I think is is great. I haven’t tested yet, but a suggestion to make the process simpler is to let PETSc build suitesparse, etc. PETSc is a C library but can be installed with pip (it has a Python-based build system). It can take care of a number of dependencies (solvers, graph partitioners, etc).
I’ve copied Andy Terrel at Conitnuum Analytics who might have something to chip in with. Garth > On 5 Jan 2015, at 13:07, Juan Luis Cano <[email protected]> wrote: > > Hello all, > > My name is Juan Luis Cano, I'm studying a MSc in Aerospace Engineering in > Madrid and I started recently to play with FEniCS for my final degree > project. For my day to day work I am using a virtualized Linux Mint and > everything works like a charm thanks to the Ubuntu PPA, but as it is not the > distribution which I normally use I tried to build a conda package these > holidays. > > I noticed there are a couple of build systems out there (dorsal, hashdist) > but, as the Anaconda distribution[1] is getting popular in the scientific > Python world these days, I really wanted to try to provide FEniCS packages > for it (at least in Linux). For those who don't know it, Anaconda's package > manager, conda, is open source[2] and provides a nice build system[3]. > > You can try out my progress so far with a Linux 64 bit box and a Python 2.7 > environment: > > $ conda create --name py27 python=2.7 > $ source activate py27 > (py27)$ conda install fenics --channel juanlu001 > > The build process itself was painful because I knew very little about FEniCS > dependencies a week ago but right now I managed to run the `demo_poisson.py` > (_without_ plotting, see below). The results seem OK from Paraview. > > The good thing is that I made the builds in an Ubuntu Server box but it works > the same in an Arch Linux machine too. I didn't try to compile it against > PETSc, Trilinos and such yet because I wanted some feedback from the > community first, and know if this is something useful for anybody! > > The trick here was avoiding the Ubuntu packages (via apt-get) and compile the > dependencies in the form of conda packages themselves. I did such with boost > and suitesparse, for instance[4]. This way there are no linking problems > across different Linux distros. I am stuck with VTK though because it seems > to look for libGL.so, which in turn pulls from X11... and everythings gets > messy very quickly[5]. > > So if I can get some feedback about how does this work in others' computers, > if this is any useful and which packages should I try to build next that > would be great. Anybody can reproduce the build process using my > conda-recipes fork. > > Kind regards and happy new year! > > Juan Luis > > [1] https://store.continuum.io/cshop/anaconda > [2] https://github.com/conda/ > [3] http://conda.pydata.org/docs/build.html > [4] https://binstar.org/juanlu001/ > [5] > https://github.com/Juanlu001/conda-recipes/commit/a18cedc56e330ba09961b8ddaeb86f580e22f3cc > _______________________________________________ > fenics-support mailing list > [email protected] > http://fenicsproject.org/mailman/listinfo/fenics-support _______________________________________________ fenics mailing list [email protected] http://fenicsproject.org/mailman/listinfo/fenics
