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CHAPTER 17 ■ EXTENDING PYTHON 369 Once you’ve got your function in place, there is still some extra wrapping needed to make your C code act as a module. But let’s get back to that once we’ve got a real example to work with, shall we? Palindromes, Detartrated 1 for Your Pleasure Without further ado, I give you the hand-coded Python C API version of the palindrome module (with some interesting new stuff added) in Listing 17-6. Listing 17-6. Palindrome Checking Again (palindrome2.c) #include static PyObject *is_palindrome(PyObject *self, PyObject *args) { int i, n; const char *text; int result; /* "s" means a single string: */ if (!PyArg_ParseTuple(args, "s", &text)) { return NULL; } /* The old code, more or less: */ n=strlen(text); result = 1; for (i=0; i
370 CHAPTER 17 ■ EXTENDING PYTHON /* An initialization function for the module (the name is significant): */ PyMODINIT_FUNC initpalindrome() { Py_InitModule("palindrome", PalindromeMethods); } Most of the added stuff in Listing 17-6 is total boilerplate. Where you see palindrome, you could insert the name of your module, while where you see is_palindrome, insert the name of your function. If you have more functions, simply list them all in the PyMethodDef array. One thing is worth noting, though: The name of the initialization function must be initmodule, where module is the name of your module; otherwise, Python won’t find it. So, let’s compile! You do this just like in the section on SWIG, except that there is only one file to deal with now. Here is an example using gcc (remember to add -fPIC in Solaris): gcc -I$PYTHON_HOME -I$PYTHON_HOME/Include -shared palindrome2.c -o palindrome.so Again, you should have a file called palindrome.so, ready for your use. Put it somewhere in your PYTHONPATH (such as the current directory) and away we go: >>> from palindrome import is_palindrome >>> is_palindrome('foobar') 0 >>> is_palindrome('deified') 1 And that’s it. Now go play. (But be careful; remember the Waldi Ravens quote from the Introduction.) A Quick Summary Extending Python is a huge subject. The tiny glimpse provided by this chapter included the following: Extension philosophy. Python extensions are useful mainly for two things: for using existing (legacy) code, or for speeding up bottlenecks. If you’re writing your own code from scratch, try to prototype it in Python, find the bottlenecks, and factor them out as extensions if needed. Encapsulating potential bottlenecks beforehand can be useful. Jython and IronPython. Extending these implementations of Python is quite easy: You simply implement your extension as a library in the underlying implementation (Java for Jython and C# or some other .NET language for IronPython) and immediately the code is usable in your Python. Extension approaches. There are plenty of tools for extending or speeding up your code: for making the incorporation of C code into your Python program easier, for speeding up common operations such as numeric array manipulation, or for speeding up Python itself. Such tools includ SWIG, Psyco, Pyrex, Weave, NumPy, ctypes, subprocess, and modulator.
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Beginning Python From Novice to Pro
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About the Technical Reviewer ■JER
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Introduction A C program is like a
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256 CHAPTER 11 ■ FILES AND STUFF
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Index ■Symbols - operator 558 !=
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