I am planning to use Jython with Django. I want to know how stable the Jython project is, how easy to use it is, and how large its developer community is.
Django is proven to work with Jython:
Special focus in Jython 2.5 was to make it compatible with modern web frameworks like Django
There is also a special project, django-jython, that focuses on making database backends and extensions available for Jython development.
There is explicit documentation on how to run Django on Jython
In theory, Jython is 100% compatible with CPython. In practice, some extensions or libraries may have badly written code that make them dependent on a specific Python implementation such as CPython. The django-jython project explicitly provides a tested solution to overcome this problem. Of course you can still run across some libraries that explicitly require CPython (hence mostly safe).
I have not used Django with Jython, so I can't speak to that specific issue, but I've used Jython for other things and I've found it quite stable of late, and just as easy as plain Python. I believe the "core committers" in Jython are substantially fewer than in C-Python (maybe 1/3 the number or less), if that's what you mean by "developer community", but I'm not quite sure what's the point in asking about this -- are you considering joining either developer community (Jython or Core Python) and wondering where you could have the best impact?
If that's the case, I think the key issue isn't really how many others are already helping out, but, "what do you bring to the party" -- if you're a JVM wizard, or an expert at any important Java framework, you could be a real boon to the Jython community while that same skill would help much less in the C-Python community; vice versa, if you're a wizard, say, with autoconfigure and C-coded system calls, that would be precious for the C-Python community, but not as useful for the Jython community.
I use Jython in testing and rapid-development.
From my point of view it is stable.
Related
I am currently looking for a possible way to integrate my C++/C# application with some of my Python scripts. At this point, IronPython seems like the way to go.
However, before proceeding, I would like to ask the following:
How stable is IronPython right now? Is it ready for production use? Are there any known major quirks/bugs?
What is the future of IronPython? Will it be maintained for bug fixes? Will there be new versions?
I am particularly interested in using IronPython to run a Python web framework such as Django or Web2py. I am very well aware that current Python web frameworks don't play very well with it. Therefore any insights on the future of IronPython's web framework support would be much appreciated as well.
To answer your second question, yes, IronPython will be developed in the future. Right now, there is a "language change moratorium" on CPython, the main branch of Python (see PEP 3003. The Python folks want CPython, Jython, and other branches of Python development to catch up with CPython, and they've been doing just that. If all goes as planned, by the time the moratorium is over, IronPython and others will be up to speed and will have implementations that follow the syntax and features of Python 3.x. Also, since IronPython is backed by Microsoft and is a key part of their Dynamic Language Runtime (whatever that is), it's unlikely to get cancelled.
Right now, IronPython is making good progress. According to their svn, code is being changed fairly regularly (1 check-in every other day or so). A Python 2.7 compatible implementation is in the works, and the alpha was released July 16 (so IronPython 2.7 can be expected in the near future).
As for the stability of the interpreter, it seems rather stable. I haven't used IronPython extensively, but the 2.6.1 release behaves almost exactly like the CPython 2.6 interpreter, disregarding standard library.
A lot of the extensions for CPython don't work with IronPython. So, if you want to use Django or something like that, it's probably not smart to use IronPython because it isn't really cross-platform, doesn't work with some frameworks, and it performs worse than CPython. The real advantage to IronPython is access to everything that .NET has to offer, including ASP.NET (a web framework) and Silverlight.
If you want to use .NET, IronPython is the best route as far as scripting goes.
I'm starting to study Python, and for now I like it very much. But, if you could just answer a few questions for me, which have been troubling me, and I can't find any definite answers to them:
What is the relationship between Python's C implementation (main version from python.org) and IronPython, in terms of language compatibility ? Is it the same language, and do I by learning one, will be able to smoothly cross to another, or is it Java to JavaScript ?
What is the current status to IronPython's libraries ? How much does it lags behind CPython libraries ? I'm mostly interested in numpy/scipy and f2py. Are they available to IronPython ?
What would be the best way to access VB from Python and the other way back (connecting some python libraries to Excel's VBA, to be exact) ?
1) IronPython and CPython share nearly identical language syntax. There is very little difference between them. Transitioning should be trivial.
2) The libraries in IronPython are very different than CPython. The Python libraries are a fair bit behind - quite a few of the CPython-accessible libraries will not work (currently) under IronPython. However, IronPython has clean, direct access to the entire .NET Framework, which means that it has one of the most extensive libraries natively accessible to it, so in many ways, it's far ahead of CPython. Some of the numpy/scipy libraries do not work in IronPython, but due to the .NET implementation, some of the functionality is not necessary, since the perf. characteristics are different.
3) Accessing Excel VBA is going to be easier using IronPython, if you're doing it from VBA. If you're trying to automate excel, IronPython is still easier, since you have access to the Execl Primary Interop Assemblies, and can directly automate it using the same libraries as C# and VB.NET.
What is the relationship between
Python's C implementation (main
version from python.org) and
IronPython, in terms of language
compatibility ? Is it the same
language, and do I by learning one,
will be able to smoothly cross to
another, or is it Java to JavaScript ?
Same language (at 2.5 level for now -- IronPython's not 2.6 yet AFAIK).
What is the current status to
IronPython's libraries ? How much does
it lags behind CPython libraries ? I'm
mostly interested in numpy/scipy and
f2py. Are they available to IronPython
?
Standard libraries are in a great state in today's IronPython, huge third-party extensions like the ones you mention far from it. numpy's starting to get feasible thanks to ironclad, but not production-level as numpy is from IronPython (as witnessed by the 0.5 version number for ironclad, &c). scipy is huge and sprawling and chock full of C-coded and Fortran-coded extensions: I have no first-hand experience but I suspect less than half will even run, much less run flawlessly, under any implementation except CPython.
What would be the best way to access
VB from Python and the other way back
(connecting some python libraries to
Excel's VBA, to be exact) ?
IronPython should make it easier via .NET approaches, but CPython is not that far via COM implementation in win32all.
Last but not least, by all means check out the book IronPython in Action -- as I say every time I recommend it, I'm biased (by having been a tech reviewer for it AND by friendship with one author) but I think it's objectively the best intro to Python for .NET developers AND at the same time the best intro to .NET for Pythonistas.
If you need all of scipy (WOW, but that's some "Renaissance Man" computational scientist!-), CPython is really the only real option today. I'm sure other large extensions (PyQt, say, or Mayavi) are in a similar state. For deep integration to today's Windows, however, I think IronPython may have an edge. For general-purpose uses, CPython may be better (esp. thanks to the many new features in 2.6), unless you're really keen to use many cores to the hilt within a single process, in which case IronPython (which is GIL-less) may prove advantageous again.
One way or another (or even on the JVM via Jython, or in peculiar environments via PyPy) Python is surely an awesome language, whatever implementation(s) you pick for a given application!-) Note that you don't need to stick with ONE implementation (though you should probably pick one VERSION -- 2.5 for maximal compatibility with IronPython, Jython, Google App Engine, etc; 2.6 if you don't care about any deployment options except "CPython on a machine under my own sole or virtual control";-).
IronPython version 2.0.2, the current release, supports Python 2.5 syntax. With the next release, 2.6, which is expected sometime over the next month or so (though I'm not sure the team have set a hard release date; here's the beta), they will support Python 2.6 syntax. So, less Java to JavaScript and more Java to J# :-)
All of the libraries that are themselves written in Python work pretty much perfectly. The ones that are written in C are more problematic; there is an open source project called Ironclad (full disclosure: developed and supported by my company), currently at version 0.8.5, which supports numpy pretty well but doesn't cover all of scipy. I don't think we've tested it with f2py. (The version of Ironclad mentioned below by Alex Martelli is over a year old, please avoid that one!)
Calling regular VB.NET from IronPython is pretty easy -- you can instantiate .NET classes and call methods (static or instance) really easily. Calling existing VBA code might be trickier; there are open source projects called Pyinex and XLW that you might want to take a look at. Alternatively, if you want a spreadsheet you can code in Python, then there's always Resolver One (another one from my company... :-)
1) The language implemented by CPython and IronPython are the same, or at most a version or two apart. This is nothing like the situation with Java and Javascript, which are two completely different languages given similar names by some bone-headed marketing decision.
2) 3rd-party libraries implemented in C (such as numpy) will have to be evaluated carefully. IronPython has a facility to execute C extensions (I forget the name), but there are many pitfalls, so you need to check with each library's maintainer
3) I have no idea.
CPython is implemented by C for corresponding platform, such as Windows, Linux or Unix; IronPython is implemented by C# and Windows .Net Framework, so it can only run on Windows Platform with .Net Framework.
For gramma, both are same. But we cannot say they are one same language. IronPython can use .Net Framework essily when you develop on windows platform.
By far, July 21, 2009 - IronPython 2.0.2, our latest stable release of IronPython, was released. you can refer to http://www.codeplex.com/Wiki/View.aspx?ProjectName=IronPython.
You can access VB with .Net Framework function by IronPython. So, if you want to master IronPython, you'd better learn more .Net Framework.
How does IronPython stack up to the default Windows implementation of Python from python.org? If I am learning Python, will I be learning a subtley different language with IronPython, and what libraries would I be doing without?
Are there, alternatively, any pros to IronPython (not including .NET IL compiled classes) that would make it more attractive an option?
There are a number of important differences:
Interoperability with other .NET languages. You can use other .NET libraries from an IronPython application, or use IronPython from a C# application, for example. This interoperability is increasing, with a movement toward greater support for dynamic types in .NET 4.0. For a lot of detail on this, see these two presentations at PDC 2008.
Better concurrency/multi-core support, due to lack of a GIL. (Note that the GIL doesn't inhibit threading on a single-core machine---it only limits performance on multi-core machines.)
Limited ability to consume Python C extensions. The Ironclad project is making significant strides toward improving this---they've nearly gotten Numpy working!
Less cross-platform support; basically, you've got the CLR and Mono. Mono is impressive, though, and runs on many platforms---and they've got an implementation of Silverlight, called Moonlight.
Reports of improved performance, although I have not looked into this carefully.
Feature lag: since CPython is the reference Python implementation, it has the "latest and greatest" Python features, whereas IronPython necessarily lags behind. Many people do not find this to be a problem.
There are some subtle differences in how you write your code, but the biggest difference is in the libraries you have available.
With IronPython, you have all the .Net libraries available, but at the expense of some of the "normal" python libraries that haven't been ported to the .Net VM I think.
Basically, you should expect the syntax and the idioms to be the same, but a script written for IronPython wont run if you try giving it to the "regular" Python interpreter. The other way around is probably more likely, but there too you will find differences I think.
Well, it's generally faster.
Can't use modules, and only has a subset of the library.
Here's a list of differences.
See the blog post IronPython is a one-way gate. It summarizes some things I've learned about IronPython from asking questions on StackOverflow.
Python is Python, the only difference is that IronPython was designed to run on the CLR (.NET Framework), and as such, can inter-operate and consume .NET assemblies written in other .NET languages. So if your platform is Windows and you also use .NET or your company does then should consider IronPython.
One of the pros of IronPython is that, unlike CPython, IronPython doesn't use the Global Interpreter Lock, thus making threading more effective.
In the standard Python implementation, threads grab the GIL on each object access. This limits parallel execution, which matters especially if you expect to fully utilize multiple CPUs.
Pro: You can run IronPython in a browser if SilverLight is installed.
It also depends on whether you want your code to work on Linux. Dunno if IronPython will work on anything beside windows platforms.
We are ready in our company to move everything to Python instead of C#, we are a consulting company and we usually write small projects in C# we don't do huge projects and our work is more based on complex mathematical models not complex software structures. So we believe IronPython is a good platform for us because it provides standard GUI functionality on windows and access to all of .Net libraries.
I know Ironpython studio is not complete, and in fact I had a hard time adding my references but I was wondering if someone could list some of the pros and cons of this migration for us, considering Python code is easier to read by our clients and we usually deliver a proof-of-concept prototype instead of a full-functional code, our clients usually go ahead and implement the application themselves
My company, Resolver Systems, develops what is probably the biggest application written in IronPython yet. (It's called Resolver One, and it's a Pythonic spreadsheet). We are also hosting the Ironclad project (to run CPython extensions under IronPython) and that is going well (we plan to release a beta of Resolver One & numpy soon).
The reason we chose IronPython was the .NET integration - our clients want 100% integration on Windows and the easiest way to do that right now is .NET.
We design our GUI (without behaviour) in Visual Studio, compile it into a DLL and subclass it from IronPython to add behaviour.
We have found that IronPython is faster at some cases and slower at some others. However, the IronPython team is very responsive, whenever we report a regression they fix it and usually backport it to the bugfix release. If you worry about performance, you can always implement a critical part in C# (we haven't had to do that yet).
If you have experience with C#, then IronPython will be natural for you, and easier than C#, especially for prototypes.
Regarding IronPython studio, we don't use it. Each of us has his editor of choice (TextPad, Emacs, Vim & Wing), and everything works fine.
There are a lot of reasons why you want to switch from C# to python, i did this myself recently. After a lot of investigating, here are the reasons why i stick to CPython:
Performance: There are some articles out there stating that there are always cases where ironpython is slower, so if performance is an issue
Take the original: many people argue that new features etc. are always integrated in CPython first and you have to wait until they are implemented in ironpython.
Licensing: Some people argue this is a timebomb: nobody knows how the licensing of ironpython/mono might change in near future
Extensions: one of the strengths of python are the thousands of extensions which are all usable by CPython, as you mentioned mathematical problems: numpy might be a suitable fast package for you which might not run as expected under IronPython (although Ironclad)
Especially under Windows you have a native GUI-toolkit with wxPython which also looks great under several other platforms and there are pyQT and a lot of other toolkits. They have nice designer like wxGlade, but here VisualStudio C# Designer is easier to use.
Platform independence (if this is an issue): CPython is ported to really a lot of platforms, whereas ironpython can only be used on the major platforms (recently read a developer was sad that he couldn't get mono to run under his AIX)
Ironpython is a great work, and if i had a special .NET library i would have to use, IronPython might be the choice, but for general purpose problems, people seem to suggest using the original CPython, unless Guido changes his mind.
The way you describe things, it sounds like you're company is switching to Python simple for the sake of Python. Is there some specific reason you want to use Python? Is a more dynamic language necessary? Is the functional programming going to help you at all? If you've got a perfectly good working set of tools in C#, why bother switching?
If you're set on switching, you may want to consider starting with standard Python unless you're specifically tied to the .NET libraries. You can write cross platform GUIs using a number of different frameworks like wxPython, pyQt, etc. That said, Visual Studio has a far superior GUI designer to just about any of the tools out there for creating Python windowed layouts.
The background
I'm building a fair-sized web application with a friend in my own time, and we've decided to go with the Django framework on Python. Django provides us with a lot of features we're going to need, so please don't suggest alternative frameworks.
The only decision I'm having trouble with, is whether we use Python or Jython to develop our application. Now I'm pretty familiar with Java and could possibly benefit from the libraries within the JDK. I know minimal Python, but am using this project as an opportunity to learn a new language - so the majority of work will be written in Python.
The attractiveness of Jython is of course the JVM. The number of python/django enabled web-hosts is extremely minimal - whereas I'm assuming I could drop a jython/django application on a huge variety of hosts. This isn't a massive design decision, but still one I think needs to be decided. I'd really prefer jython over python for the jvm accessibility alone.
Questions
Does Jython have many limitations compared to regular python? Will running django on jython cause problems? How quick is the Jython team to release updates alongside Python? Will Django work as advertised on Jython (with very minimal pre-configuration)?
Decision
Thanks for the helpful comments. What I think I'm going to do is develop in Jython for the JVM support - but to try to only use Python code/libraries. Portability isn't a major concern so if I need a library in the JDK (not readily available in python), I'll use it. As long as Django is fully supported, I'm happy.
Django does work on Jython, although you'll need to use the development release of Jython, since technically Jython 2.5 is still in beta. However, Django 1.0 and up should work unmodified.
So as to whether you should use the regular Python implementation or Jython, I'd say it's a matter of whether you prefer having all the Java libraries available or all of the Python libraries. At this point you can expect almost everything in the Python standard library to work with Jython, but there are still plenty of third-party packages which will not work, especially C extension modules. I'd personally recommend going with regular Python, but if you've got a ton of JVM experience and want to stick with what you know, then I can respect that.
As for finding Python hosting, this page might be helpful.
I'd say that if you like Django, you'll also like Python. Don't make the (far too common) mistake of mixing past language's experience while you learn a new one. Only after mastering Python, you'll have the experience to judge if a hybrid language is better than either one.
It's true that very few cheap hostings offer Django preinstalled; but it's quite probable that that will change, given that it's the most similar environment to Google's app engine. (and most GAE projects can be made to run on Django)
I have recently started working on an open source desktop project in my spare time. So this may not apply. I came to the same the question. I decided that I should write as much of the code as possible in python (and Django) and target all the platforms CPython, Jython, and IronPython.
Then, I decided that I would write plugins that would interface with libraries on different implementations (for example, different GUI libraries).
Why? I decided early on that longevity of my code may depend on targeting not only CPython but also virtual machines. For today's purposes CPython is the way to go because of speed, but who knows about tomorrow. If you code is flexible enough, you may not have to decide on targeting one.
The downside to this approach is that you will have more code to create and maintain.
Django is supposed to be jython-compatible sinc version 1.0.
This tutorial is a bit outdated, but from there you can see there are no special issues.