Panda3D provides a safe threading interface you can use, which works very similar to Python’s threading modules. Panda3D is compiled by default to use “true” threading, which makes it safe to use Python threading interfaces (or any other threading library) in conjunction with or in lieu of Panda’s own built-in threading interfaces described below.
If you want to test whether threading is enabled in your build of panda, use the following program:
from panda3d.core import Thread print(Thread.isThreadingSupported())
If threading is enabled, it’s also possible to turn it off, for example if you want to test if a certain problem you are experiencing is related to threading. Put this in your Config.prc:
Panda3D provides several useful functions for loading models and doing other expensive operations in a thread, so the user of your application will not notice chugs in the frame rate.
loader.loadModel call also accepts an optional ‘callback’
argument. If callback is not None, then the model load will be performed
asynchronously. In this case,
loadModel() will initiate a background load
and return immediately. The return value will be an object that may later be
loader.cancelRequest() to cancel the asynchronous request. At some
later point, when the requested model(s) have finished loading, the callback
function will be invoked with the n loaded models passed as its parameter list.
It is possible that the callback will be invoked immediately, even before
loadModel() returns. If you use callback, you may also specify a priority,
which specifies the relative importance over this model over all of the other
asynchronous load requests (higher numbers are loaded first).
True asynchronous model loading requires Panda to have been compiled with
threading support enabled. In the absence of threading support, the asynchronous
interface still exists and still behaves exactly as described, except that
loadModel() might not return immediately.
Similarly, there is
loader.asyncFlattenStrong. This performs a
model.flattenStrong() operation in a sub-thread (if threading is compiled
into Panda). The model may be a single NodePath, or it may be a list of
Each model is duplicated and flattened in the sub-thread. If the optional
inPlace parameter is True, then when the flatten operation completes, the
newly flattened copies are automatically dropped into the scene graph, in place
the original models.
If a callback is specified, then it is called after the operation is finished, receiving the flattened model (or a list of flattened models).
loader.cancelRequest() method works for asyncFlattenStrong as well.
In addition, you can further ask textures to be loaded to the graphics card asynchronously. This means that the first time you look at a particular model, the texture might not be available; but instead of holding up the frame while we wait for it to be loaded, Panda can render the model immediately, with a flat color instead of the texture; and start the texture loading in the background. When the texture is eventually loaded, it will be applied. This results in fewer frame-rate chugs, but it means that the model looks a little weird at first. It has the greatest advantage when you are using lazy-load textures as well as texture compression, because it means these things will happen in the background. You will need these configuration options to enable this behavior:
preload-textures 0 preload-simple-textures 1 texture-compression 1 allow-incomplete-render 1
A similar behavior can be enabled for Actors, so that when you have an Actor
with a large number of animations (too many to preload them all at once), you
can have the Actor load them on-demand, so that when you play an animation, the
animation may not start playing immediately, but will instead be loaded in the
background. Until it is ready, the actor will hold its last pose, and then when
the animation is fully loaded, the actor will start playing where it would have
been had the animation been loaded from the beginning. To make this work, you
have to run all of the animations through
egg-optchar with the
option, and you might also want to set:
allow-async-bind 1 restore-initial-pose 0
If you want to use threading with Panda3D, it’s not recommended to use Python’s built-in threading modules, since you will most likely run into issues (for Panda3D is written in C++ and thus does not use the Python threading modules). However, Panda3D offers a threading implementation that is safe to use, by reimplementing Python’s “thread” and “threading” modules, these work the same as the Python built-in threading modules but are actually safe to use with Panda3D.
You can get access to Panda3D’s implementation of Python’s “thread” module by
importing the “thread” module from
# WRONG: import thread # RIGHT: from direct.stdpy import thread
For the Python module “threading”, Panda3D offers two equivalents, “threading” and “threading2”, which you can find both in direct.stdpy also. The “threading” module implements the threading module with a thin layer over Panda’s threading constructs. As such, the semantics are close to, but not precisely, the semantics documented for Python’s standard threading module. If you really do require strict adherence to Python’s semantics, see the threading2 module instead.
In fact, the threading2 module is a bald-face copy of Python’s threading module from Python 2.5, with a few lines at the top to import Panda’s thread reimplementation instead of the system thread module, and so it is therefore layered on top of Panda’s thread implementation.
However, if you don’t need such strict adherence to Python’s original semantics, the “threading” module is probably a better choice. It is likely to be slightly faster than the threading2 module (and even slightly faster than Python’s own threading module). It is also better integrated with Panda’s threads, so that Panda’s thread debug mechanisms will be easier to use and understand.
# WRONG: import threading # RIGHT: from direct.stdpy import threading # ALSO RIGHT: from direct.stdpy import threading2 as threading
It is permissible to mix-and-match both threading and threading2 within the same application.
Panda3D also offers a thread-safe replacement for the Python file module. You can find it in direct.stdpy.file. The interface is exactly the same as Python’s, so it’s safe to put this import above all the files where you want to use the “file” or “open” functions:
from direct.stdpy.file import *
This module reimplements Python’s file I/O mechanisms using Panda constructs. This enables Python to interface more easily with Panda’s virtual file system, and it also better-supports Panda’s SIMPLE_THREADS model, by avoiding blocking all threads while waiting for I/O to complete.
Compiling Panda3D with threading support¶
There are two different interfaces for threading which you can enable using the definitions HAVE_THREADS and SIMPLE_THREADS. The former is a full and heavy implementation of threading and compiling with that option will slow down the Panda3D build, unless you fully make use of the benefits that threading gives. The latter, however, is a more simple threading interface that doesn’t give you the runtime overhead HAVE_THREADS gives you.
Note that you will have to define both HAVE_THREADS and SIMPLE_THREADS at the same time to enable the simple interface, or you will not have threading.
The public builds enable true threading by default, so you will not need to build Panda3D yourself if you want to take advantage of true threading.
If you wish to disable threading, you can pass the option
--override HAVE_THREADS=UNDEF to makepanda.py. If you wish to use the simple
threading model, you may pass
--override SIMPLE_THREADS=1 instead.