On 04/04/2008, Alan G Isaac <[EMAIL PROTECTED]> wrote: > On Fri, 4 Apr 2008, Gael Varoquaux apparently wrote: > > I really thing numpy should be as thin as possible, so > > that you can really say that it is only an array > > manipulation package. This will also make it easier to > > sell as a core package for developpers who do not care > > about "calculator" features. > > > I'm a user rather than a developer, but I wonder: > is this true? > > 1. Even as a user, I agree that what I really want from > NumPy is a core array manipulation package (including > matrices). BUT as long as this is the core of NumPy, > will a developer care if other features are available? > > 2. Even if the answer to 1. is yes, could the > build/installation process include an option not to > build/install anything but the core array functionality? > > 3. It seems to me that pushing things out into SciPy remains > a problem: a basic NumPy is easy to build on any platform, > but SciPy still seems to generate many questions. > > 4. One reason this keeps coming up is that he NumPy/SciPy > split is rather too crude. If the split were instead > something like NumPy/SciPyBasic/SciPyFull/SciPyFull+Kits > where SciPyBasic contained only pure Python code (no > extensions), perhaps the desired location would be more > obvious and some of this recurrent discussion would go away.
It seems to me that there are two separate issues people are talking about when they talk about packaging: * How should functions be arranged in the namespaces? numpy.foo(), scipy.foo(), numpy.lib.financial.foo(), scikits.foo(), numkitfull.foo()? * Which code should be distributed together? Should scipy require separate downloading and compilation from numpy? The two questions are not completely independent - it would be horribly confusing to have the set of functions available in a given namespace depend on which packages you had installed - but for the most part it's not a problem to have several toplevel namespaces in one package (python's library is the biggest example of this I know of). For the first question, there's definitely a question about how much should be done with namespaces and how much with documentation. The second is a different story. Personally, I would prefer if numpy and scipy were distributed together, preferably with matplotlib. Then anybody who used numpy would have available all the scpy tools and all the plotting tools; I think it would cut down on wheel reinvention and make application development easier. Teachers would not need to restrict themselves to using only functions built into numpy for fear that their students might not have scipy installed - how many students have learned to save their arrays in unportable binary formats because their teacher didn't want them to have to install scipy? I realize that this poses technical problems. For me installing scipy is just a matter of clicking on a checkbox and installing a 30 MB package, but I realize that some platforms make this much more difficult. If we can't just bundle the two, fine. But I think it is mad to consider subdividing further if we don't have to. I think python's success is due in part to its "batteries included" library. The fact that you can just write a short python script with no extra dependencies that can download files from the Web, parse XML, manage subprocesses, and save persistent objects makes development much faster than if you had to forever decide between adding dependencies and reinventing the wheel. I think numpy and scipy should follow the same principle, of coming "batteries included". So in this specific case, yes, I think the financial functions should absolutely be included; whether they should be included in scipy or numpy is less important to me because I think everyone should install both packages. Anne _______________________________________________ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
