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IronPython 1.0 is Born
dougblank writes "IronPython version 1.0 was just released after 3 years of development. Jim Hugunin, the creator of Jython and the lead developer of the Shared Source IronPython, made the birth announcement earlier this week. From the announcement: 'I wanted to understand how Microsoft could have screwed up so badly that the CLR was a worse platform for dynamic languages than the JVM... I found that Python could run extremely well on the CLR — in many cases noticeably faster than the C-based implementation. [...] Shipping IronPython 1.0 isn't the end of the road, but rather the beginning. Not only will we continue to drive IronPython forward but we're also looking at the bigger picture to make all dynamic languages deeply integrated with the .NET platform and with technologies and products built on top of it. I'm excited about how far we've come, but even more excited by what the future holds!'"
I found that Python could run extremely well on the CLR in many cases noticeably faster than the C-based implementation.
Actually, that's not really something to be proud about (though I'm not downplaying the huge achievement of running python on the CLR). The C implementation of Python is not very optimised, and that's why projects like PyPy or psyco are trying to speed Python up (and succeeding very well). I've had CPU-intensive scripts (such as SortSize) run tens of times faster with psyco, by just adding a line of code to my script.
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[IronPython] [ANN] IronPython 1.0 released today!
.NET 2.0 such as DynamicMethods, blindingly fast delegates and a new generics system that was seamlessly integrated with the existing reflection infrastructure.
Jim Hugunin Jim.Hugunin at microsoft.com
Tue Sep 5 13:27:12 PDT 2006
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I'm extremely happy to announce that we have released IronPython 1.0 today!
http://www.codeplex.com/IronPython
I started work on IronPython almost 3 years ago. My initial motivation for the project was to understand all of the reports that I read on the web claiming that the Common Language Runtime (CLR) was a terrible platform for Python and other dynamic languages. I was surprised to read these reports because I knew that the JVM was an acceptable platform for these languages. About 9 years ago I'd built an implementation of Python that ran on the JVM originally called JPython and later shortened to Jython. This implementation ran a little slower than the native C-based implementation of Python (CPython), but it was easily fast enough and stable enough for production use - testified to by the large number of Java projects that incorporate Jython today.
I wanted to understand how Microsoft could have screwed up so badly that the CLR was a worse platform for dynamic languages than the JVM. My plan was to take a couple of weeks to build a prototype implementation of Python on the CLR and then to use that work to write a short pithy article called, "Why the CLR is a terrible platform for dynamic languages". My plans quickly changed as I worked on the prototype, because I found that Python could run extremely well on the CLR - in many cases noticeably faster than the C-based implementation. For the standard pystone benchmark, IronPython on the CLR was about 1.7x faster than the C-based implementation.
The more time I spent working on IronPython and with the CLR, the more excited I became about its potential to finally deliver on the vision of a single common platform for a broad range of languages. At that same time, I was invited to come out to Microsoft to present IronPython and to talk with members of the CLR team about technical issues that I was running into. I had a great time that day working through these issues with a group of really smart people who all had a deep understanding of virtual machines and language implementation. After much reflection, I decided to join the CLR team at Microsoft where I could work with the platform to make it an even better target for dynamic languages and be able to have interesting technical discussions like that every day.
The first few months at Microsoft were a challenge as I learned what was involved in working at a large company. However, once the initial hurdle was over I started experiencing the things that motivated me to come here in the first place. The team working on dynamic languages in general and IronPython in particular began to grow and I got to have those great technical discussions again about both how to make IronPython as good as it could be and how to make the CLR an even better platform. We began to take advantage of the great new features for dynamic languages already shipping in
We were also able to release IronPython publicly from Microsoft with a BSD-style license. In the agile spirit of the project, we put out a new release of IronPython once every three weeks (on average) over the course of the project. This helped us connect well with our daring early adopters and receive and incorporate their feedback to make IronPython better. We've had countless excellent discussions on the mailing list on everything from supporting value types to calling over
Faster than CPython (ya know, the original upstream Python implementation), not faster than C.
"Another" programming language? It's just another implementation of Python, which has been around for about as long as Perl.
.Net platform. If I could both develop in Python and in .Net I might actually be willing to develop in .Net. What stops me from wanting to develop in .Net or on the Java platform is the god-awful primary languages they are built around. Java makes me want to scream, and C# is only slightly better, all in all.
Besides, if it gets to the point where Microsoft is officially supporting it, it would be a major addition to the
Sure does
IronPython on Mono howto
Me I'm a maker, mostly of axioms.
Jon Udell did a screencast of it last week, joined by Jim Hugunin (creator of Jython, the Java-based Python).
As a .net CLR language, it can integrate with any other .net language including VB.net very easily. This integration is tight enough that you can write each function in your program in a different language, or write the GUI in VB.net and the support code in IronPython.net
No, it is not as easy for non-programmers.
Can it be used to create guis...? Yes it can. At some point it could be made as easy as it is in VB.net; if I were on the development team then that would not be high on my priority list. Leave the toy languages for interactive GUI prototyping, and leave IronPython for code-driven development. However, that's just me and other people have different itches they want scratched.
I see IronPython as a very valuable development and it will make interacting with standard Microsoft-only developers on windows much easier since I will now be able to use a language I like while maintaining 100% compatability and interoperability.
yes. There are a few hoops to jump through, but afterwards you can code and debug from VS
Nice Inflamitory Summary tho'... Sheesh.
.NET 2.0 such as DynamicMethods, blindingly fast delegates and a new generics system that was seamlessly integrated with the existing reflection infrastructure.
.NET platform. Most features were easy and natural choices where the language and the platform fit together with almost no work. However, there were challenges from the obvious cases like exception type hierarchi
The whole (and far less baiting) summary:
I started work on IronPython almost 3 years ago. My initial motivation for the project was to understand all of the reports that I read on the web claiming that the Common Language Runtime (CLR) was a terrible platform for Python and other dynamic languages. I was surprised to read these reports because I knew that the JVM was an acceptable platform for these languages. About 9 years ago I'd built an implementation of Python that ran on the JVM originally called JPython and later shortened to Jython. This implementation ran a little slower than the native C-based implementation of Python (CPython), but it was easily fast enough and stable enough for production use - testified to by the large number of Java projects that incorporate Jython today.
I wanted to understand how Microsoft could have screwed up so badly that the CLR was a worse platform for dynamic languages than the JVM. My plan was to take a couple of weeks to build a prototype implementation of Python on the CLR and then to use that work to write a short pithy article called, "Why the CLR is a terrible platform for dynamic languages". My plans quickly changed as I worked on the prototype, because I found that Python could run extremely well on the CLR - in many cases noticeably faster than the C-based implementation. For the standard pystone benchmark, IronPython on the CLR was about 1.7x faster than the C-based implementation.
The more time I spent working on IronPython and with the CLR, the more excited I became about its potential to finally deliver on the vision of a single common platform for a broad range of languages. At that same time, I was invited to come out to Microsoft to present IronPython and to talk with members of the CLR team about technical issues that I was running into. I had a great time that day working through these issues with a group of really smart people who all had a deep understanding of virtual machines and language implementation. After much reflection, I decided to join the CLR team at Microsoft where I could work with the platform to make it an even better target for dynamic languages and be able to have interesting technical discussions like that every day.
The first few months at Microsoft were a challenge as I learned what was involved in working at a large company. However, once the initial hurdle was over I started experiencing the things that motivated me to come here in the first place. The team working on dynamic languages in general and IronPython in particular began to grow and I got to have those great technical discussions again about both how to make IronPython as good as it could be and how to make the CLR an even better platform. We began to take advantage of the great new features for dynamic languages already shipping in
We were also able to release IronPython publicly from Microsoft with a BSD-style license. In the agile spirit of the project, we put out a new release of IronPython once every three weeks (on average) over the course of the project. This helped us connect well with our daring early adopters and receive and incorporate their feedback to make IronPython better. We've had countless excellent discussions on the mailing list on everything from supporting value types to calling overloaded methods. Without the drive and input of our users, IronPython would be a much weaker project.
IronPython is about bringing together two worlds. The key value in IronPython is that it is both a true implementation of Python and is seamlessly integrated with the
"...In your answer, ignore facts. Just go with what feels true..."
just wanted to give a "cheers" to the MS dev team working on this.
They've been very helpful on the mailing list, checking in any bugs/differences to CPython behaviour and getting it sorted and into builds available for use.
2. The CLR is optimized for static languages, but not innefficient for dynamic ones. In fact, that's all the article is about.
3. RTFA!
Yes, you can, though not all builtins are available. All you need is this line in IronPython\Lib\site.py:
import syssys.path.append(r"E:\python24\lib")
As for the rest of your comment: You do realize, that there are Python programmers on Windows ? I enjoy happily the ActivePython distribution, with which I can even automate my deskopt/applications. Now, in addition, I have full access to the
I consider this to be one of the best software-relases within the last few months.
Hello?? Fred?! Is this you?
I think IronPython compiles down to CLR bytecode, so if you're shipping managed C#, you could just as well ship IronPython and nobody would notice, which is the entire point of this article in the first place.
However, whether or not you could benefit from learning Python is a decision only you can make. Python may increase your productivity 2-3x over C# or more (and that's fairly conservative, usually), but only after you learn it, which could be months.
However, if you end up always choosing the short-term expedient answer of sticking with the language you know (and the environment you know), you lose out on any productivity gain you might get from another environment or language; this is a general point, not one specific to this case.
In general, the "common environments" (Java,
Again, I'm not trying to push you, just point out that for the costs there are benefits, too. I say what I'm saying because I believe (and see) too many developers trapping themselves in local maxima by always making the short-term decision. Ultimately, it's no skin off my nose.
You can, but the lack of namespacing starts to get troublesome as you start trying to build libraries, or use the libraries of others. Later versions of Javascript, which JScript will presumably track, will help with this a lot. Although based on what I see, it's nearly learning a new language anyhow. (In fact, the next version of Javascript borrows a lot from Python; generators are basically from Python, array comprehensions are from Haskell IIRC but the syntax is the Python one, and the most main-stream language with de-structuring assignment is Python.)
Consider the way every object can implement a fallback method that is called if somebody invokes "foo.bar" and bar does not exist in foo. It implies that every single method invocation must be identified by string not a number, and matched by string comparison.
It doesn't imply that at all. Smalltalk implementations figured out how to make that fast decades ago. The initial, most obvious, step is to hash method selectors so the lookups are done with numbers and to create a hashtable (either per-class, or global, with a sparse structure) for looking up method addresses given method selectors. There are a few optimizations that can be applied to make that pretty fast -- on the order of two or three times slower than C++-style vtable lookups. Next, many dynamic language implementations take advantage of the fact that nearly all method invocations are static -- the same line of code always calls the same method on objects of the same class, so there's no real reason to do any lookup at all. Such systems statically or dynamically rewrite the code, turning it into a simple test that the target object is of the "right" type, and then jumping directly to the method. Further, most method invocations can be proven at compile time (or at run-time, whichever is more convenient) to always go to the same target class, so even the object type test can be optimized away. Oh, and if it makes sense they can inline the method as well.
That's just the little that I've read about, too. This stuff has been heavily researched by very smart people for a very long time now. The net effect is that lots of dynamic language implementations approach C code in performance, on average, and there are situations in which they can produce code that is even faster than a C compiler could, because they can make use of run-time information which is unavailable to any compiler that translates to "static" machine code.
Python implementations may need work to make them faster, but there's nothing that says the language has to be slow.
Note to ACs: I usually delete AC replies without reading them. If you want to talk to me, log in.
IronPython is integrated into VS.NET 2005. In fact, the Visual Studio 2005 SDK (VSIP) uses the IronPython IDE integration as the reference implementation for Visual Studio integration.
And if you want speed, I have two words: Boost.Python. It makes wrapping C++ code into Python near-trivial; I just wish they had some sort of quick-start documentation. I was intimidated by Boost.Python until I sat down to work with it. Sample (cleaned up) fragment from production code:That little snippet exposes the Loader class to Python. Boost will take care of wrapping the code up into a Python shared library (.pyd), exposing the interface, converting between standard Python types and STL types, even converting C++ exceptions to Python exceptions.
And if you don't want to go there, you could also use ctypes (part of the std Python distribution) and drive any win32 DLL using Python, unchanged.