DaveA posted
import random, functools
class Person:
def __init__(self, size):
self.size = size
def __str__(self):
return "Person of size %s" % self.size
class MakePeople:
def __init__(self, random_func):
self.random_func = random_func
def make_them(self, count):
return [Person(self.random_func()) for i in xrange(count)]
people_maker = MakePeople(functools.partial(random.gauss, 100, 2))
persons = people_maker.make_them(100)
for person in persons:
print person.size
I changed the last line, from
print person
print person.size
So this does what I want, but I am not sure why.
I read the entry about functools.partial but it was not very clear to me.
If I
people_maker = MakePeople(random.gauss(100, 2))
then I only get 1 random #.
and if I
MakePeople('random.gauss(100, 2)')
then I just a fix string
So DaveA uses
functools.partial(random.gauss, 100, 2)
not obvious to me from that it should not be
functools.partial(random.gauss(100, 2))
and I guess the other key is
Person(self.random_func())
Also now this
people_maker = MakePeople(123)
does not work, which is not terrible.
Anyone have some more to add, I would not have confidence in applying this
to new situations and it seems.
Also I thank DaveA improving my Python conventions. I am really bad about
that. Is there a cheat sheet for Python conventions.
Like class (Capitals), def (two_words), I guess I should make my own.
Thanks
Vincent Davis
720-301-3003
On Sat, Oct 31, 2009 at 5:55 AM, Dave Angel <da...@ieee.org> wrote:
> Vincent Davis wrote:
>
>> I have a program that generates many instances of a class with an
>> attribute
>> self.x = random.gauss(10, 2). So each instance has a different value for
>> self.x. This is what I want. Now I want to make a class that starts my
>> program and sets the attributes.
>> class people:
>> def __init__(self, size)
>> self.size = size
>>
>> class makepeople:
>> def __init__(self, randomsize)
>> self.rsize = randomsize
>> self.allpeople = []
>> def makethem():
>> for x in range(1,100):
>> p+str(x) = people(self.rsize)
>> allpeople.append(p+str(x))
>>
>> so what I would like to have work is set the attribute of makepeople so
>> that
>> when it is used to make instances of people each will have a different
>> size.
>>
>> listofp = makepeople(random.guass(100, 2))
>> listofp.makethem()
>>
>> I would then what listofp.allpeople to be a list of people with different
>> sizes. The above code does not work, I don't think it does anyway.
>>
>> I hope this makes sense, I am sure there is a term for what I am trying to
>> do but I don't know it.
>>
>> Thanks
>> Vincent Davis
>>
>>
>>
> You're trying to do several things here, and I'm unclear on many of the
> details. So here's a new spec, and the implementation for it.
>
> We want a factory class, which can be given a particular distribution
> function and parameters, and using those parameters generate a list of
> Person objects, whose heights are distributed according to that random
> function. There might be duplicates in that list, but they'd be random
> coincidence, and the list as a whole would be as random as the function
> specified by the caller.
>
> I also took a few liberties on the names of things, trying to use Python
> conventions for naming, and things like using a singular word for a
> classname of a single item. And I removed the allpeople attribute, as the
> class only makes sense to me if you can use its instance multiple times, to
> generate more items with the same given distribution.
>
>
> CODE----
> import random, functools
>
> class Person:
>
> def __init__(self, size):
> self.size = size
> def __str__(self):
> return "Person of size %s" % self.size
>
> class MakePeople:
> def __init__(self, random_func):
> self.random_func = random_func
>
> def make_them(self, count):
> return [Person(self.random_func()) for i in xrange(count)]
>
>
> people_maker = MakePeople(functools.partial(random.gauss, 100, 2))
> persons = people_maker.make_them(100)
> for person in persons:
> print person
>
> /CODE---
>
> DaveA
>
_______________________________________________
Tutor maillist - Tutor@python.org
To unsubscribe or change subscription options:
http://mail.python.org/mailman/listinfo/tutor
