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When dealing with a repetitive workflow such as spreadsheet row/column manipulation, there is no support for conditional interaction during a sequential workflow run.

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Originally, Kepler was designed to download data sets into a cache on the machine where it is running, so Kepler actors run as local Java threads. However, in order to provide access to web-based resources, actors have been implemented that spawn distributed execution threads to access distributed resources.

Using Jython in Kepler

Python scripts run in a Jython interpreter within the same JVM as Kepler. This interpreter is only instantiated once so it does not need to be reloaded by each Python actor. On the downside, a global variable set in one actor can cause unexpected side effects if it is reset in another actor. We discovered that if a function is defined as a global (i.e. outside of a class), the method name cannot be reused. The Jython interpreter will always persist the code from the first instantiation of the method.

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Kepler 1.0

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PythonActors use the Jython 2.2.1 interpreter which implements a subset of the Python 2.2 language. See http://www.jython.org/archive/22/index.html for details.

Add-on packages such as FCRepoKepler must be put in the user's home directory under the Lib directory. For example, on a Windows box, this would be C:\Documents and Settings\username\Lib.

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Kepler 2.0 (dev)

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PythonActors use the Jython 2.5.1 interpreter which implements a most of the Python 2.5 language. See Is Jython the same language as Python for details. This is a significant improvement over the version of Jython supplied with Kepler 1.0.

Add-on packages such as FCRepoKepler must be put in the Kepler installation directory under the core/lib/jar/Lib directory.

Using R and MATLAB in Kepler

R  R and Matlab actors require that those applications be installed outside of Kepler. When an associated script is run, the code and data are passed to an external process running R or Matlab.  The actor waits for that process to finish before proceeding. Thus workflows with multiple R/Matlab steps will incur the corresponding application startup overhead for each instance of the actor. This can significantly affect workflow performance. Kepler is a very good tool for building scientific workflows for those who are familiar with software development. However, it is not particularly friendly to those who are used to .  (Google Code project hydrant-kepler discussion of this issue)Originally, Kepler was designed to download data sets into a cache on the machine where it is running, so Kepler actors run as local Java threads. However, in order to provide access to web-based resources, actors have been implemented that spawn distributed execution threads to access distributed resources.

Issues with Kepler 1.0

Python actors use the Jython 2.2.1 interpreter which implements a subset of the Python 2.2 language. See http://www.jython.org/archive/22/index.html for details. The The PythonActor is not in the list of availbale actors. In order to use it you must open one of the Python demo worflows and copy one of those actors to your new workflow.

Make sure you save a copy of all your jython scripts in a file external to Kepler. Python actors PythonActors have a tendency to lose their scripts if they contain a coding error when the workflow is saved. On occasion, we have seen similar behavior when copying PythonActors from one workflow to another. Be sure to save a copy of Jython scripts for ALL PythonActors in a file external to Kepler.

It
I agree with y'all that it should be possible to save fully scripted Python Actors for reuse. So I did some more research and found a poorly documented feature that sometimes saves scripted Python Actors PythonActors in the local Kepler component library. I say sometimes because it may take a few tries to overcome the ActorPythonActor's tendency to lose track of it's script along the way. On occasion, I have seen similar behavior when copying Python Actors from one workflow to another. I had read of these problems online and that is what caused me to hedge on the topic of saving fully configured actors (and also why I keep a copy of the scripts outside of Kepler).

These irregularities in behavior apparently occur because the PythonActor hasn't been integrated into Kelper's Actor repository yet. The only reason we can use copied PythonActors is because the base class is available in the underlying Ptolemy II modeling engine.

New Java actors cannot be dynamically loaded to an installed instance of Kepler 1.0. Incorporating g a new Java actor requires a rebuild of the entire application and consequent rebuild of the actor database. Thus, a small change to an actor under development requires a complete rebuild of Kepler.

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Kepler 2.0 is very promising with a lot of features that will help our project but it has proven to be very buggy at times. Python actors use the Jython 2.5.1 interpreter which implements a most of the Python 2.5 language. See http://wiki.python.org/jython/JythonFaq/GeneralInfo#IsJythonthesamelanguageasPython.3F for details. This is a significant improvement of the version of Jython supplied with Kepler 1.0make life easier for projects that need to extend Kepler's functionality. Most important is the updated module management system that allows new features to be loaded at runtime rather than requiring complete rebuilds from source.

There are several new actors available and the PythonActor is fully integrated into the Kepler actor database. This has improved much of the flakiness seen when using PythonActors in Kepler 1.0. NOTE using Kepler 1.0 to open a workflow that was saved in Kepler 2.0 can cause PythonActors to lose their scripts. Reopening these workflows in Kepler 2.0 will NOT fix them, the scripts must be re-entered from some external source.

Kepler 2.0 is still in development and changes daily, so it has proven to be very buggy at times. On the other hand, the development team does a very good job of letting the community know about critical bugs and then fixing them quickly.

The targeted release date now appears to be early 2010. The Kepler 2.0 Release Roadmap discusses details of what will be included in that release.

Downloads

Kepler 1.0

Download Kepler 1.0 at https://kepler-project.org/users/downloads

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