An important question at least for me is what sort of libraries will be usable from these python instances? Like, I would like to have NumPy and SciPy libraries available for a lot of the heavy computations I do. (in particular, linear algebraic representations of graphs for heuristic solutions to various planning and image processing problems)
I am wondering the same. I have a lot of SciPy and NetworkX based simulation code I have been meaning to plug into web interfaces. This could be extremely useful for academic research.
fat fucking chance at present. Processes must return data within a few seconds, so unless I can take up an arbitrary amount of CPU-hours in those few seconds, there won't be an awful lot of simulation or analysis going on until the TOS changes.
Not that I expected otherwise -- there are plenty of people (like, say, my officemate) who would pay a few bucks to run a few million simulations on Google's infrastructure. (I would too, but it'd have to be a lot of nodes, since I have my own farm of client machines due to the way I arrange consulting)
I hear they are actually CPU starved these days, which quite literally boggles my mind... if Google can run out of cycles, anyone can. But that informs the current deployment and limitations if it is true.
Some aspects of SciPy are a bear to build (I maintained the binary distributions for a couple of years), with a huge dependency chain. I wouldn't bet on being able to install it without a lot of trouble. NumPy isn't so bad.
well, as long as they have NumPy, I can deal with rolling my own ontop the rest. OTOH, what would be amazing would be to have some of these hosting services have a setup where you can execute matlab code and extensions on top! I suppose that that would require a pretty complicated licensing setup though...
