[IPython-user] Trouble importing my own modules?
Tue Jun 12 22:51:28 CDT 2007
> Building on some of the things that Greg asked about, I'm curious,
> what, if any, future plans there are for a "cooperative computing"
> environment. That is, you could imagine that two users would want to
> work on the same data at the same time. Perhaps both updating
> calculations or performing visualizations while communicated over the
> phone or in a chat session.
We definitely want to move in that direction even further as it seems
like something that could be really useful.
> I realize that much of this is possible to the point that two users
> can connect and run commands in the same namespace...but this is not
> really the same as a system designed with cooperative computation in
In my mind being able to run commands in the same namespace (and thus
on the same data) seems to cover most of the usage cases I have come
up with. But, this area is wide open - I don't know of any other
system that even come close in this respect. What other
capabilties/feature do you think would be useful for a full
"cooperative computation" system? I think there is a lot of
interesting work on this front and we are glad to take suggestions or
> On 6/12/07, Fernando Perez <firstname.lastname@example.org> wrote:
> > Hi Greg,
> > sorry but I'll only provide a partial reply right now. I'm at a
> > conference with very limited email access and a bit swamped.
> > On 6/11/07, Greg Novak <email@example.com> wrote:
> > > I'm having trouble importing my own modules into the ipython1 engines.
> > >
> > > First ipython wasn't finding them, in spite of the fact that they were
> > > in the current working directory of the engines. That's strange, but
> > > not a problem--I set PYTHONPATH to include the modules in question and
> > > the modules were found.
> > >
> > > The other problem is that if I just do:
> > > import ipython1.kernel.api as par
> > > rc = par.RemoteController(('localhost', 10105))
> > > rc.executeAll('import analytic')
> > >
> > > Then I get the traceback attached below. However, if I do:
> > >
> > > [rc.execute(i, 'import analytic') for i in rc.getIDs()]
> > >
> > > Then it seems to work. So, I'm reasonably happy since I have a an
> > > easy workaround, but it is strange. This is using a CVS checkout from
> > > May 8.
> > Why don't you try to update saw to current SVN and let us know what
> > happens. The traceback situation is better now (see below).
> > > 1) Thank you for putting this together. My opinion is that high
> > > end/parallel computing sucks these days because the whole mindset
> > > differs from that of desktop computing. On desktops, you have
> > > interactive GUI programs and flexible languages (like Python). On
> > > high-end computers, you have non-interactive batch job systems,
> > > laborious/difficult visualization, and Fortran. Things like ipython1
> > > are a breath of fresh air.
> > Thanks for the kind words :) There's still a LOT to be done, and we
> > know that. It's a big effort and a lot of this is not easy, but we
> > hope you (a collective you, the users) won't lose patience. Work
> > continues...
> > > 2) Is there a way to get better tracebacks? When my code generates
> > > exceptions, the exception is thrown in the bowels of ipython/twisted,
> > > rather than anything indicating what was my actual mistake. I realize
> > > that this may be an impossible task since I pass code to be executed
> > > as a string and after that Python has no good way of figuring out
> > > where in the source file it came from.
> > This is a particularly thorny issue, but is much better in current
> > SVN. Now we generate a full remote traceback on the engine when it
> > happens, and we stuff that as the *value* of the exception. So while
> > you'll still see that ugly local twisted-related traceback (I can't
> > avoid that, unfortunately, because I can't subvert the true local
> > stack with a remote one), at least at the bottom you'll now see a much
> > more informative traceback.
> > > 3) I understand from mailing list posts that the eventual goal is to
> > > have the engines running Ipython rather than plain python instances.
> > > That seems fine as a default, but I'd like to put in a vote for having
> > > it continue to be possible to run plain python instances on the
> > > engines. The reason is a little esoteric...
> > Don't worry. When we say 'ipython in the engines' we don't mean
> > *today's* readline-based ipython. We mean a pure python program that
> > provides things like object introspection, nice tracebacks, etc, but
> > over an API. There will be a *terminal* based ipython that will use
> > such an object to build what looks like today's ipython, and will
> > hence use readline. But the code running in the engines will simply
> > expose the ipython API over a network, so no readline too worry about.
> > > 4) Multiple users. Do you have any ideas or a preferred model for
> > > allowing multiple people to connect to the same controller (and
> > > therefore have access to the same pool of engines?) That would be
> > > truly killer.
> > So far, we've done it just by starting more than one remote controller
> > within a subnet with no firewalls, and it seems to work fine.
> > Security needs to be added for using it in open networks though.
> > While twisted offers a lot in that terrain, we need to actually do the
> > implementation.
> > >
> > > To be concrete, what excites me about ipython1 is the idea of
> > > interactive data analysis. For the most part exploration of data is
> > > limited to what you can do on a single processor because you need to
> > > hook your application up to a GUI. GUIs, being event driven, lead to
> > > the potential of a lot of idle time since the user might have to think
> > > about what he sees for a while before requesting more action.
> > > Typically (in my experience) the only way to run something on a large
> > > computer is to submit a batch job, and then it's supposed to crank
> > > away like mad, not wait for user input via some connection to a GUI.
> > > Therefore it's either practically or politically impossible to harness
> > > a large number of processors for interactive data exploration.
> > >
> > > Hence my interest in multiple users. Let's say you have a cluster
> > > with 100 machines and 4 users. One way to handle this would be to
> > > give each user a separate controller and 25 engines. This is nice
> > > because it insulates users from one another, and a user can be sure
> > > that when he tells his controller to do something, there will be
> > > engines available. However, the downside is that if the four users
> > > are doing interactive data exploration, then there will be a lot of
> > > idle time and user A would benefit from being able to use user B's
> > > engines when they're idle.
> > >
> > > Another way to do it would be to have one controller with access to
> > > all 100 engines. This would be truly killer since it would be as
> > > though you had 100 processors inside your desktop machine. You'd
> > > click "View Some Complicated Plot" and 100 processors would crank away
> > > at generating it, returning the processed data to your desktop where
> > > it's dutifully plotted in a GUI window. The guy in the next office
> > > would be doing the same thing, and unless you both happened to hit
> > > "Plot" at the same moment, you won't notice each other's presence.
> > >
> > > That would be incredible, and would, I think drag high end computing
> > > into the modern era. There's a world of difference in how you think
> > > about things if you're doing it interactively in real-time as opposed
> > > to waiting minutes or hours for the result.
> > What you describe is precisely what we've had in mind for a long time.
> > The infrastructure is getting to that point, though it's not that
> > seamless quite yet. We'll get it though...
> > > Last, an observation which is sure to categorize me as a lunatic: In
> > > poking around the ipython1 code, I came across several places where
> > > source code is laboriously manipulated as strings. That's a heroic
> > > effort, but it makes me sad, because the Lisp people realized the
> > > usefulness of representing source code in one of the language's basic
> > > data structures since its inception in the 60's. And they realized
> > > the usefulness of manipulating source code with the language (via
> > > macros) since the early 70's. And you can add type declarations at
> > > will if you want the compiler to be able to do a better job optimizing
> > > your code. And the compilers compile to native machine code. Those
> > > guys didn't have bad ideas--they just had the misfortune of being 40
> > > years ahead of their time.
> > Yes, unfortunately Python isn't lisp in that regard. There is a way
> > to get to the AST, and in core1/ you'll find some code by Robert Kern
> > that already uses it. But Python doesn't really 'sell' AST
> > manipulations as a user feature, so I honestly don't know exactly what
> > can be done there. Perhaps we can replace some of our current
> > string-munging with more AST work, I don't know. Feel free to pitch
> > in if you notice anything specific of that nature.
> > Cheers, and many thanks for your comments!
> > f
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