Learning Python - Mark Lutz [34]
By implementation, IronPython is very much like Jython (and, in fact, was developed by the same creator)—it replaces the last two bubbles in Figure 2-2 with equivalents for execution in the .NET environment. Also, like Jython, IronPython has a special focus—it is primarily of interest to developers integrating Python with .NET components. Because it is being developed by Microsoft, though, IronPython might also be able to leverage some important optimization tools for better performance. IronPython’s scope is still evolving as I write this; for more details, consult the Python online resources or search the Web.[4]
Execution Optimization Tools
CPython, Jython, and IronPython all implement the Python language in similar ways: by compiling source code to byte code and executing the byte code on an appropriate virtual machine. Still other systems, including the Psyco just-in-time compiler and the Shedskin C++ translator, instead attempt to optimize the basic execution model. These systems are not required knowledge at this point in your Python career, but a quick look at their place in the execution model might help demystify the model in general.
The Psyco just-in-time compiler
The Psyco system is not another Python implementation, but rather a component that extends the byte code execution model to make programs run faster. In terms of Figure 2-2, Psyco is an enhancement to the PVM that collects and uses type information while the program runs to translate portions of the program’s byte code all the way down to real binary machine code for faster execution. Psyco accomplishes this translation without requiring changes to the code or a separate compilation step during development.
Roughly, while your program runs, Psyco collects information about the kinds of objects being passed around; that information can be used to generate highly efficient machine code tailored for those object types. Once generated, the machine code then replaces the corresponding part of the original byte code to speed your program’s overall execution. The net effect is that, with Psyco, your program becomes much quicker over time and as it is running. In ideal cases, some Python code may become as fast as compiled C code under Psyco.
Because this translation from byte code happens at program runtime, Psyco is generally known as a just-in-time (JIT) compiler. Psyco is actually a bit different from the JIT compilers some readers may have seen for the Java language, though. Really, Psyco is a specializing JIT compiler—it generates machine code tailored to the data types that your program actually uses. For example, if a part of your program uses different data types at different times, Psyco may generate a different version of machine code to support each different type combination.
Psyco has been shown to speed Python code dramatically. According to its web page, Psyco provides “2x to 100x speed-ups, typically 4x, with an unmodified Python interpreter and unmodified source code, just a dynamically loadable C extension module.” Of equal significance, the largest speedups are realized for algorithmic code written in pure Python—exactly the sort of code you might normally migrate to C to optimize. With Psyco, such migrations become even less important.
Psyco is not yet a standard part of Python; you will have to fetch and install it separately. It is also still something of a research project, so you’ll have to track its evolution online. In fact, at this writing, although Psyco can still be fetched and installed by itself,