I may be attempting something improper here, but maybe I'm just going
about it the wrong way. I'm subclassing
http.server.CGIHTTPRequestHandler, and I'm using a decorator to add
functionality to several overridden methods.
def do_decorate(func):
. def wrapper(self):
. if appropriate():
.
On Nov 1, 1:13 am, "Gabriel Genellina" wrote:
> Looks like in 3.1 this can be done with bytes+str and viceversa, even if
> bytes and str don't have a common ancestor (other than object; basestring
> doesn't exist in 3.x):
>
> p3> Base = bytes
> p3> Other = str
> p3>
> p3> class Derived(Base):
On Oct 29, 10:41 pm, "Gabriel Genellina"
wrote:
> We know the last test fails because the == logic fails to recognize mySet
> (on the right side) as a "more specialized" object than frozenset (on the
> left side), because set and frozenset don't have a common base type
> (although they share
On Oct 29, 3:54 pm, Mick Krippendorf wrote:
> Jess Austin wrote:
> > That's nice, but it means that everyone who imports my class will have
> > to import the monkeypatch of frozenset, as well. I'm not sure I want
> > that. More ruby than python, ne?
>
> I t
On Oct 28, 10:07 pm, Mick Krippendorf wrote:
> You could just overwrite set and frozenset:
>
> class eqmixin(object):
> def __eq__(self, other):
> print "called %s.__eq__()" % self.__class__
> if isinstance(other, (set, frozenset)):
> return True
> return su
I'm subclassing set, and redefining __eq__(). I'd appreciate any
relevant advice.
>>> class mySet(set):
... def __eq__(self, other):
... print "called mySet.__eq__()!"
... if isinstance(other, (set, frozenset)):
... return True
... return set.__eq__(self, o
Bryan,
You'll get the same result without the lock. I'm not sure what this
indicates. It may show that the contention on the lock and the race
condition on i aren't always problems. It may show that generators, at
least in CPython 2.4, provide thread safety for free. It does seem to
disprove m
I just noticed, if you don't define maxsize in _init(), you need to
override _full() as well:
def _full(self):
return False
cheers,
Jess
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Paul wrote:
>def f():
>lock = threading.Lock()
>i = 0
>while True:
>lock.acquire()
>yield i
>i += 1
>lock.release()
>
> but it's easy to make mistakes when implementing things like that
> (I'm not even totally confident tha
Alex wrote:
> Last, I'm not sure I'd think of this as a reentrantQueue, so
> much as a ReentrantCounter;-).
Of course! It must have been late when I named this class... I think
I'll go change the name in my code right now.
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Thanks for the great advice, Alex. Here is a subclass that seems to
work:
from Queue import Queue
from itertools import count
class reentrantQueue(Queue):
def _init(self, maxsize):
self.maxsize = 0
self.queue = [] # so we don't have to override put()
self.counter =
I guess we think a bit differently, and we think about different
problems. When I hear, "immutable container", I think "tuple". When I
hear, "my own class that is an immutable container", I think, "subclass
tuple, and probably override __new__ because otherwise tuple would be
good enough as is".
msoulier wrote:
> I find that DP junkies don't tend to keep things simple.
+1 QOTW. There's something about these "political" threads that seems
to bring out the best quotes. b^)
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hi,
This seems like a difficult question to answer through testing, so I'm
hoping that someone will just know... Suppose I have the following
generator, g:
def f()
i = 0
while True:
yield i
i += 1
g=f()
If I pass g around to various threads and I want them to always be
y
To be clear, in this simple example I gave you don't have to override
anything. However, if you want to process the values you place in the
container in some way before turning on immutability (which I assume
you must want to do because otherwise why not just use a tuple to begin
with?), then that
Since this is a container that needs to be "immutable, like a tuple",
why not just inherit from tuple? You'll need to override the __new__
method, rather than the __init__, since tuples are immutable:
class a(tuple):
def __new__(cls, t):
return tuple.__new__(cls, t)
cheers,
Jess
--
hi,
I'm not sure why this hasn't come up yet, but this seems to beg for
list comprehensions, if not generator expressions. All of the
following run in under 2 seconds on my old laptop:
>>> alph = 'abcdefghijklmnopqrstuvwxyz'
>>> len([''.join((a,b,c,d)) for a in alph for b in alph for c in alph f
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