Matimus,
I was surprised that "lazy" was the algorithm that won your time tests, and
I saw a way to improve it even better (algorithm is O(# ones in number)
rather than O(# bits in number))
def lazy2(a, b, bits=32):
x = (a ^ b) & ((1 << bits) - 1)
tot = 0
while x:
tot += 1
You could overload __getattr__ (might have to play around a bit to make sure
any possible AttributeError's look right, but the basic idea is here)
class A(object):
# ...
def __getattr__(self, name):
try:
return object.__getattribute__(self, name)
except AttributeError:
> pred = EveryOtherOne()
>>> lst = [1,2,2,1]
>>> extracted = [ obj for obj in lst if pred(obj) ]
>>> extracted
[2, 1]
>>> lst = [ obj for obj in lst if obj not in extracted ]
>>> lst
[]
On Wed, Apr 23, 2008 at 6:14 PM, Brian <[EMAIL PROTECTED]> wro
classes
to handle.
I haven't found a function that will both remove objects from a list, but
save the ones that do get removed.
Jared
On 23 Apr 2008, at 10:15, Tim Golden wrote:
Jared Grubb wrote:
I want a function that removes values from a list if a predicate evaluates
to True. The b
I want a function that removes values from a list if a predicate evaluates
to True. The best I could come up with is:
def extract(lst, pred):
idx = 0
ret = []
for obj in lst[:]:
if pred(obj):
ret.append(obj)
lst.pop(idx)
else:
idx +=
I think bearophile makes an excellent point. I also have a hard time
remembering what else does.
I have always pictured that the "normal" behavior of a for loop is to get
through all the items. In special circumstances, it is necessary to break
out early. Therefore, it FEELS like the else loop shou
Er, instead of "getattr(self,...) you gotta do
"object.__getattr__(self,...)" and same for setattr and delattr. Dumb error
on my part. (Otherwise you get infinite recursion!)
On Feb 6, 2008 12:43 PM, Jared Grubb <[EMAIL PROTECTED]> wrote:
> Here's one way of doing
Here's one way of doing what you're asking... I would suggest using
__getattribute__ and __setattr__ to dispatch the methods to the custom class
you invent that holds all those properties.
For example (I simplified your makeprops into __init__ just to keep the
example short, but you can probably s
Quine-McCluskey isn't too bad to do once or twice by hand, but if you change
even one row in your dataset, you'll have to repeat the ENTIRE Q-M
algorithm. It gets very tedious. For your application, I'd just use a hash
table. You dont need the reduced form of your data, you just need a look-up
tabl
You should look into the struct module. For example, you could do the same
thing via (using the variable names you used before):
header_str = info.read(13)
a,b,c,d,e = struct.unpack("6s4sBBB", header_str)
After that, you will probably be able to get the integers by (doing it one
at a time... read'
You could also do:
"".join(['%02x' % ord(c) for c in 'AAA'])
On 31 Jan 2008, at 14:09, Paul Rubin wrote:
Antonio Chay <[EMAIL PROTECTED]> writes:
"AAA" should be "414141"
'AAA'.encode('hex')
--
http://mail.python.org/mailman/listinfo/python-list
On 31 Jan 2008, at 14:05, Antonio Chay wrot
How can I iterate through the slots of a class, including those it inherits
from parent classes?
class C(object):
__slots__ = ['a']
class D(C):
__slots__ = ['b']
>>> d = D()
>>> d.__slots__
['b']
>>> d.a = 1 # this works, so slots inherit properly
>>> d.b = 2
>>> d.c = 3 # this doesnt work,
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