IronPython 0.6 has been released as open source timed to coincide with OSCON, and the author, Jim Hugunin, is going to work for Microsoft to work on the CLR.
It was a little less than a year ago that I first started investigating the Common Language Runtime (CLR). My plan was to do a little work and then write a short pithy article called, "Why .NET is a terrible platform for dynamic languages". My plans changed when I found the CLR to be an excellent target for the highly dynamic Python language. Since then I've spent much of my spare time working on the development of IronPython.
The more time that I spent with the CLR, the more excited I became about its potential. At the same time, I was becoming more frustrated with the slow pace of progress that I was able to make working on this project in my spare time. After exploring many alternatives, I think that I've found the ideal way to continue working to realize the amazing potential of the vision of the CLR. I've decided to join the CLR team at Microsoft beginning on August 2.
At Microsoft I plan to continue the work that I've begun with IronPython to bring the power and simplicity of dynamic/scripting languages to the CLR. My work with Python should continue as a working example of a high-performance production quality implementation of a dynamic language for the CLR. I will also reach out to other languages to help overcome any hurdles that are preventing them from targeting the CLR effectively.
Ed Dumbill has comments. It turns out he was able to take the source code for IronPython (which is written in C#) and run it directly on Mono with no changes. That's excellent!
John Udell has more:
"When you think about it," Hugunin said, "why would the CLR be worse for dynamic languages than the JVM, given that Microsoft had the second mover advantage?" And in fact, while he had to do plenty of extra work to support dynamic features that the CLR doesn't natively offer, he notes that the massive engineering resources invested in the CLR make it highly optimized along a number of axes. So, for example, the CLR's function call overhead is apparently less than the native-code CPython's function call overhead, and this is one of the reasons why IronPython benchmarks well against CPython.
All of this is great news. Discussion at Lambda.
Thursday, July 29, 2004
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