I believe his thesis was actually that most languages are handicapped because they can not easily be called via the usual "load a .so file and call a function" ABI. Java, for instance, would be a more useful language to me if I could easily create Python bindings for useful Java libraries like Lucene, without needing to use something like Jython that runs on the JVM.
The confusion arises when some language developers decide to ignore or break existing ABI for a particular platform.
There are general ways to call procedures - there machine instructions for this. ABI defines how exactly parameters and return values should be passed - using, registers or stack or both.
As long as you follow the rules there is no difficulty in calling everything you wish.
The whole idea of JVM as something disconnected from reality^W OS and hardware is simply wrong, and all the confusion is the consequence of that premature decision.
Of course, slogan "you don't have to know" always wins.
You can run Python 2.5 on lastest Jython, then you have access to JVM libs and the JVM libs to Python libs 2.5 compatible.
Calling JVM from CPython is actually possible:
- with pyjnius from kivy fame built with cython it is still in development, AFAIK it is missing the possibility to call Python code from Java code aka. submitting a Python "callback" to a Java method, I think it is called IoC pattern and Hollywood principle «Don't call me, I call you». jnius is used in Kivy to make it possible to call Android libs. As an example, I created Python bindings of Blueprints with it. Blueprints is an abstraction library for graphdb like Neo4j, OrientDB, Titan, available here https://github.com/Printemps/python-blueprints/. Tutorial: «JavaClass = autoclass('path.to.JavaClass'); JavaClass.JavaMethod(python_object)». Those bindings are merely Pythonification but they are gotchas in types conversions.
- There is also jpype which looks like an established solution used by Neo4J fame to make it possible to embed Neo4J embedded into CPython.
