[bip] Announcing PEBL (and asking for assistance)

[Abhik Shah]

Hi Kevin,
   comments below..

On Tue, Jun 17, 2008 at 6:37 PM, Kevin Teague <kteague at bcgsc.ca> wrote:
>
> On 17-Jun-08, at 2:34 PM, Abhik Shah wrote:
>
>> Installation is currently a bit painful but I'm working on improving that.
>
> Yes, this is common with a great number of scientific toolkits and apps ...
>
> ... I don't follow the science to closely, so I'll only make comments
> regarding installation:
>
> ---
> You can't have imports in setup.py that are required to install by setup.py.
> e.g.:
>
>   import numpy
>   setup(
>    install_requires=[
>        'numpy >= 1.0.3',       # matrices, linear algebra, etc
>
> setup.py won't run unless you've already installed numpy here, but you need
> to run "include_dirs=[numpy.get_include()]" to compile the software.

oops, didn't catch that.. :)
I suppose I can ask users to 'easy_install numpy' first but that just
lengthens the installation steps even more. I'll look into
zc.buildout.

fyi: I've created a bug for this
(http://code.google.com/p/pebl-project/issues/detail?id=18).

Thanks,
Abhik.


>
> ---
> Installing software using easy_install works OK for utility packages (e.g.
> nose), but it can get nasty real quick when using it to install application
> software, since code get's installed on Python's path - e.g. if you install
> Application A and it uses Library B v1.0, and Application C is installed and
> it uses Library B v2.0, next time you use Application A you will find it
> borked :(
>
> If you add instructions for VirtualEnv you can isolate your applications
> installation from the plethora of other applications a user may wish to run
> against their Python interpreter:
>
> http://pypi.python.org/pypi/virtualenv
>
> With VirtualEnv, you can run easy_install without risking breaking other
> previously installed applications.
>
> However, if you have custom build and install steps, you will probably want
> to go beyond hacking on setup.py and use a proper build tool. There are
> quite a few build tools written in Python
> (http://wiki.python.org/moin/ConfigurationAndBuildTools). My current
> favorite is Buildout (http://pypi.python.org/pypi/zc.buildout) with this you
> would:
>
>  1. Add a buildout.cfg file to the root of your project directory.
>
>  2. Write Buildout Recipes for any custom Python code to automate manual
> installation parts (e.g. make the numpy include files available for
> compilation somewhere).
>
> End users could then:
>
>  1. Download your project
>
>  2. Bootstrap the build tool: "python2.5 bootstrap.py"
>
>  3. Run the build, which will download, compile and install all the project
> dependencies: "./bin/buildout"
>
>  4. You may have an alternate build config used for development, e.g.
> "./bin/buildout -c dev.cfg" (would install nose for example)
>
> Everything built by buildout gets installed inside your project directory.
> This is great because if you are just trying something out, you don't have
> to rely on an uninstallation script, or worry about leaving a bunch of
> packages in your site-packages directory.
>
> However, you may find the current documentation for Buildout somewhat
> difficult to get started with. Also, you'll probably find a number of
> packages you depend upon which don't install so easily from source as a
> Python egg so easily (e.g. matplotlib). For trickier packages, I sometimes
> just compile a binary egg, throw it into an Apache directory, and add the
> URL to the project's buildout.cfg find-links directive - this gives the
> build an additional location beyond PyPI where it can fetch packages from -
> e.g. http://www.bcgsc.ca/downloads/parts/software/resources/eggs/
>
> I am using Buildout for Zope, Plone and Grok based projects, whose
> server-side applications can have fairly complex deployments (lots and lots
> of eggs and getting the specific versions of the eggs just right for each
> deployment is very important). When you can walk up to a project you've
> never used with a complex deployment and run "./bin/buildout" and get a
> complete working development environment or application environment, it's a
> beautiful thing :)
>
>
>
>



-- 
Abhik Shah - http://umich.edu/~shahad
Systems Biology Lab, University of Michigan