panda3d/doc/INSTALL

Panda3D Install

This document describes how to compile and install Panda 3D on a
system for the first time.  Panda is a complex project and is not
trivial to install, although it is not really very difficult.  Please
do take the time to read this document before starting.

Panda is known to build successfully on Linux, SGI Irix, Windows NT
and Windows 2000.  It should also be easily portable to other
Unix-based OpenGL systems with little or no changes (please let us
know if you try this).  When compiled by Windows NT or 2000, it will
then run on a Windows 95 or 98 system, but we have found that Windows
98 is not itself stable enough to compile the codebase without
crashing.

Presently, Panda does not compile successfully with Microsoft Visual
C++ version 6.0.  You must install Visual C++ 7.0 (that is, Microsoft
Visual Studio .NET) in order to compile Panda on Windows.

Before you begin to compile Panda, there are a number of optional
support libraries that you may wish to install.  None of these are
essential; Panda will build successfully without them, but possibly
without some functionality.

* Python.  Panda is itself a C++ project, but it can generate a
  seamless Python interface layer to its C++ objects and function
  calls.  Since Python is an interpreted language with a command
  prompt, this provides an excellent way to get interactive control
  over the 3-D environment.  However, it is not necessary to use the
  Python interface; Panda is also perfectly useful without Python, as
  a C++ 3-D library.

  Other scripting language interfaces are possible, too, in theory.
  Panda can generate an interface layer for itself that should be
  accessible by any scripting language that can make C function calls
  to an external library.  We have used this in the past, for
  instance, to interface Panda with Squeak, an implementation of
  Smalltalk.  At the present, the Python interface is the only one we
  actively maintain.  We use Python 2.2; you can get Python at
  http://www.python.org .

* NSPR.  This is the Netscape Portable Runtime library, an OS
  compatibility layer written by the folks at Mozilla for support of
  the Netscape browser on different platforms.  Panda takes advantage
  of NSPR to implement threading and network communications.  At the
  present, if you do not have NSPR available Panda will not be able to
  fork threads and will not provide a networking interface.  Aside
  from that, the PStats analysis tools (which depend on networking)
  will not be built without NSPR.  We have compiled Panda with NSPR
  version 3 and 4.0, although other versions should also work.  You
  can download NSPR from http://www.mozilla.org .

* VRPN, the "Virtual Reality Peripheral Network," a peripheral
  interface library designed by UNC.  This is particularly useful for
  interfacing Panda with external devices like trackers and joysticks;
  without it, Panda can only interface with the keyboard and mouse.
  You can find out about it at http://www.cs.unc.edu/Research/vrpn .

* libjpeg and libtiff.  These free libraries provide support to Panda
  for reading and writing JPEG and TIFF image files, for instance for
  texture images.  Even without these libraries, Panda has built-in
  support for pbm/pgm/ppm, SGI (rgb), TGA, BMP, and a few other
  assorted image types like Alias and SoftImage native formats.  Most
  Linux systems come with libjpeg and libtiff already installed, and
  the version numbers of these libraries is not likely to be
  important.  You can download libjpeg from the Independent JPEG group
  at http://www.ijg.org , and libtiff from SGI at
  ftp://ftp.sgi.com/graphics/tiff .

* Gtk--.  This is a C++ graphical toolkit library, and is only used
  for one application, the PStats viewer for graphical analysis of
  real-time performance, which is part of the pandatool package.
  Gtk-- only compiles on Unix, and primarily Linux; it may be possible
  to compile it with considerable difficulty on Irix.  We have used
  version 1.2.1.  You can find it at http://www.gtkmm.org .


PANDA'S BUILD PHILOSOPHY 

Panda is divided into a number of separate packages, each of which
compiles separately, and each of which generally depends on the ones
before it.  The packages are, in order:

  dtool - this defines most of the build scripts and local
    configuration options for Panda.  It also includes the program
    "interrogate," which is used to generate the Python interface, as
    well as some low-level libraries that are shared both by
    interrogate and Panda.  It is a fairly small package.

  panda - this is the bulk of the C++ Panda code.  It contains the 3-D
    engine itself, as well as supporting C++ interfaces like
    networking, audio, and device interfaces.  Expect this package to
    take from one to two hours to build from scratch.  You must build
    and install dtool before you can build panda.

  direct - this is the high-level Python interface to Panda.  Although
    there is some additional C++ interface code here, most of the code
    in this package is Python; there is no reason to install this
    package if you are not planning on using the Python interface.
    DIRECT is an acronym, and has nothing to do with DirectX.
    You must build and install dtool and panda before you can build
    direct.

  pandatool - this is a suite of command-line utilities, written in
    C++ using the Panda libraries, that provide useful support
    functionality for Panda as a whole, like model-conversion
    utilities.  You must build and install dtool and panda before you
    can build pandatool, although it does not depend on direct.

In graphical form, here are packages along with a few extras:

  +------------------------------+
  | Your Python Application Here |
  +------------------------------+
      |
      V
  +--------+  +-----------+  +---------------------------+
  | direct |  | pandatool |  | Your C++ Application Here |
  +--------+  +-----------+  +---------------------------+
      |             |                   |
      +-------------+-------------------/
      V
  +-------+
  | panda |
  +-------+
      |
      V
  +-------+
  | dtool |
  +-------+

The arrows above show dependency.


Usually, these packages will be installed as siblings of each other
within the same directory; the build scripts expect this by default,
although other installations are possible.

In order to support multiplatform builds, we do not include makefiles
or project files with the sources.  Instead, all the compilation
relationships are defined in a series of files distributed throughout
the source trees, one per directory, called Sources.pp.

A separate program, called ppremake ("Panda pre-make") reads the
various Sources.pp files, as well as any local configuration
definitions you have provided, and generates the actual makefiles that
are appropriate for the current platform and configuration.  It is
somewhat akin to the idea of GNU autoconf ("configure"), although it
is both less automatic and more general, and it supports non-Unix
platforms easily.


HOW TO CONFIGURE PANDA FOR YOUR ENVIRONMENT

When you run ppremake within a Panda source tree, it reads in a number
of configure variable definitions given in the file Config.pp in the
root of the dtool package.  Many of these variables will already have
definitions that are sensible for you; some will not.  You must
customize these variables before you run ppremake.

Normally, rather than modifying dtool/Config.pp directly, you would
create your own, empty Config.pp file in a safe place (for instance,
in your personal home directory) and define just the variables you
need there.  The definitions you give in your personal Config.pp file
will override those in the source directory.  You will need to set an
environment variable PPREMAKE_CONFIG to the full filename path of your
personal Config.pp (more on this in the platform-specific installation
notes, below).  It is also possible simply to modify dtool/Config.pp,
but this is not recommended as it makes it difficult to install
updated versions of Panda.

The syntax of the Config.pp file is something like a cross between the
C preprocessor and Makefile syntax.  The full syntax of ppremake
input scripts is described in more detail in another document, but the
most common thing you will need to do is set the value of a variable
using the #define statement.  Look in dtool/Config.pp for numerous
examples of this.

Some of the variables you may define within the Config.pp file hold a
true or a false value by nature.  It is important to note that you
indicate a variable is true by defining it to some nonempty string
(e.g. "yes" or "1"), and false by defining it to nothing.  For
example:
  #define HAVE_DX 1
Indicates you have the DirectX SDK installed, while
  #define HAVE_DX
Indicates you do not.  Do not be tempted to define HAVE_DX to "no" or
"0"; since these are both nonempty strings, they are considered to
represent "true"!

The comments within dtool/Config.pp describe a more complete list of
the variables you may define.  The ones that you are most likely to
find useful are:

  INSTALL_DIR - this is the prefix of the directory hierarchy into
    which Panda should be installed.  By default, this is
    /usr/local/panda, a fine convention for Unix machines although a
    little questionable for Windows environments.

  OPTIMIZE - define this to 1, 2, 3, or 4.  This is not the same thing
    as compiler optimization level; our four levels of OPTIMIZE define
    broad combinations of compiler optimizations and debug symbols:

     1 - No compiler optimizations, full debug symbols
     2 - Full compiler optimizations, full debug symbols
           (if the compiler supports this)
     3 - Full compiler optimizations, no debug symbols, non-debug heap
     4 - Full optimizations, no debug symbols, and asserts removed

    Usually OPTIMIZE 2 or 3 is the most appropriate choice for
    development work.

  PYTHON_IPATH / PYTHON_LPATH / PYTHON_LIBS - the full pathname to
    Python header files, if Python is installed on your system.  As of
    Python version 2.0, compiling Python interfaces doesn't require
    linking with any special libraries, so normally PYTHON_LPATH and
    PYTHON_LIBS are left empty.

  NSPR_IPATH / NSPR_LPATH / NSPR_LIBS - the full pathname to NSPR
    header and library files, and the name of the NSPR library, if
    NSPR is installed on your system.

  VRPN_IPATH / VRPN_LPATH / VRPN_LIBS - the full pathname to VRPN
    header and library files, and the name of the VRPN libraries, if
    VRPN is installed on your system.

  DX_IPATH / DX_LPATH / DX_LIBS - the full pathname to the DirectX 8.1
    SDK header and library files, if you have installed this SDK.
    (You must currently install this SDK in order to build DirectX
    support for Panda.)

  GL_IPATH / GL_LPATH / GL_LIBS - You get the idea.  (Normally, OpenGL
    is installed in the standard system directories, so you can leave
    GL_IPATH and GL_LPATH empty.  But if they happen to be installed
    somewhere else on your machine, you can fill in the pathnames
    here.)



HOW TO BUILD PANDA ON A UNIX SYSTEM

First, make a subdirectory to hold the Panda sources.  This can be
anywhere you like; in these examples, we'll assume you build
everything within a directory called "panda3d" in your home directory.

  mkdir ~/panda3d

You must compile ppremake before you can begin to compile Panda
itself.  Generally, you do something like the following:

  cd ~/panda3d/ppremake
  ./configure
  make
  make install

By default, ppremake will install itself in /usr/local/panda/bin, the
same directory that the other Panda binaries will install themselves
to.  If you prefer, you can install it in another directory by doing
something like this:

  ./configure --prefix=/my/install/directory

If you do this, you will also want to redefine INSTALL_DIR in your
Config.pp to be the same directory (see above).  Wherever you install
it, you should make sure the bin directory is included on your search
path, and the corresponding lib directory (e.g. /usr/local/panda/lib)
is on your LD_LIBRARY_PATH (the following example assumes you are
using a csh derivative):

  set path=(/usr/local/panda/bin $path)
  setenv LD_LIBRARY_PATH /usr/local/panda/lib:$LD_LIBRARY_PATH

If you have a Bourne-shell derivative, e.g. bash, the syntax is:

  PATH=/usr/local/panda/bin:$PATH
  LD_LIBRARY_PATH=/usr/local/panda/lib:$LD_LIBRARY_PATH
  export LD_LIBRARY_PATH

Now you should create your personal Config.pp file, as described
above, and customize whatever variables are appropriate.  Be sure to
set the PPREMAKE_CONFIG environment variable to point to it.

  setenv PPREMAKE_CONFIG ~/Config.pp

In bash:

  PPREMAKE_CONFIG=~/Config.pp
  export PPREMAKE_CONFIG

You may find it a good idea to make these environment settings in your
.cshrc or .bashrc file so that they will remain set for future sessions.

Now that you have ppremake, you can test the configuration settings in
your Config.pp file.

  cd ~/panda3d/dtool
  ppremake

When you run ppremake within the dtool directory, it will generate a
file, dtool_config.h (as well as all of the Makefiles).  This file
will be included by all of the Panda3D sources, and reveals the
settings of many of the options you have configured.  You should
examine this file to ensure that your settings have been made the way
you expect.

Now you can build the Panda3D sources.  Begin with dtool (the current
directory):

  make
  make install

Once you have successfully built and installed dtool, you can then
build and install panda:

  cd ~/panda3d/panda
  ppremake
  make
  make install

After installing panda, you are almost ready to run the program
"pview," which is a basic model viewer program that demonstrates some
Panda functionality.  Successfully running pview proves that Panda is
now installed and configured correctly.  However, you must set up a
Configrc file to set your runtime configuration options before you can
run Panda and open up a graphics window.  See HOW TO RUN PANDA, below.

If you wish, you may also build direct or pandatool:

  cd ~/panda3d/direct
  ppremake
  make
  make install

  cd ~/panda3d/pandatool
  ppremake
  make
  make install



HOW TO BUILD PANDA ON A WINDOWS SYSTEM, USING CYGWIN

Cygwin is a set of third-party libraries and tools that present a very
Unix-like environment for Windows systems.  If you prefer to use a
Unix environment, Cygwin is the way to go.  You can download a free
version from http://www.cygwin.com which will have almost everything
you might need, or you can purchase a CD which has some additional
tools (including csh or bash) that you might find useful.

Panda can build and run within a Cygwin environment, but it does not
require it.  Note that Cygwin is used strictly as a build environment;
the Cygwin compiler is not used, so no dependency on Cygwin will be
built into Panda.  The Panda DLL's that you will generate within a
Cygwin environment will be exactly the same as those you would
generate in a non-Cygwin environment; once built, Panda will run
correctly on any Win32 machine, with or without Cygwin installed.

If you do not wish to install Cygwin for your build environment, see
the instructions below.

If you wish to use Cygwin, there is one important point to keep in
mind.  Panda internally uses a Unix-like filename convention; that is,
forward slashes (instead of backslashes) separate directory
components, and there is no leading drive letter on any filename.
These Unix-like filenames are mapped to Windows filenames (with drive
letters and backslashes) when system calls are made.

Cygwin also uses a Unix-like filename convention, and uses a series of
mount commands to control the mapping of Unix filenames to Windows
filenames.  Panda is not itself a Cygwin program, and does not read
the Cygwin mount definitions.

That's important enough it's worth repeating.  Panda is not aware of
the Cygwin mount points.  So a Unix-like filename that makes sense to
a Cygwin command may not be accessible by the same filename from
within Panda.

However, you can set things up so that most of the time, Cygwin and
Panda agree, which is convenient.  To do this, it is important to
understand how Panda maps Unix-like filenames to Windows filenames.

  * Any relative pathname (that is, a pathname that does not begin
    with a leading slash) is left unchanged, except to reverse the
    slashes.

  * Any full pathname whose topmost directory component is *not* a
    single letter is prepended with the contents of the environment
    variable PANDA_ROOT.

  * Any full pathname whose topmost directory component *is* a single
    letter is turned into a drive letter and colon followed by the
    remainder of the path.  For example, /c/windows/system is turned
    into C:\windows\system.

The expectation is that most of the files you will want to access
within Panda will all be within one directory structure, which you
identify by setting the PANDA_ROOT variable.  Generally, when you are
using Cygwin, you will want to set this variable to be the same thing
as the root of your Cygwin tree.

For instance, typically Cygwin installs itself in C:\Cygwin.  This
means that when you reference the directory /usr/local/bin within
Cygwin, you are actually referring to C:\Cygwin\usr\local\bin.  You
should therefore set PANDA_ROOT to C:\Cygwin, so that /usr/local/bin
within Panda will also refer to C:\Cygwin\usr\local\bin.

To sum up: to use Panda within a Cygwin environment,

In tcsh:

  setenv PANDA_ROOT 'C:\Cygwin'

or in bash:

  PANDA_ROOT='C:\Cygwin'

Follow the instructions under HOW TO BUILD PANDA FOR A UNIX
ENVIRONMENT, above.



HOW TO BUILD PANDA ON A WINDOWS SYSTEM, WITHOUT CYGWIN

You will need a directory for holding the installed Panda.  This can
be anywhere you like; in this example we'll assume you use a directory
called "panda3d" on the root of the C drive.

  md c:\panda3d

Panda3D includes a pre-compiled ppremake.exe, but not the cygwin DLL.
Since ppremake is a Cygwin program (even though the rest of Panda is
not), you will need the DLL in order to run ppremake.

The cygwin1.dll should be available at http://www.cygwin.com

Make sure the Panda bin and lib directories are on your path, and set
a few environment variables for building.  We suggest creating a file
called PandaEnv.bat to hold these commands; then you may invoke this
batch file before every Panda session to set up your environment
properly.  Alternatively, you may make these definitions in the
registry.

  path c:\panda3d\bin;c:\panda3d\lib;%PATH%
  set PANDA_ROOT=c:\
  set PPREMAKE_CONFIG=c:\panda3d\Config.pp

Setting PANDA_ROOT specifies the default drive Panda will search for
file references.  (Panda internally uses a Unix-like filename
convention, which does not use leading drive letters.  See the bullet
points in the Cygwin section, above, describing the rules Panda uses
to map its Unix-like filenames to Windows filenames.)

Now make a directory for building Panda.  This may be different from
the directory, above, that holds the installed Panda files; or it may
be the same.  In this example we assume you will be building in the
same directory, c:\panda3d.

Now set up your personal Config.pp file to control your local
configuration settings, as described above.  We suggest putting it in
the root of the build directory.

  edit c:\panda3d\Config.pp

Add at least the following line to your Config.pp file.  (You may want
to add additional lines, according to your needs.  See HOW TO
CONFIGURE PANDA FOR YOUR ENVIRONMENT, above.)

  #define INSTALL_DIR c:\panda3d

Now you should be able to build dtool.

  c:
  cd \panda3d\dtool
  ppremake
  nmake
  nmake install

And then build panda.

  c:
  cd \panda3d\panda
  ppremake
  nmake
  nmake install

And (optionally) build direct.

  c:
  cd \panda3d\direct
  ppremake
  nmake
  nmake install

And (optionally) build pandatool.

  c:
  cd \panda3d\pandatool
  ppremake
  nmake
  nmake install





HOW TO RUN PANDA

Once Panda has been successfully built and installed, you should be
able to run pview to test that everything is working:

  pview

The first time you run pview, if you have not yet created a Configrc
file, you should see something like this:

  Known pipe types:
  No interactive pipe is available!  Check your Configrc!

If you get instead an error about some shared library or libraries not
being found, check that your LD_LIBRARY_PATH setting (on Unix) or your
PATH (on Windows) include the directory in which all of the Panda
libraries have been installed (That is, $INSTALL_DIR/lib, or whatever
you set INSTALL_DIR to followed by "lib".  On Unix, this defaults to
/usr/local/panda/lib).

If you do get the above error message, you will need to create a
Configrc file to indicate some run-time parameters.  This is different
from the Config.pp file you created above, which is only used by
ppremake to define compile-time parameters; the Configrc file is read
every time Panda is started and it defines parameters that control
run-time behavior.

Create a file called Configrc in your home directory (or wherever you
find convenient).  Note that this file must have no extension; in
particular, it should not have the extension "txt".  Notepad will add
this extension by default, so if you use Notepad to create the file,
you should then rename it so that it does not have the extension
"txt".

For now, add just the line:

  load-display pandagl

Or, if you are on Windows and prefer to use DirectX instead of OpenGL,
add instead the line:

  load-display pandadx

Later you may add additional lines here to control the default
behavior of Panda in other ways.

If you do not specify otherwise, Panda will look for the Configrc file
in the current directory, so for now try to run pview from within the
same directory as your Configrc file.  If all goes well, it should
open up a window with a blue triangle.  You can use the mouse to move
the triangle around.  You can also pass the name of an egg file, if
you have one, on the command line, and pview will load up and display
the egg file.

If you want to load the Configrc from other than the current
directory, set the following two environment variables:

  CONFIG_CONFIG=:configpath=CFG_PATH
  CFG_PATH=/my/home/directory

Where /my/home/directory is the name of your home directory (or
wherever you put the Configrc file).  Note that forward slashes should
be used, according to the Panda convention.  Also note that on
Windows, the path you specify is relative to the directory named by
PANDA_ROOT, unless it begins with a single-letter directory name (see
the explanation of how Panda maps its internal filenames to Windows
filenames, above.)