Getting Started Guide

Patrick Hartling

Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with the Invariant Sections being Appendix A, GNU Free Documentation License, with no Front-Cover Texts, and with no Back-Cover Texts. A copy of the license is included in Appendix A, GNU Free Documentation License.

Table of Contents

What is PyJuggler?
1. Getting the Software
Additional Software
2. Configuring the Environment
3. Running Example Applications
4. Writing Code
Context-Specific Data (vrj::GlContextData<T>)
Clustered Application Data (cluster::UserData<T>)
A. GNU Free Documentation License
ADDENDUM: How to use this License for your documents

List of Examples

4.1. C++ Use of vpr::Interval
4.2. Python Use of PyJuggler.vpr.Interval
4.3. Using PyJuggler.vrj.GlContextData
4.4. Sharing Application Data with PyJuggler.cluster.UserData

What is PyJuggler?

PyJuggler is a collection of Python bindings for the VR Juggler C++ application development framework. With PyJuggler, VR Juggler application objects can be written in Python and loaded into the VR Juggler C++ microkernel. Python application objects can even be intermingled with C++ application objects to allow for multi-language switching between virtual worlds.

The Python bindings that make up PyJuggler are written as C++ modules that the Python interpreter can load at runtime just as it would any other Python module. There are several Python modules, each corresponding to one of the software modules that comprise the larger Juggler framework. For example, the module PyJuggler.gadget contains bindings for the Gadgeteer C++ library.

Chapter 1. Getting the Software

Because PyJuggler follows the well-known layered architecture for software, it is built on top of other tools. These must be downloaded and installed prior to installing PyJuggler to ensure that dependencies are satisfied correctly.

Additional Software

The following is a list of software that is required to utilize PyJuggler, regardless of the type of VR Juggler application that will be written. In other words, these software packages are required to use PyJuggler.

  • Python: The dynamically typed object-oriented scripting language. The version of Python required depends on the requirements of Boost.Python (see the next bullet item), but as of this writing, Python 2.2 or newer is necessary.

  • Boost.Python: The high-level glue between C++ and Python code. PyJuggler requires Boost.Python v2 or newer. The version of Boost.Python used should come from the Boost same version against which VR Juggler was compiled. As of this writing, that is Boost 1.31.0.

  • VR Juggler: The cross-platform, cross-VR system virtual platform for which PyJuggler provides Python bindings. Without VR Juggler, PyJuggler has no purpose. Releases of PyJuggler come shortly after VR Juggler releases. Hence, the latest version of PyJuggler requires the latest version of VR Juggler (2.0 or newer).

  • PyGMTL: Python bindings for the Generic Math Template Library (GMTL). These are required for proper acquisition of GMTL-based data from VR Juggler classes. For example, the transformation matrix for a gadget.PositionInterface object will be returned as a gmtl.Matrix44f object. PyGMTL is developed independently of VR Juggler and PyJuggler, but the version of PyGMTL used must be the same as the version of GMTL that comes with a VR Juggler release.

With those packages installed, one or more of the following will be needed in order to render graphics from the VR Juggler application object:

  • PyOpenGL: Python bindings for the OpenGL graphics API. OpenGL-based VR Juggler applications written in Python use PyOpenGL to make calls into the natively compiled OpenGL libraries on the local system. We have tested with PyOpenGL 2.0.

  • PyOSG: Python bindings for the Open Scene Graph (OSG). OSG-based VR Juggler applications written in Python use PyOSG to make calls to the natively compiled OSG libraries on the local system. If direct OpenGL calls must also be made, then PyOpenGL will be needed (see above). We have tested with PyOSG 0.4.5.


PyJuggler is distributed from the VR Juggler project site. Because PyJuggler is still in the developmental stages, it is recommended that users keep up to date with the latest version at all times. PyJuggler will always keep up to date with the VR Juggler API, and because it provides a one-to-one mapping of C++ to Python, the API will be identical except for slight differences based on Python syntax.

PyJuggler is an open source software library, and as such, its source code is available. Users are free to download the source, look at it, and modify it (keeping in mind the requirements of the license, of course). For the most part, the PyJuggler source code is pretty dull; the interesting aspect is what developers can do to write VR Juggler application objects in Python. As such, the source is provided primarily so that people can compile it for their local hardware and operating system. Some pre-compiled binary versions will exist, but the requirements of those binaries may not satisfy every single user's needs.


PyJuggler comes in a compressed archive format. For UNIX-based environments, we use the well-known tar(1) format for the archive and either gzip(1) (.gz file extension) or bzip2(1) (.bz2 file extension) for the compression. Because pre-compiled versions of PyJuggler are quite large, we normally use the BZIP2 format because it gives a better compression ratio than GZIP. To extract the contents of a BZIP2-compressed TAR file, use the following if GNU tar(1) is not available:

% bzip2 -cd pyjuggler.tar.bz2 | tar -xvf -

If GNU tar(1) is installed (it may be installed as gtar on some systems), use the following simpler command:

% tar -xjvf pyjuggler.tar.bz2

For Win32 environments, we use PKZIP compression (files have a .zip extension). The typical way to extract such an archive is to use the WinZip software. We will not show its use here since it offers a fairly straightforward GUI.

Chapter 2. Configuring the Environment

PyJuggler needs all the environment variables required for execution of normal C++ VR Juggler applications. Additionally, the PyJuggler lib directory must be included in the shared library (DLL) search path so that the library (or pyjutil.dll or libpyjutil.dylib) can be found at module load time. This is normally accomplished by modifying the environment variable LD_LIBRARY_PATH, PATH, or DYLD_LIBRARY_PATH, depending on the operating system. If PyJuggler is installed so that its lib directory is already in the shared library search path, then the library search path does not have to be changed.

With the addition of Python into the mix, it may be necessary to set the PYTHONPATH environment variable. This environment variable tells Python where to look for modules outside of its default path. In other words, it augments the Python module search path to use the directories listed therein.

The need for PYTHONPATH depends on where PyJuggler is installed. If PyJuggler is installed where Python modules are installed by default, then Python will not need any help to find the PyJuggler modules. However, a pre-compiled version of PyJuggler can be installed anywhere (which is good for people who do not have administrative rights on their local system and thus cannot perform system-wide installations). For example, on a UNIX-based system, PyJuggler could be unpacked into $HOME/pyjuggler. If PyJuggler was compiled against Python 2.2, PYTHONPATH would be set as follows (assuming the use of either csh or tcsh as the user's shell):

% setenv PYTHONPATH $HOME/pyjuggler/lib/python2.2/site-packages

For more information about Python, Python modules, and environment variables utilized by the Python interpreter, refer to the on-line Python documentation.


PyOpenGL and PyGMTL may have to be handled similarly to PyJuggler as far as PYTHONPATH is concerned. It may be convenient to install all three in the same place so that only one directory must be specified in PYTHONPATH. Of course, one or both of PyOpenGL or PyGMTL may be installed in the default Python module directory, so this may not be a concern at all.

On Mac OS X, problems have been encountered with the omniORB-based plug-ins that are loaded by the JCCL Config Manager and by the VR Juggler Performance Mediator. Loading of these plug-ins can be disabled by setting the environment variables NO_RTRC_PLUGIN and NO_PERF_PLUGIN respectively. They may be set to any value. Setting these environment variables will prevent a crash inside the omniORB libraries due to static initializatoin problems.


According to users of omniORBpy, setting DYLD_BIND_AT_LAUNCH should be sufficient to fix the static initialization problems within the omniORB C++ libraries when they are loaded into the Python interpreter application space on Mac OS X. Thus far, this has not proven to fix the problem when running a PyJuggler Python application, but there may be something else going wrong. For now, setting the two environment variables described above gets around the omniORB problems within the scope of PyJuggler.

Chapter 3. Running Example Applications

Executing the example PyJuggler applications works very similarly to C++ VR Juggler applications. This is done on purpose to make it easier for people with C++ VR Juggler experience to get started with PyJuggler. Of course, how any given application is written is entirely up to the author; these are simply examples.


In the PyJuggler installation directory, a very simple “pure Python” application can be found under share/pyjuggler/examples/python/simpleGL. The directory contains a single file To execute this application, the following will work in a UNIX-based environment:

% ./ standalone.jconf

For a DOS/Win32 environment, the command is similar:

> python standalone.jconf


For VR Juggler 2.0 Alpha 4 and beyond, the full path to the configuration files does not have to be specified, so it is omitted in the above examples. The file standalone.jconf can be found in the directory $VJ_BASE_DIR/share/vrjuggler/data/configFiles.

This opens a single graphics window showing the default VR Juggler simulator environment and a gray box. Clicking button 1 on the mouse causes the box to be grabbed so that it moves wherever the simulated user's hand moves. Releasing button 1 causes the box to return to its original location. To exit the application, press the ESC key.


This pure-Python application demonstrates the use of context-specific data through PyJuggler. The application can be found under the directory share/pyjuggler/examples/python/contextApp. It contains a single file To execute this application, the following will work in a UNIX-based environment:

% ./ standalone.jconf

For a DOS/Win32 environment, the command is similar:

> python standalone.jconf

This opens a single graphics window showing the default VR Juggler simulator environment and a gray box attached to the wand. To exit the application, press the ESC key. To see the multi-context support in action, run the application as follows:

% ./ sim.base.jconf sim.wand.mixin.jconf sim.c6displays.mixin.jconf


The above will open nine OpenGL windows, which can be very taxing on the graphics hardware. In some cases, it may even crash the computer. The multi-context behavior can be demonstrated through less abusive measures by using sim.c6viewports.mixin.jconf instead of sim.c6displays.mixin.jconf.


PyAppLoader is a C++ application that demonstrates how to load Python modules containing VR Juggler application objects into the VR Juggler microkernel for execution. It can be found in share/pyjuggler/examples/cxx/PyAppLoader under the base PyJuggler installation directory.


PyExtApp is another C++ that shows how Python code can be called from within a C++ VR Juggler application object. The Python function called is quite trivial because the purpose of the application is to show what of the Python/C API must be utilized in order to make things work. The source code can be found in share/pyjuggler/examples/cxx/PyExtApp under the base PyJuggler installation directory.

Chapter 4. Writing Code

In creating PyJuggler and PyGMTL, a conscious effort has been made to keep the Python class interfaces the same, or nearly the same, as the backend C++ class. Reading the VR Juggler Programmer's Guide should be more than sufficient for programmers to learn how to use PyJuggler. The most notable syntactic difference from C++ to Python will be the lack of the :: and -> operators. This difference is illustrated in the following two code blocks. While this example is overly simple, it illustrates the point that the Python interface to a given C++ classes uses the same basic interface.

Example 4.1. C++ Use of vpr::Interval

#include <iostream>
#include <vpr/Util/Interval.h>

void func()
   vpr::Interval i = vpr::Interval::now();
   std::cout << i.sec() << " seconds" << std::endl;

Example 4.2. Python Use of PyJuggler.vpr.Interval

import PyJuggler.vpr as vpr

def func():
   i =
   print i.sec(), "seconds"

With that in mind, there are some important parts of the Juggler C++ interface that do not map well to Python. For example, the context-specific data handler vrj::GlContextData<T> relies on language-level support for templates (more accurately, generic types) and the higher level concept of a smart pointer. Python does not have generic types; indeed, it is an untyped language. In some cases, Python language features have been exploited to make the interfaces more Python-esque so that experienced Python programmers can take advantage of the Python features they know and love. The remainder of this chapter will explain the specific instances where the PyJuggler classes differ from the C++ Juggler classes.

Context-Specific Data (vrj::GlContextData<T>)

Context-specfic data is an important aspect of utilizing the VR Juggler OpenGL Draw Manager. As such, it must be available for authors of VR Juggler application objects who write their application objects in Python. We will not get into the details of context-specific data here and instead refer readers to the relevant parts of the VR Juggler Programmer's Guide.

In a C++ application object, we would define a type instantiation of the generic type vrj::GlContextData<T>. As stated above, Python does not have generic types, so we cannot define our own instantiations of vrj::GlContextData<T> in a Python application object. We can, however, take advantage of the dynamic nature of Python to mimic the semantics of a C++ instantiation of vrj::GlContextData<T>. The result is an easy-to-use Python class that allows dynamic context-specific type construction, conveniently named PyJuggler.vrj.GlContextData.

For each piece of context-specific data that is required by the application object, an instance of PyJuggler.vrj.GlContextData (referred to henceforth as vrj.GlContextData) must exist as a data member in the application object. The vrj.GlContextData instances can then have any number of attributes added to them dynamically. This usage is shown in Example 4.3, “Using PyJuggler.vrj.GlContextData.

Example 4.3. Using PyJuggler.vrj.GlContextData

  1 from OpenGL.GL import *
    import PyJuggler.vrj as vrj
    class MyApp(vrj.GlApp):
  5    def __init__(self):
          # Allocate the context-specific objects.
          self.cube_display_list = vrj.GlContextData()
 10       self.texture_obj       = vrj.GlContextData()
       def contextInit(self):
          # Add an attribute named 'id' that stores a display list ID
          # for this context.
 15 = glGenList(1)
          glNewList(, GL_COMPILE)
          # Define the OpenGL commands for the display list...
 20       # Add an attribute named 'id' that stores a texture object ID
          # for this context.
 = glGenTextures(1)
 25    def draw(self):
          # Requests the display list ID for this context.
          # Set up texture coordinates...
 30       # Render the texture using the texture object ID for this context.

Using instances of vrj.GlContextData has the same basic restrictions as in C++. Reads and writes to the attributes of the vrj.GlContextData instances can only occur when an OpenGL context is active. That is, context-specific data attribute access can occur only in the application object overrides of contextInit(), contextPreDraw(), draw(), contextPostDraw(), and contextClose(). This usage is shown in more detail in the example Python application share/pyjuggler/examples/contextApp/

Clustered Application Data (cluster::UserData<T>)

The cluster feature of VR Juggler includes support for sharing user-defined data types across the nodes of the cluster. This is achieved through the use of the generic type cluster::UserData<T> where T must be a subclass of vpr::SerializableObject. Programmers must implement overrides of the pure virtual methods vpr::SerializableObject::readObject() and vpr::SerializableObject::writeObject(), which serialize and de-serialize the object respectively. In Python terms, this corresponds directly to pickling and unpickling an object. This correlation provides the foundation for the access to cluster::UserData<T> through PyJuggler[1].

Clustered application data is implemented using the class PyJuggler.cluster.UserData, henceforth referred to as cluster.UserData. This class takes advantage of Python language features to provide a more powerful, flexible data sharing mechanism that is easier to use than its C++ counterpart. An instance of cluster.UserData can share any Python data structure that can be pickled. Since most Python types can be pickled automatically, there is no need for application programmers to write any code for serializing and de-serializing their data structures. Furthermore, the dynamic nature of Python types allows the shared data structures to change at run time. Multiple instances of cluster.UserData can be used to share multiple data structures, or the multiple data structures can be aggregated into a single Python object that is shared via a single cluster.UserData instance.

The use of cluster.UserData is shown in Example 4.4, “Sharing Application Data with PyJuggler.cluster.UserData. Just as with cluster::UserData<T>, the clustered data must be initialized in the application object's init() method using a GUID. After the cluster.UserData object is initialized, the Python object to be shared must be registered through the method cluster.UserData.setPickleObject(). All nodes in the cluster must perform these actions.

Example 4.4. Sharing Application Data with PyJuggler.cluster.UserData

  1 import gmtl
    from PyJuggler import *
    class ClusterApp(vrj.GlApp):
  5    def __init__(self):
          self.user_data = cluster.UserData()
          self.nav_matrix = gmtl.Matrix44f()
       def init(self):
 10       self.user_data.init(vpr.GUID("2bbad1af-27c4-11d9-bd0d-00045a86e9cd"))
       def preFrame(self):
          if self.user_data.isLocal():
 15          nav_delta = gmtl.Matrix44f()
             # Calculate navigation change...
             gmtl.postMult(self.nav_matrix, nav_delta)
       def draw(self):
 20       glPushMatrix()
          # Render the scene...

Once the shared data is registered with the cluster.UserData instance, only the application data host node should be allowed to write to the shared data. If any other node writes to the shared data, the changes will be lost the next time the shared data is unpickled. The application data host node can be determined using the method cluster.UserData.isLocal(), just as in the C++ counterpart. Any node can read from the shared data. Note that, unlike the of cluster::UserData<T> in C++, the shared data can be accessed directly. Indeed, it must be accessed directly as there is no smart pointer semantics associated with cluster.UserData. While this makes shared application data use easier in Python than in C++, it is also more efficient because there is no extra level of indirection.

As noted above, most shared data structures will not require any special code to allow pickling and unpickling. Refer to the Python object pickling documentation. More specifically, refer to the documentation on what can be pickled and unpickled.


As of this writing, the only PyJuggler classes that can be pickled are PyJuggler.vpr.Interval and PyJuggler.vpr.GUID. If any other PyJuggler class instances are stored in an object shared across the cluster via cluster.UserData, pickling will fail. All data types in PyGMTL can be pickled.

[1] It is assumed that the reader is already familiar with the use of cluster::UserData<T> in C++. Those readers who are not familiar with this class should refer to the appropriate chapter of the VR Juggler Programmer's Guide for details.

Appendix A. GNU Free Documentation License

Version 1.2, November 2002

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You may combine the Document with other documents released under this License, under the terms defined in section 4 above for modified versions, provided that you include in the combination all of the Invariant Sections of all of the original documents, unmodified, and list them all as Invariant Sections of your combined work in its license notice, and that you preserve all their Warranty Disclaimers.

The combined work need only contain one copy of this License, and multiple identical Invariant Sections may be replaced with a single copy. If there are multiple Invariant Sections with the same name but different contents, make the title of each such section unique by adding at the end of it, in parentheses, the name of the original author or publisher of that section if known, or else a unique number. Make the same adjustment to the section titles in the list of Invariant Sections in the license notice of the combined work.

In the combination, you must combine any sections Entitled "History" in the various original documents, forming one section Entitled "History"; likewise combine any sections Entitled "Acknowledgements", and any sections Entitled "Dedications". You must delete all sections Entitled "Endorsements".


You may make a collection consisting of the Document and other documents released under this License, and replace the individual copies of this License in the various documents with a single copy that is included in the collection, provided that you follow the rules of this License for verbatim copying of each of the documents in all other respects.

You may extract a single document from such a collection, and distribute it individually under this License, provided you insert a copy of this License into the extracted document, and follow this License in all other respects regarding verbatim copying of that document.


A compilation of the Document or its derivatives with other separate and independent documents or works, in or on a volume of a storage or distribution medium, is called an "aggregate" if the copyright resulting from the compilation is not used to limit the legal rights of the compilation's users beyond what the individual works permit. When the Document is included in an aggregate, this License does not apply to the other works in the aggregate which are not themselves derivative works of the Document.

If the Cover Text requirement of section 3 is applicable to these copies of the Document, then if the Document is less than one half of the entire aggregate, the Document's Cover Texts may be placed on covers that bracket the Document within the aggregate, or the electronic equivalent of covers if the Document is in electronic form. Otherwise they must appear on printed covers that bracket the whole aggregate.


Translation is considered a kind of modification, so you may distribute translations of the Document under the terms of section 4. Replacing Invariant Sections with translations requires special permission from their copyright holders, but you may include translations of some or all Invariant Sections in addition to the original versions of these Invariant Sections. You may include a translation of this License, and all the license notices in the Document, and any Warranty Disclaimers, provided that you also include the original English version of this License and the original versions of those notices and disclaimers. In case of a disagreement between the translation and the original version of this License or a notice or disclaimer, the original version will prevail.

If a section in the Document is Entitled "Acknowledgements", "Dedications", or "History", the requirement (section 4) to Preserve its Title (section 1) will typically require changing the actual title.


You may not copy, modify, sublicense, or distribute the Document except as expressly provided for under this License. Any other attempt to copy, modify, sublicense or distribute the Document is void, and will automatically terminate your rights under this License. However, parties who have received copies, or rights, from you under this License will not have their licenses terminated so long as such parties remain in full compliance.


The Free Software Foundation may publish new, revised versions of the GNU Free Documentation License from time to time. Such new versions will be similar in spirit to the present version, but may differ in detail to address new problems or concerns. See

Each version of the License is given a distinguishing version number. If the Document specifies that a particular numbered version of this License "or any later version" applies to it, you have the option of following the terms and conditions either of that specified version or of any later version that has been published (not as a draft) by the Free Software Foundation. If the Document does not specify a version number of this License, you may choose any version ever published (not as a draft) by the Free Software Foundation.

ADDENDUM: How to use this License for your documents

To use this License in a document you have written, include a copy of the License in the document and put the following copyright and license notices just after the title page:

Sample Invariant Sections list

Copyright (c) YEAR YOUR NAME. Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with no Invariant Sections, no Front-Cover Texts, and no Back-Cover Texts. A copy of the license is included in the section entitled "GNU Free Documentation License".

If you have Invariant Sections, Front-Cover Texts and Back-Cover Texts, replace the "with...Texts." line with this:

Sample Invariant Sections list

with the Invariant Sections being LIST THEIR TITLES, with the Front-Cover Texts being LIST, and with the Back-Cover Texts being LIST.

If you have Invariant Sections without Cover Texts, or some other combination of the three, merge those two alternatives to suit the situation.

If your document contains nontrivial examples of program code, we recommend releasing these examples in parallel under your choice of free software license, such as the GNU General Public License, to permit their use in free software.