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In the earlier posts on dynamic operations I talked about dynamic binders and rules. Then, rule was two things combined - test and target, both represented as expression trees. Test would determine whether arguments of the dynamic operations 'fit the Read More...
It's been over a week since we released IronPython 2.0 Beta 1 which also contains the Beta 1 version of DLR. The release includes several favorites of mine in the area of expression trees and compilation, mostly invisible to users of IronPython, but of Read More...
Interesting question came to me ... where can one get (latest) sources of DLR? Basically, right now there are two sources you can get DLR from: RubyForge CodePlex RubyForge RubyForge is where the whole IronRuby project lives and as the development progresses, Read More...
I am still working on answering the 2nd question. In the previous post and the one before that I answered most of it, but there is one more thing to address: Problem Two What if the language syntax doesn't provide good guidance for the placement of the Read More...
In the previous post we explored options to express dynamic behavior of "formatting" an object for output. First option was to use relatively well fitting dynamic operation from the DLR core set - CodeRepresentation. There's another option which we'll Read More...
Getting now to the second question that Ales asked: " ... As an example let's take Print function .. where I want to print different data types - integers, strings, decimals etc and each type should be printed differently. Instead of doing the same Read More...
Yesterday a question from one of the readers prompted me to talk a bit more about the DLR trees, a means DLR uses to represent programs. We focused on just couple of nodes, and today won't be much different, except I'll bring a friend in ... LINQ Expression Read More...
After a month break (a month which I spent deep in the guts of the DLR compiler so I wasn't really slacking off) I am back and notice several questions, and since they are good ones (Diky moc, Alesi!), let me address those questions here. First question Read More...
In the last installment we discussed how language can express dynamic behavior using ActionExpression and how DLR treats such cases. In short summary, DLR will turn the ActionExpression into sophisticated cache which keeps updating itself as new runtime Read More...
In the last post we experimented with expressing a dynamic behavior (addition) using a helper function and came to conclusion that such implementation is definitely feasible (after all, IronPython 1.x uses just that), but it has its drawbacks. Today we'll Read More...
How does the programming language express dynamic behaviors in the DLR? So far most of the trees we saw were statically and strongly typed. For example, by constructing tree such as: Ast .Add(     Ast .Constant(1),     Ast Read More...
So far we looked at simple expressions and statements. This time we'll talk about constructs for describing functions / lambdas. ToyScript language supports simple functions. Consider rather trivial ToyScript code: def f(a) { var x = "Hello" print x print Read More...
The ToyScript sample language's front-end is very similar to that of any traditional compiler. It has tokenizer, parser and an abstract syntax tree representation of the toy language. What makes it a DLR based language (from the compiler pipeline perspective) Read More...
Starting with Alhpa 6 release of the Dynamic Language Runtime and IronPython , the distribution includes a small sample language ToyScript. As the name suggests, rather than a serious 'real' language, it is a toy complex barely enough to deserve the label Read More...
The story of the Dynamic Language Runtime starts in early 2004. Jim Hugunin then decided to spend few weeks to explore dynamic languages in the context of Microsoft's .NET platform by implementing IronPython . It is a wonderful story and you can actually Read More...
 
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