I'm building a rendering engine in Python for fun. I need to load 3D scenes. Any standard modern format like DAE, 3DS, or MAX would work: I can convert my files easily between standard formats.
OpenSceneGraph seems to be the most comprehensive and well-maintained solution. It would be ideal to be able to use it in Python without much hassle. Are there working Python bindings for OSG that are easy to install, work on Mac OS X (I'm on 10.8), and are compatible with the latest versions of OSG?
I searched around and came across osgswig (http://code.google.com/p/osgswig/) and PyOSG (http://sourceforge.net/projects/pyosg/), but they don't seem to be actively maintained. I don't see any recent activity related to these packages, and it seems that people had trouble running osgswig on OSX. Ideally, I'd like to find something that "just works", without major compilation hassles. I'd like to just install a package and be able to import a module that will let me load COLLADA or 3DS files.
I also came across pycollada (https://github.com/pycollada/pycollada). It seems active, but fairly early-stage. Ideally, I'd like a reasonably comprehensive package that supports specular maps, normal maps, and other reasonably advanced features. Animation would be nice as well.
In summary, I need to load 3D scenes in Python. Bindings for OSG would probably be ideal, because OSG is so comprehensive. But I need something that works on OSX. I would also prefer something that can be installed reasonably easily. Does something like this exist?
Thanks!
Take a look at Open Asset Import Library (short name: Assimp). It is a portable Open Source library to import various well-known 3D model formats in a uniform manner. http://www.assimp.org/
You should loot at panda3D (http://www.panda3d.org/), it's a game engine with extensive python bindings. It has the features you want : http://www.panda3d.org/manual/index.php/Features
I used it for a few years and it was a solid tool.
I made my own fork of a mirror of a clone of the osgswig project for a similar purpose. I have it working with OpenSceneGraph version 3.2.1 on Windows and Mac; and it's likely I will eventually polish it for linux too. I'm already delivering one product to customers based on my version of osgswig, and I'm considering making others. Find my fork here:
https://github.com/cmbruns/osgswig
If others show enough interest, I might be coaxed into creating binary installers for my version of the osgswig module, to make installation easier.
If you just want the easiest OpenSceneGraph bindings for OSG 3.2.1, you can stop reading this answer here. Read on for more of my thoughts for the future.
Though I am maintaining a fork of osgswig (as stated above), I sort of hate SWIG, and I would prefer to use bindings based on Boost.Python, rather than on SWIG. For large, complex C++ APIs, like OpenSceneGraph, Boost.Python can be much more elegant than SWIG, both for the API consumer, and for the binding maintainer (me, and me). I found one project using Boost.Python to wrap OSG, at https://code.google.com/p/osgboostpython/, but the developer is lovingly wrapping each part of the interface by hand, and has thus only completed a tiny fraction of the large OpenSceneGraph API.
Taking that Boost.Python based project as inspiration, I created yet another OpenSceneGraph Python binding project, at https://github.com/JaneliaSciComp/osgpyplusplus. Eventually, I want to use this osgpyplusplus project for all my python osg needs. And I would appreciate help in making it ready. Right now, osgpyplusplus suffers from the following weaknesses, compared to osgswig:
osgpyplusplus is not yet used in any working product
The build environment is tricky to set up, requiring both Boost.Python and Pyplusplus
I haven't paid much attention to osgpyplusplus recently, so it might rust away if I continue to ignore it.
Though osgpyplusplus probably wraps most of the OpenSceneGraph API, there are probably some important missing pieces that won't be identified until someone tries to develop a significant project with it.
It would be a lot of work for me to create a binary module installer for osgpyplusplus at this point, so please don't ask me to.
Related
So it's a new millennium; Apple has waved their hand; it's now legal to include a Python interpreter in an iPhone (App Store) app.
How does one go about doing this? All the existing discussion (unsurprisingly) refers to jailbreaking. (Older question: Can I write native iPhone apps using Python)
My goal here isn't to write a PyObjC app, but to write a regular ObjC app that runs Python as an embedded library. The Python code will then call back to native Cocoa code. It's the "control logic is Python code" pattern.
Is there a guide to getting Python built in XCode, so that my iPhone app can link it? Preferably a stripped-down Python, since I won't need 90% of the standard library.
I can probably figure out the threading and Python-extension API; I've done that on MacOS. But only using command-line compilers, not XCode.
It doesn't really matter how you build Python -- you don't need to build it in Xcode, for example -- but what does matter is the product of that build.
Namely, you are going to need to build something like libPython.a that can be statically linked into your application. Once you have a .a, that can be added to the Xcode project for your application(s) and, from there, it'll be linked and signed just like the rest of your app.
IIRC (it has been a while since I've built python by hand) the out-of-the-box python will build a libPython.a (and a bunch of other libraries), if you configure it correctly.
Of course, your second issue is going to be cross-compiling python for ARM from your 86 box. Python is an autoconf based project and autoconf is a pain in the butt for cross-compilation.
As you correctly state, making it small will be critical.
Not surprising, either, is that you aren't the first person to want to do this, but not for iOS. Python has been squeezed into devices much less capable than those that run iOS. I found a thread with a bunch of links when googling about; it might be useful.
Also, you might want to join the pyobjc-dev list. While you aren't targeting a PyObjC based application (which, btw, is a good idea -- PyObjC has a long way to go before it'll be iOS friendly), the PyObjC community has been discussing this and Ronald, of anyone, is probably the most knowledgeable person in this particular area. Note that PyObjC will have to solve the embedded Python on iOS problem prior to porting PyObjC. Their prerequisite is your requirement, as it were.
I've put a very rough script up on github that fetches and builds python2.6.5 for iPhone and simulator.
http://github.com/cobbal/python-for-iphone
Work in progress
Somewhat depressing update nearly 2 years later: (copied from README on github)
This project never really got python running on the iPhone to my
satisfaction, and I can't recommend using it for any serious project
at this stage.
Most notably missing is pyobjc support (which turns out to be much
harder to port to iPhone since it relies on more platform-specific
code)
Also missing is the ability to statically compile modules, (all are
currently built as dylibs which works for development, but to my
knowledge wouldn't be allowed in the App Store)
At this point this project is mostly meant to be a starting point for
anyone smarter than me who wants to and can tackle the above issues.
I really wish it were practical to write apps entirely in Python, but
at this point it seems impossible.
I also started such a project. It comes with its own simplified compile script so there is no need to mess around with autoconf to get your cross compiled static library. It is able to build a completely dependency-free static library of Python with some common modules. It should be easily extensible.
https://github.com/albertz/python-embedded/
So I am working on setting up an agent-based model that runs over a geographic map--syria in this case. I tried writing it in python, but the performance is rather slow--even after some optimization tricks. I was thinking that I should shift to just writing the model in C++, but I don't know which visualization packages can incorporate maps? I tend to use gnuplot in C++, but I have not been able to find a way to incorporate a gis basemap in that package. I am not sure if this is possible in VTK or any other packages. I would like to find a way to run my model fast in C++ but not lose the geographic information. Any suggestions?
Perhaps this project could be useful to you ?
http://code.google.com/p/vtk-grass-bridge/
If you can handle your GIS data using GRASS, it seems that project can convert it to something VTK can render, all in one C++ application.
So I actually figured out the answer to this problem and am posting the solution for everyone. The best choice if you are using python, is to just use the mayavi and tvtk packages from Enthought. Mayavi is a gui on top of the C++ VTK libraries. And tvtk is actually a wrapper for python access to VTK objects. So this allows a person to use python GIS packages--like pyshp, Shapely, and others to manipulate GIS objects and then write them to robust and fast mayavi for visualization. At the same time, if you want to stick to C++ then you can still just write your code in C++ using gdal or ogr, etc., and then run your visualization in VTK. This seems a lot easier and more intuitive then trying to run through some other packages like GRASS, QGIS, or ArcGIS.
Here is a good example of this toolset in action.
Example
What makes you believe that a C++ implementation of your model will be dramatically faster? I suggest before being concerned with how you will visualize the results you focus first on what causes your python implementation to be slow. Is it that your algorithm won't scale? If you have tried optimization tricks, what tricks were those and why do you believe they did not work?
It all eventually comes down to machine instructions being executed on hardware, whether those instructions started out as python, C++ , or some other language source code. Unless your python was running fully interpreted all the time I don't think you will find that switching languages alone will cause you to have a fundamentally different performance profile. Premature optimization is still something to be avoided.
Is it possible to deploy python applications such that you don't release the source code and you don't have to be sure the customer has python installed?
I'm thinking maybe there is some installation process that can run a python app from just the .pyc files and a shared library containing the interpreter or something like that?
Basically I'm keen to get the development benefits of a language like Python - high productivity etc. but can't quite see how you could deploy it professionally to a customer where you don't know how there machine is set up and you definitely can't deliver the source.
How do professional software houses developing in python do it (or maybe the answer is that they don't) ?
You protect your source code legally, not technologically. Distributing py files really isn't a big deal. The only technological solution here is not to ship your program (which is really becoming more popular these days, as software is provided over the internet rather than fully installed locally more often.)
If you don't want the user to have to have Python installed but want to run Python programs, you'll have to bundle Python. Your resistance to doing so seems quite odd to me. Java programs have to either bundle or anticipate the JVM's presence. C programs have to either bundle or anticipate libc's presence (usually the latter), etc. There's nothing hacky about using what you need.
Professional Python desktop software bundles Python, either through something like py2exe/cx_Freeze/some in-house thing that does the same thing or through embedding Python (in which case Python comes along as a library rather than an executable). The former approach is usually a lot more powerful and robust.
Yes, it is possible to make installation packages. Look for py2exe, cx_freeze and others.
No, it is not possible to keep the source code completely safe. There are always ways to decompile.
Original source code can trivially be obtained from .pyc files if someone wants to do it. Code obfuscation would make it more difficult to do something with the code.
I am surprised no one mentioned this before now, but Cython seems like a viable solution to this problem. It will take your Python code and transpile it into CPython compatible C code. You also get a small speed boost (~25% last I checked) since it will be compiled to native machine code instead of just Python byte code. You still need to be sure the user has Python installed (either by making it a pre-requisite pushed off onto the user to deal with, or bundling it as part of the installer process). Also, you do need to have at least one small part of your application in pure Python: the hook into the main function.
So you would need something basic like this:
import cython_compiled_module
if __name__ == '__main__':
cython_compiled_module.main()
But this effectively leaks no implementation details. I think using Cython should meet the criteria in the question, but it also introduces the added complexity of compiling in C, which loses some of Python's easy cross-platform nature. Whether that is worth it or not is up to you.
As others stated, even the resulting compiled C code could be decompiled with a little effort, but it is likely much more close to the type of obfuscation you were initially hoping for.
Well, it depends what you want to do. If by "not releasing the source code" you mean "the customer should not be able to access the source code in any way", well, you're fighting a losing battle. Even programs written in C can be reverse engineered, after all. If you're afraid someone will steal from you, make them sign a contract and sue them if there's trouble.
But if you mean "the customer should not care about python files, and not be able to casually access them", you can use a solution like cx_Freeze to turn your Python application into an executable.
Build a web application in python. Then the world can use it via a browser with zero install.
I recently started learning Python. Not yet ventured into coding.
During one of my learning sessions, i came accross the term Jython.
I googled it & got some information.
I would like to know if anyone has implemented any real-world program using Jython.
Most of the time, Jython isn't used directly to write full read-world programs, but a lot of programs actually embed Jython to use it as a scripting language.
The official Jython website gives a list of projects, some written in Jython, others using Jython for scripting:
http://wiki.python.org/jython/JythonUsers
I am writing a full application in Jython at the moment, and would highly recommend it. Having all of the Java libraries at your disposal is very handy, and the Python syntax and language features actually make using some of them easier than it is in Java (I'm mostly talking about Swing here).
Check out the chapter on GUI Applications from the Jython book. It does a lot of comparisons like 'Look at all this Java code, and now look at it reduced to Python code of half the length!'.
The only caveats I've found are:
Jython development tends to run slightly behind Python, which can be annoying if you find a cool way of doing something in Python, only to discover it's not supported in the current Jython version.
Occasionally you might have hiccups with the interface between Python and Java (I have a couple of unsolved problems here and here, although there are always workarounds for this kind of thing).
Distribution is not as simple as it could be, although once you figure out how to do it, it's fairly painless. I recommend following the method here. It essentially consists of:
Exploding jython.jar and adding your own modules into it.
Writing and compiling a small Java class that creates a Python interpreter and loads up your Python modules.
Creating an executable .jar file consisting of the jython.jar modules, your own Python modules, and the Java class.
Jython really shines for dependency injection.
You know those pesky variables you have to give your program, like
file system paths
server names
ports
Jython provides a really nice way of injecting those variables by putting them in a script. It works equally well for injecting java dependencies, as well.
WebSphere and WebLogic use it as their default scripting engine for administrative purposes.
A lot of other Oracle products ship it as part of their "oracle_commons" module (Oracle Universal Installer, Oracle HTTP Server etc). It's mostly version 2.2 being deployed though, which is a bit old and clunky.
There is a list of application that uses jython at http://wiki.python.org/jython/JythonUsers
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I'm looking to set up my development environment at home for writing Windows applications in Python.
For my first piece, I'm writing a simple, forms-based application that stores data input as XML (and can read that information back.) I do want to set up the tools I'd use professionally, though, having already done a round of didactic programming.
What tools are professional python developers using these days? In order to have a working python environment, what version of the compiler should I be using? What editor is common for professionals? What libraries are considered a must-have for every serious python developer?
Specifically, which Windowing and XML libraries are de rigeur for working in Windows?
I like Eclipse + PyDev (with extensions).
It is available on Windows, and it works very well well. However, there are many other IDEs, with strengths and weakness.
As for the interpreter (Python is interpreted, not compiled!), you have three main choices: CPython, IronPython and Jython.
When people say "Python" they usually refer to "CPython" that is the reference implementation, but the other two (based, respectively, on .Net and Java) are full pythons as well :-)
In your case, I would maybe go on IronPython, because it will allow you to leverage your knowledge of .Net to build the GUI and treating the XML, while leaving the implementation of business logic to Python.
Finally, should you decide to use CPython, finally, there are several choices for working with xml:
minidom; included in the standard library
lxml, faster and with a better API; it means an additional installation on top of Python.
Lots of questions, most hard to answer correctly. First of all, most of python development happens on unix-like platforms. You will hit many walls during development on Windows box.
Python is not a compiled lanugage, current preferred version for production is 2.5. For environement setup you should take a look at virtualenv. Editor is a personal choice, many Python developers use Vim, you can customize it pretty well to suite your needs.
About libraries, Python is very strong around this area and it's really hard to say what is a must to know. If you want to handle XML, I would preffer lxml.
If you go for CPython, make sure you get the win32 extensions by Mark Hammond, either as a separate download which you install on top of the vanilla Python installation, or as part of ActiveState's ActivePython. It includes an integrated editor and debugger.
Jython has recently reached 2.5 compliancy, but we quickly ran into recursion limit issues.
The standard distribution includes IDLE, a graphical editor and debugger.
I like shells, so I'm using IPython for interactive work, and pydb as debugger (unfortunately, I had problems getting pydb to work under Windows).
"What tools are professional python developers using these days?"
Lots
"In order to have a working python environment, what version of the compiler should I be using?"
["compiler" is meaningless. I'll assume you mean "Python"]
We use 2.5.4. We'll be upgrading to 2.6 as soon as we've done the testing.
"What editor is common for professionals?"
We use Komodo Edit.
"What libraries are considered a must-have for every serious python developer?"
We use Django, XLRD, PIL, and a few others. We don't plan this kind of thing in advance. As our requirements arrive, we start looking for libraries. We don't "pre-load" a bunch of "must-have" libraries. The very idea is silly. We load what we need to solve the problems we have.
There are no set standards in these matters, and for good reasons:
there is a fair amount of good choice
different people are productive with different tools
different tools and libraries are suited for solving different problems
That said, I think it's a valid question exactly because there is a fair amount of good choice. When there is too much choice people often do not chose at all and move on. You still need to do your own research to decide what is best for you but you may find here some good starting points.
Here is what I use professionally on windows:
python 2.5.4
latest wxPython
XRC Resource Editor from the wxPython docs & demos for the grunt of the tedious GUI design
lxml or gnosis utils for xml
WingIDE Professional
Taking the headline question literally, the answer has to be IronPython. The 2.0 releases are equivalent to CPython 2.5, and the 2.6 release (currently at beta2) is intended to match CPython 2.6 (full 2.6 release some time in the next couple of months). With either you can use the state of the art in Windows GUI frameworks, i.e. WPF; and you get the whole .net XML support libraries (excepting Linq to XML, which relies on clever bits of C# that IronPython cannot yet emulate).
I've used NetBeans Python plug-in happily as an IDE for IronPython using WPF.
The answer would depend on what you want to do with Python. If you want to do web programming, Python is blessed with many web frameworks. The most popular ones are: Django, Pylons, and Turbogears. There's also Google App Engine, where you can deploy your Python webapp (based on GAE framework) to Google's infrastructure. If you want to do Desktop programming then there is PyQT and TkInter, or you can even try using Java Swing with Jython. And if you want to do Mobile app programming then there is Python for S60 which is backed by Nokia.
Python is interpreted language, so there is no compiler (although the interpreter also compiles your python module into bytecode). I would recommend using Python 2.6 as it has some syntax and libraries that is different compared to 2.5. You can also start learning Python 3.0 too.
There is several IDE that is good for Python. You don't have to get yourself attached into one editor/IDE because most of them are good ones. For the commercial ones there is WingIDE which is really focus on making IDE for Python and I would really recommend IntelliJ IDEA with Python plugin which is really nice if you often look at the libraries in your Python environment. For the free ones (as others have said) there is Komodo Edit or you can also try Netbeans with Python plugin.
As for the must-have libraries, this is depending on what you want to do. What kind of application you want to develop with Python. But I think every Python developer should consider PIL for imaging library. I also use simplejson quite often, because I prefer using JSON rather than XML. If you are using XML though, you can use lxml as it is really fast in parsing XML.