Martin Maly

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...