PyPy - Automatic Generation of VMs for Dynamic Languages

Google Tech Talks November, 14 2007 In Search of Speed and Flexibility. PyPy and the Art of Generating Virtual Machines We all want our favorite dynamic language to be faster, to be even more dynamic and to pick up nifty ideas from its peers. But this is so much work! There ought to be a better way to implement dynamic languages that enables growth and necessary change with less effort and more ease. Writing yet another interpreter in C or even Java is not it. PyPy is a framework to implement dynamic languages that embraces this challenge. It allows us to write such languages in the form of simple interpreters, expressed in a rich subset of Python. This means that the resulting implementations can can be evolved with reasonable effort. PyPy then generates a variety of virtual machines (VMs) from a single source. We can therefore target a wide range of environments, including C/Posix, Java, or .NET. This avoids the major source of fragmentation within a dynamic language community -- the need for a separate language implementation for each virtual machine. It also means that languages as distinct as Python, Prolog and Smalltalk can share the bulk of our compiler machinery. The flexible toolchain which is necessary for virtual machine generation turns out to be good for other things as well. Traditional implementations for dynamic languages have to make some very hard decisions early, which then become entrenched in the whole codebase, making it difficult or impossible to change later. It can be nice to experiment with different garbage collectors, but not if you have to write a complete new implementation of your favourite language for each one. With PyPy you don't have to. You can also generate and tailor a JIT-compiler for the language at hand, putting to rest the notion that flexibility must come at the expense of speed. Speaker: Samuele Pedroni Speaker: Armin Rigo Speaker: Jacob Hallén Speaker: Laura Creighton