Now that I’ve recovered from Maker Faire, I can continue documenting what I did. In the lead up to the event, I tried to streamline the FaceCube project as much as possible so visitors wouldn’t have to waste precious Faire time waiting for a print to start. On the hardware side, I kept the extruder and heated bed warmed up to operating temperature and (literally) hot swapped 4″x4″ pieces of glass so that prints could run back to back. I updated the FaceCube script to do capture, cleaning, meshing, scaling, and running through OpenSCAD with a single button press. The remaining bottleneck was running Skeinforge on my geriatric in computer years laptop. Skeinforge is an amazing utility, but written in Python, it is slower than a drunk sloth.
There are ways of speeding up drunk sloths though. Psyco is commonly recommended, but does not support 64 bit architectures. My roommate Will came up with a plan to run a Skeinforge server on PyPy on a faster computer and have a client on my laptop send STLs to it for skeining. We ran out of time on that, but we did get PyPy running normal Skeinforge on my laptop. As of PyPy 1.5, there is support for Tkinter. Following those instructions to install PyPy and Tkinter and run Skeinforge on 64 bit Linux:
wget https://bitbucket.org/pypy/pypy/downloads/pypy-1.5-linux64.tar.bz2 tar -xjvf pypy-1.5-linux64.tar.bz2 cd pypy-c-jit-43780-b590cf6de419-linux64 wget http://peak.telecommunity.com/dist/ez_setup.py ./bin/pypy ez_setup.py ./bin/easy_install tkinter-pypy ./bin/pypy ~/path_to_skeinforge/skeinforge.py
The fonts may look slightly different, but the application should behave the same. Export times should decrease the first couple of times you put a file through as the JIT compiler optimizes and then stay good as long as you keep the process running. On my laptop with a 2.00 GHz Core 2 Duo, Skeinforge runs 2 to 3 times faster on PyPy than on stock CPython 2.6.6. The tested objects were a Weighted Storage Cube, a Flower, Whistle v2, and the Prusa Mendel vertex.