[pypy-dev] Custom types for annotating a flow object space

[Henry Gomersall]

I'm looking at using PyPy's flow object space for an experimental 
converter for MyHDL (http://www.myhdl.org/), a Python library for 
representing HDL (i.e. hardware) models. By conversion, I mean 
converting the MyHDL model that represents the hardware into either 
Verilog or VHDL that downstream tools will support. Currently, there is 
a converter that works very well in many situations, but there are 
substantial limitations on the code that can be converted (much greater 
restrictions than RPython imposes), as well as somewhat frustrating 
corner cases.

It strikes me that much of the heavy lifting of the conversion problem 
can be handled by the PyPy stack.

My question then regards the following. MyHDL represents certain low 
level structures as python objects. For example, there is a notion of a 
signal, represented by a Signal object, that has a one to one mapping to 
the target HDL language. All the attributes of the Signal object 
describe how it should be converted. So, during annotation, the Signal 
object should be maintained as a base type, rather than burying deeper 
into the object to try and infer more about its type (which invariably 
breaks things due to RPython non-conformity). There are probably a few 
other types (though not many) that should be handled similarly.

How does one instruct the translator to do this? Is it a case of writing 
a custom TranslationDriver to handle the custom types?

Thanks for any help,

Henry