Sorry to be late on this thread, but I was out of town, and I do feel strongly about this issue.
Gael Varoquaux wrote: > For the beginner, "from numpy.all import *" is more confusing than "from > numpy import *" (which is already confusing). except that the beginner, nor anyone else, should ever use "import *" anyway! > I know namespace are good things, but the beginner struggles with them. > This is why I used the "import *" in my above examples. You're better off with a good foundation -- really. And particularly for a beginner, knowing what comes from numpy, and what from python (or other packages) is a "good thing". It's a mixed bag, but I like namespaces a lot -- there's a lot to be said for thinking: I need some stats, an doing something like: from numpy.stats import stats That being said, having a numpy.all namespace has its uses, particularly for interactive use, but let's not make it the default. Look at history here: Everyone used to do "from Numeric import *", now many (most?) folks use the numpy namespace, with something like "import numpy as N". Matplotlib started out with a Matlab like: "from pylab import *", now there is a separate namespace for plotting, etc, and a movement towards using separate namespaces. "Namespaces are one honking great idea -- let's do more of those!" That's "more", not "fewer" Gael Varoquaux wrote: > Convention are important, especially in coding. This is really, really important. What if we all used a different name for "self?" -- just as correct, but it would be a lot harder to understand other's code. I really don't get the reluctance -- EVERY major package I've worked with has moved AWAY from "import *" (numpy, wxPython, matplotlib, ...). We should never, never, recommend it to beginners. Period. And it would be very nice to use a standard. I use "import numpy as N", but would be quite happy to use "np" or "nx", or anything else short that becomes a standard. > IMHO the > pylab option is quite nice: matplotlib is nice and modular, but pylab has > it all. Use whichever you want. I disagree -- with pylab and numpy, there is constant confusion from folks as they move past the beginner stage -- "where did that function come from?", "What do I have to change now that I'm embedding my MPL code in a GUI?" "There should be one-- and preferably only one --obvious way to do it." Maybe there is a large population of folks that never do move past the beginner stage -- but I say -- let then use Octave! I use Python specifically because it's a more sophisticated language than Matlab. > The only thing > namespaces solve is name collisions imho. The other one is readability -- I like knowing where things come from, and what that have to do with. This is really an augment against "import *", but it applied to hierarchical namespaces too -- you can see the structure in the code, -- I like that. > I don't believe that the > current numpy has too many names in its basic namespace, It's a little too big, rather than a lot too small though -- remember this thread started from "where do we put financial functions". > and it > already has split out some things into subpackages (fft, random, > linear algebra) that have such a potential. exactly -- so numpy.finance fits right in... > 3) Some don't like the bloat (in disk space or download sizes) of > adding things to numpy. In my case, as long as the addition doesn't > make installations any more difficult I don't care. +1 Easy of installation is far more important than download size. Brian Granger wrote: > Simply putting things into > numpy because of convenience (numpy is easier to install) only > encourages people to never install or use scipy. Actually it's worse -- it discourages us from making scipy easier to install. I still don't use it. But we can save most of this for 1.1 (or 2.0, or...) -Chris -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R (206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
