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CHAPTER 17 ■ EXTENDING PYTHON 359 Once you have compiled the class (and put the .class file either in your current directory or somewhere in your Java CLASSPATH), you can fire up Jython (with the jython command) and import the class directly: >>> import JythonTest >>> test = JythonTest() >>> test.greeting() Hello, world! See? There’s nothing to it. ■Tip If you’re working with Java, you can also use the command jythonc to compile your Python classes into Java classes, which can then be imported into your Java programs. Listing 17-2 shows a similar class in C#. Compile this with your compiler of choice (free software available from http://www.mono-project.com). Listing 17-2. A Simple C# Class (IronPythonTest.cs) using System; namespace FePyTest { public class IronPythonTest { public void greeting() { Console.WriteLine("Hello, world!"); } } } One way of using this in IronPython would be to compile the class to a DLL (see the documentation for your C# installation for details) and update the relevant environment variables (such as PATH) as needed. Then you should be able to use it as in the following (using the FePyConsole prompt): >>> import sys >>> sys.LoadAssemblyFromFile("IronPythonTest.dll") >>> import FePyTest >>> f = FePyTest.IronPythonTest() >>> f.greeting()
360 CHAPTER 17 ■ EXTENDING PYTHON ■Note While I focus on extending Python here, it is also entirely possible to use Jython in your Java programs, IronPython in your C# programs, and CPython in your C programs (in other words, you can use Python to extend other languages). See the relevant documentation for more information. For more details on these implementations of Python, see the Jython Web page (http:// www.jython.org) and the IronPython Web page (http://www.ironpython.org; see also http:// workspaces.gotdotnet.com/ironpython). Writing C Extensions This is what it’s all about, really. Extending Python normally means extending CPython, the standard version of Python, implemented in the programming language C. ■Tip For a basic introduction and some background material, see the Wikipedia article on C, http:// en.wikipedia.org/wiki/C_programming_language. For more information, check out Ivor Horton’s book Beginning C, Third Edition (Apress, 2004). A really authoritative source of information is the all-time classic by Brian Kernighan and Dennis Ritchie, the inventors of the language: The C Programming Language, Second Edition (Prentice-Hall, 1988). C isn’t quite as dynamic as Java or C#, and it’s not as easy for Python to figure out things for itself if you just supply it with your compiled C code. Therefore, you have to adhere to a relatively strict API when writing C extensions for Python; I discuss this API a bit later. There are several projects that try to make the process of writing C extensions easier, though, and one of the better-known projects is SWIG, which I discuss in the following section. (See the sidebar “Other Approaches” for some . . . well . . . other approaches.) OTHER APPROACHES If you’re using CPython, there are plenty of tools available to help you speed up your programs, either by generating and using C libraries or by actually speeding up your Python code. Here is an overview of some options: Psyco (http://psyco.sf.net). A specialized just-in-time compiler for Python, which can speed up certain kinds of code (especially low-level code dealing with lists of numbers) by an order of magnitude or more. It won’t help in all cases, and does need quite a bit of memory to do its job well. It’s very easy to use— in the simplest case, just import it and call psyco.full(). One of the interesting things about Psyco is that it actually analyzes what goes on while the program is running, so it may, in fact, speed up some Python code beyond what you could achieve by writing a C extension! (Perhaps it’s worth a try, before you dive into the nearest C textbook?)
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Beginning Python From Novice to Pro
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Index ■Symbols - operator 558 !=
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