poked in'
zot: (1, 2)
>>> b1 = B()
>>> b1.dump()
== dumping B instance:
>>> b1.esrever = 'esrever'[::-1]
>>> b1.dump()
== dumping B instance:
esrever: 'reverse'
>>>
HTH,
John
Steven D'Aprano
> And yes, you CAN save about 1/3 of those 85 nanoseconds by having
> '__slots__=["zop"]' in your class A(object)... but that's the kind of
> thing one normally does only to tiny parts of one's program that have
> been identified by profiling as dramatic bottlenecks
Seems to me that:
class Record(object):
__slots__ = ["x", "y", "z"]
has a couple of major advantages over:
class Record(object):
pass
aside from the micro-optimization that classes using __slots__ are faster
and smaller than classes with __dict__.
(1) The field names are explicit and self-documenting;
(2) You can't accidentally assign to a mistyped field name without Python
letting you know immediately.
Maybe it's the old Pascal programmer in me coming out, but I think
they're big advantages.
--
Steven.
Alex Martelli
I'm also an old Pascal programmer (ask anybody who was at IBM in the
'80s who was the most active poster on the TURBO FORUM about Turbo
Pascal, and PASCALVS FORUM about Pascal/Vs...), and yet I consider these
"advantages" to be trivial in most cases compared to the loss in
flexibility, such as the inability to pickle (without bothering to code
an explicit __getstate__) and the inability to "monkey-patch" instances
on the fly -- not to mention the bother of defining a separate 'Record'
class for each and every combination of attributes you might want to put
together.
If you REALLY pine for Pascal's records, you might choose to inherit
from ctypes.Structure, which has the additional "advantages" of
specifying a C type for each field and (a real advantage;-) creating an
appropriate __init__ method.
>>> import ctypes
>>> class Record(ctypes.Structure):
... _fields_ =
(('x',ctypes.c_float),('y',ctypes.c_float),('z',ctypes.c_float)
)
...
>>> r=Record()
>>> r.x
0.0
>>> r=Record(1,2,3)
>>> r.x
1.0
>>> r=Record('zip','zop','zap')
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: float expected instead of str instance
See? You get type-checking too -- Pascal looms closer and closer!-)
And if you need an array of 1000 such Records, just use as the type
Record*1000 -- think of the savings in memory (no indirectness, no
overallocations as lists may have...).
If I had any real need for such things, I'd probably use a metaclass (or
class decorator) to also add a nice __repr__ function, etc...
Alex
Steven Bethard
> Steven D'Aprano <st...@REMOVE-THIS-cybersource.com.au> wrote:
>> class Record(object):
>> __slots__ = ["x", "y", "z"]
>>
>> has a couple of major advantages over:
>>
>> class Record(object):
>> pass
>>
>> aside from the micro-optimization that classes using __slots__ are faster
>> and smaller than classes with __dict__.
>>
>> (1) The field names are explicit and self-documenting;
>> (2) You can't accidentally assign to a mistyped field name without Python
>> letting you know immediately.
> If I had any real need for such things, I'd probably use a metaclass (or
> class decorator) to also add a nice __repr__ function, etc...
Yep. That's what the recipe I posted [1] does. Given a class like::
class C(Record):
__slots__ = 'x', 'y', 'z'
it adds the most obvious __init__ and __repr__ methods. Raymond's
NamedTuple recipe [2] has a similar effect, though the API is different.
[1] http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/502237
[2] http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/500261
STeVe
Aahz
Steven Bethard <steven....@gmail.com> wrote:
>
>You can use __slots__ [...]
Aaaugh! Don't use __slots__!
Seriously, __slots__ are for wizards writing applications with huuuge
numbers of object instances (like, millions of instances). For an
extended thread about this, see
http://groups.google.com/group/comp.lang.python/browse_thread/thread/8775c70565fb4a65/0e25f368e23ab058
--
Aahz (aa...@pythoncraft.com) <*> http://www.pythoncraft.com/
The best way to get information on Usenet is not to ask a question, but
to post the wrong information.
Michele Simionato
+1 QOTW ;)
Michele Simionato
Michele Simionato
> If you REALLY pine for Pascal's records, you might choose to inherit
> from ctypes.Structure, which has the additional "advantages" of
> specifying a C type for each field and (a real advantage;-) creating an
> appropriate __init__ method.
>
> >>> import ctypes
> >>> class Record(ctypes.Structure):
>
> ... _fields_ =
> (('x',ctypes.c_float),('y',ctypes.c_float),('z',ctypes.c_float)
> )
> ...>>> r=Record()
> >>> r.x
> 0.0
> >>> r=Record(1,2,3)
> >>> r.x
> 1.0
> >>> r=Record('zip','zop','zap')
>
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> TypeError: float expected instead of str instance
>
> See? You get type-checking too -- Pascal looms closer and closer!-)
>
> And if you need an array of 1000 such Records, just use as the type
> Record*1000 -- think of the savings in memory (no indirectness, no
> overallocations as lists may have...).
That's very cool Alex! I have just a question: suppose I want
to measure the memory allocation of a million of records made
with ctypes vs the memory allocation of equivalent
records made with __slots__, how do I measure it? Say on Linux,
Mac and Windows?
If ctypes records are more efficient than __slots__ records,
I will ask for deprecation of __slots__ (which is something
I wanted from the beginning!).
Michele Simionato
Bruno Desthuilliers
> Bruno Desthuilliers <bruno.42.de...@wtf.websiteburo.oops.com>
> writes:
>
>> Use dicts, not lists or tuples:
>>
>> a = dict(name='yadda', val=42)
>> print a['name']
>> print a['val']
>
> I guess you will then need a list or tuple to store the dicts?
Should be a list then IMHO. But then it's the correct use of a list : an
homegenous collection.
Steven D'Aprano
> In article <2tqdncU0D6K8v5Ta...@comcast.com>, Steven
> Bethard <steven....@gmail.com> wrote:
>>
>>You can use __slots__ [...]
>
> Aaaugh! Don't use __slots__!
>
> Seriously, __slots__ are for wizards writing applications with huuuge
> numbers of object instances (like, millions of instances). For an
> extended thread about this, see
>
> http://groups.google.com/group/comp.lang.python/browse_thread/
thread/8775c70565fb4a65/0e25f368e23ab058
Well, I've read the thread, and I've read the thread it links to, and for
the life of me I'm still no clearer as to why __slots__ shouldn't be used
except that:
1 Aahz and Guido say __slots__ are teh suxxor;
2 rumour (?) has it that __slots__ won't make it into Python 3.0;
3 inheritance from classes using __slots__ doesn't inherit the slot-
nature of the superclass.
Point 1 is never to be lightly dismissed, but on the other hand Guido
doesn't like reduce(), and I'm allergic to "Cos I Said So" arguments.
History is full of things which were invented for one purpose being used
for something else. So, that being the case, suppose I accept that using
__slots__ is not the best way of solving the problem, and that people of
the skill and experience of Guido and Aahz will roll their eyes and
snicker at me.
But is there actually anything *harmful* that can happen if I use
__slots__?
--
Steven.
Diez B. Roggisch
Point 3 clearly is harmful. As is the fact that __slots__ gives you troubles
if you e.g. pass objects to code that tries to set arbitrary attributes on
an object. While this might be frowned upon, it can be useful in situations
where you e.g. link GUI-code/objects with data-objects: instead of creating
cumbersome, explicit mappings (as you have to in C/C++/Java) or wrappers,
just set a well-named property.
The question is: what does a slot buy you for this kind of problem? And
while arguing with "then I can't set an attribute I didn't want to be set"
is certainly possible, it ultimately leads to the darn
static-vs-dynamic-discussion. Which we might spare us this time.
Diez
Steven D'Aprano
>> Well, I've read the thread, and I've read the thread it links to, and
>> for the life of me I'm still no clearer as to why __slots__ shouldn't
>> be used except that:
>>
>> 1 Aahz and Guido say __slots__ are teh suxxor;
>>
>> 2 rumour (?) has it that __slots__ won't make it into Python 3.0;
>>
>> 3 inheritance from classes using __slots__ doesn't inherit the slot-
>> nature of the superclass.
>>
>>
>> Point 1 is never to be lightly dismissed, but on the other hand Guido
>> doesn't like reduce(), and I'm allergic to "Cos I Said So" arguments.
>>
>> History is full of things which were invented for one purpose being
>> used for something else. So, that being the case, suppose I accept that
>> using __slots__ is not the best way of solving the problem, and that
>> people of the skill and experience of Guido and Aahz will roll their
>> eyes and snicker at me.
>>
>> But is there actually anything *harmful* that can happen if I use
>> __slots__?
>
> Point 3 clearly is harmful.
No, it is DIFFERENT, not harmful. At worst, it's a "gotcha" -- a really
well-documented gotcha.
> As is the fact that __slots__ gives you
> troubles if you e.g. pass objects to code that tries to set arbitrary
> attributes on an object.
You mean like this?
>>> x = 1
>>> x.label = "foo"
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'int' object has no attribute 'label'
I guess that means ints and floats and strings and tuples and lists are
all harmful too, yes?
> The question is: what does a slot buy you for this kind of problem?
Simplicity and explicitness.
--
Steven.
Diez B. Roggisch
> On Mon, 08 Oct 2007 15:15:36 +0200, Diez B. Roggisch wrote:
>
>>> Well, I've read the thread, and I've read the thread it links to, and
>>> for the life of me I'm still no clearer as to why __slots__ shouldn't
>>> be used except that:
>>>
>>> 1 Aahz and Guido say __slots__ are teh suxxor;
>>>
>>> 2 rumour (?) has it that __slots__ won't make it into Python 3.0;
>>>
>>> 3 inheritance from classes using __slots__ doesn't inherit the slot-
>>> nature of the superclass.
>>>
>>>
>>> Point 1 is never to be lightly dismissed, but on the other hand Guido
>>> doesn't like reduce(), and I'm allergic to "Cos I Said So" arguments.
>>>
>>> History is full of things which were invented for one purpose being
>>> used for something else. So, that being the case, suppose I accept that
>>> using __slots__ is not the best way of solving the problem, and that
>>> people of the skill and experience of Guido and Aahz will roll their
>>> eyes and snicker at me.
>>>
>>> But is there actually anything *harmful* that can happen if I use
>>> __slots__?
>>
>> Point 3 clearly is harmful.
>
> No, it is DIFFERENT, not harmful. At worst, it's a "gotcha" -- a really
> well-documented gotcha.
To the casual observer? I doubt it. I wasn't aware of that until a recent
discussion about slots. But then, I've so far _never_ felt the need to use
them...
>
>> As is the fact that __slots__ gives you
>> troubles if you e.g. pass objects to code that tries to set arbitrary
>> attributes on an object.
>
> You mean like this?
>
>>>> x = 1
>>>> x.label = "foo"
> Traceback (most recent call last):
> File "<stdin>", line 1, in <module>
> AttributeError: 'int' object has no attribute 'label'
>
> I guess that means ints and floats and strings and tuples and lists are
> all harmful too, yes?
You are very well aware that I was talking about complex objects. And I
didn't say that they are harmful, but that using __slots__ to constrain
object attribute will lead to surprising results here in comparison to
the "usual" behavior. And with usual I mean
most-of-the-classes-work-that-way. Which might be considered as reason to
_not_ do it. But you are free to limit yourself, be my guest.
>> The question is: what does a slot buy you for this kind of problem?
>
> Simplicity and explicitness.
Where is that more simple? Additional notation that will lead to
runtime-errors, the same way misspelled attribute-names do?
And yes, it is more explicit. As are interfaces, and type declarations.
Diez
Steven Bethard
> In article <2tqdncU0D6K8v5Ta...@comcast.com>,
> Steven Bethard <steven....@gmail.com> wrote:
>> You can use __slots__ [...]
>
> Aaaugh! Don't use __slots__!
>
> Seriously, __slots__ are for wizards writing applications with huuuge
> numbers of object instances (like, millions of instances).
You clipped me saying that __slots__ are for performance tweaks:
You can use __slots__ to make objects consume less memory and have
slightly better attribute-access performance. Classes for objects
that need such performance tweaks should start like...
I fully agree that __slots__ are for applications with huge numbers of
instances. But if you have that situation, you really do want to be
using __slots__.
STeVe
Hrvoje Niksic
> Well, I've read the thread, and I've read the thread it links to,
> and for the life of me I'm still no clearer as to why __slots__
> shouldn't be used except that:
[...]
> But is there actually anything *harmful* that can happen if I use
> __slots__?
Here is one harmful consequence: __slots__ breaks multiple
inheritance:
class A(object):
__slots__ = ['a', 'b']
class B(object):
__slots__ = ['c']
class AB(A, B):
pass
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: Error when calling the metaclass bases
multiple bases have instance lay-out conflict
Even if A and B had the exact same slots, for example ['a', 'b'], it
wouldn't make a difference. AB explicitly setting __slots__ to
something like ['a', 'b', 'c'] doesn't help either. But that is only
a technical answer to your technical question which misses the real
problem people like Aahz and Guido have with __slots__. (I don't
claim to represent them, of course, the following is my
interpretation.)
The backlash against __slots__ is a consequence of it being so easy to
misunderstand what __slots__ does and why it exists. Seeing __slots__
has led some people to recommend __slots__ to beginners as a way to
"catch spelling mistakes", or as a way to turn Python's classes into
member-declared structures, a la Java. For people coming from Java
background, catching mistakes as early as possible is almost a dogma,
and they are prone to accept the use of __slots__ (and living with the
shortcomings) as a rule.
Python power users scoff at that because it goes against everything
that makes Python Python. Use of __slots__ greatly reduces class
flexibility, by both disabling __dict__ and __weakref__ by default,
and by forcing a tight instance layout that cripples inheritance.
With people using __slots__ for the majority of their classes, it
becomes much harder for 3rd-party code to attach an unforeseen
attribute to an existing object. Even with single inheritance,
__slots__ has unintuitive semantics because subclasses automatically
get __dict__ and __weakref__, thereby easily breaking the "benefits"
of their use.
__slots__ is a low-level tool that allows creation of dict-less
objects without resorting to Python/C. As long as one understands it
as such, there is no problem with using it.
Licheng Fang
This is enlightening. Surely I shouldn't have worried too much about
performance before doing some measurement.
Kevin
structs in python?
For example:
FileObject = {
"filename" : None,
"path" : None,
}
fobj = FileObject.copy()
fobj["filename"] = "passwd"
fobj["path"] = "/etc/"
Kevin Kelley
> --
> http://mail.python.org/mailman/listinfo/python-list
>
--
Kevin Kelley
http://technogeek.org/
Steven Bethard
> Am I missing something, or am I the only one who explicitly declares
> structs in python?
>
> For example:
> FileObject = {
> "filename" : None,
> "path" : None,
> }
>
> fobj = FileObject.copy()
> fobj["filename"] = "passwd"
> fobj["path"] = "/etc/"
Yes, I think this is the only time I've ever seen that. I think the
normal way of doing this in Python is:
class FileObject(object):
def __init__(self, filename, path):
self.filename = filename
self.path = path
fobj = FileObject(filename='passwd', path='etc')
STeVe
Joe Riopel
> Am I missing something, or am I the only one who explicitly declares
> structs in python?
> For example:
> FileObject = {
> "filename" : None,
> "path" : None,
> }
>
> fobj = FileObject.copy()
> fobj["filename"] = "passwd"
> fobj["path"] = "/etc/"
I am pretty new to python, but isn't that just a dictionary?
Bjoern Schliessmann
> Am I missing something, or am I the only one who explicitly
> declares structs in python?
Yes -- you missed my posting :)
Regards,
Björn
--
BOFH excuse #209:
Only people with names beginning with 'A' are getting mail this week
(a la Microsoft)
Steven Bethard
> Kevin wrote:
>> Am I missing something, or am I the only one who explicitly
>> declares structs in python?
>
> Yes -- you missed my posting :)
Actually, your posting just used dicts normally.
Kevin is creating a prototype dict with a certain set of keys, and then
copying that dict and filling in the keys each time he creates a new
instance. It's basically a poor man's OOP.
STeVe
Delaney, Timothy (Tim)
> This is enlightening. Surely I shouldn't have worried too much about
> performance before doing some measurement.
And with that statement you have truly achieved enlightenment.
Or to put it another way ... performance tuning without profiling is a
waste of time.
Tim Delaney
Bjoern Schliessmann
> Actually, your posting just used dicts normally.
>
> Kevin is creating a prototype dict with a certain set of keys, and
> then copying that dict and filling in the keys each time he
> creates a new instance. It's basically a poor man's OOP.
And operatively, IMHO, there is no difference.
Regards,
Björn
--
BOFH excuse #176:
vapors from evaporating sticky-note adhesives
Scott David Daniels
And the performance of a programmer both with and without excessive
early performance tweaking has been measured time and again (we do that
particular experiment _way_ too often). The early performance tweaking
version loses almost every time.
-Scott
Aahz
Well, then, just make sure to put big honking warnings up whenever you
mention __slots__. ;-)
kiil...@gmail.com
> $ python -mtimeit -s'class A(object):pass' -s'a=A()' 'a.zop=23'
When I know that all instances of classes inheriting from object have
a namespace, then I would expect either that all objects have a
namespace or that it was inherited from object. I would expect
instantiating object to be the simplest and best way to get a
namespace.
But ...
>>> o = object()
>>> o.foo = 7
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'object' object has no attribute 'foo'
>>> o.__slot__
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
AttributeError: 'object' object has no attribute '__slot__'
>>> class O(object): pass
>>> o = O()
>>> o.foo = 7
That object is kind of "pure virtual" seems to me to be a confusing
special case without any advantages.
Why can't object be instantiated directly? Is that explained and
documented anywhere?
/Mads
Chris Mellon
What makes you think it can't be instantiated directly? You just did
it. It's not, however, suitable for use as an arbitrary thing to stick
attributes on.
Which is a little sad, but a necessary requirement for things like
int() and str() to be small and fast.
kiil...@gmail.com
> On 10/17/07, kiil...@gmail.com <kiil...@gmail.com> wrote:
> > >>> o = object()
> > >>> o.foo = 7
>
> it. It's not, however, suitable for use as an arbitrary thing to stick
> attributes on.
>
> Which is a little sad, but a necessary requirement for things like
> int() and str() to be small and fast.
So it's an optimization with side effects, giving a special case where
the simple and otherwise "right" way to do it doesn't work? Too bad :-
(
Ok; I'll continue to create dummy classes inheriting from object. And
hope that one day it will be simpler.
Thanks,
Mads
Marc 'BlackJack' Rintsch
I'm using the following "dummy" class with a little extra functionality:
def Bunch(object):
def __init__(self, **kwargs):
self.__dict__.update(kwargs)
person = Bunch(name='Eric', age=42)
print person.name
point = Bunch(x=4711, y=23)
Ciao,
Marc 'BlackJack' Rintsch