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Newsgroups: comp.lang.python
Date: Tue, 12 Mar 2013 22:35:51 -0700 (PDT)
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Subject: Re: How can i create a random array of floats from 0 to 5 in python
From: llanitedave <llanitedave@veawb.coop>
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On Tuesday, March 12, 2013 2:59:29 PM UTC-7, Oscar Benjamin wrote:
> On 12 March 2013 20:21, llanitedave <llanitedave@veawb.coop> wrote:
>=20
> > On Tuesday, March 12, 2013 10:47:25 AM UTC-7, Maarten wrote:
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> >> On Tuesday, March 12, 2013 6:11:10 PM UTC+1, Norah Jones wrote:
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> >>
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> >> > I want to create a random float array of size 100, with the values i=
n the array ranging from 0 to 5. I have tried random.sample(range(5),100) b=
ut that does not work. How can i get what i want to achieve?
>=20
> >>
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> >> Use numpy
>=20
> [SNIP]
>=20
> >
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> > While numpy would work, I fail to see how encouraging the op to downloa=
d and install a separate library and learn a whole new set of tools would b=
e beneficial by default, without knowing the purpose of the need.  This is =
like recommending an RPG to fix a sticky door hinge.
>=20
>=20
>=20
> This suggestion comes after others that show how to use the stdlib's
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> random module. I don't think it's unreasonable to recommend numpy for
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> this. If you want to create *arrays* of random numbers then why not
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> use a library that provides an API specifically for that? You can test
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> yourself to see that numpy is 10x faster for large arrays:
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>=20
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> Python 2.7 on Linux:
>=20
> $ python -m timeit -s 'import random' -- '[random.uniform(0, 5) for x
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> in range(1000)]'
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> 1000 loops, best of 3: 729 usec per loop
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> $ python -m timeit -s 'import random' -- '[random.random() * 5 for x
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> in range(1000)]'
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> 1000 loops, best of 3: 296 usec per loop
>=20
> $ python -m timeit -s 'import numpy' -- 'numpy.random.uniform(0, 5, 1000)=
'
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> 10000 loops, best of 3: 32.2 usec per loop
>=20
>=20
>=20
> I would use numpy for this mainly because if I'm creating arrays of
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> random numbers I probably want to use them in ways that are easier
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> with numpy arrays. There's also a chance the OP might benefit more
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> generally from using numpy depending on what they're working on.
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>=20
>=20
>=20
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> Oscar

I don't think numpy is unreasonable for you or me.  I just started learning=
 it recently, and I'm pretty jazzed about its possibilities.  I obtained an=
 app for work that uses it, and now it's up to me to maintain it, so learni=
ng it is a good idea for me regardless.  Now I'm starting to fantasize abou=
t other things I could do with it.

But the OP appears like a pretty basic beginner, and I really think that fo=
r such a entry-level knowledge scale, we should stick to the standard libra=
ry until they're ready to take on more sophisticated tasks.  "Premature Opt=
imization" is the analogy that comes to mind.