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CHAPTER 17 ■ EXTENDING PYTHON 361 Pyrex (http://www.cosc.canterbury.ac.nz/~greg/python/Pyrex). A Python “dialect”—sort of. It’s a language specifically designed for writing extension modules for Python. The Pyrex language combines Python (or a subset of it) with optional static typing as in C. Once you’ve written a module in Pyrex, you can translate it into C code using the pyrexc program. The resulting C code has been constructed to conform to the Python C API, so after compiling it (as described in the main text), you should be able to use it in your Python program without problems. Pyrex can certainly take much of the drudgery out of writing C extensions, while still letting you control the details you might care about, such as the exact C data types for some of your variables. Weave (http://www.scipy.org/documentation/weave). Part of the SciPy distribution, but also available separately, Weave is a tool for including C or C++ code directly in your Python code (as strings) and having the code compiled and executed seamlessly. If you have certain mathematical expressions you want to compute quickly, for example, then this might be the way to go. Weave can also speed up expressions using numeric arrays (see the next item). NumPy (http://numeric.scipy.org). At present, there are two main implementations of multidimensional, numeric arrays in Python—numeric and numarray—both using more or less the same interface. It seems that they may be unified as the package scipy.core. However this turns out, numeric arrays are very useful for analyzing many forms of numeric data (from stock values to astronomical images). One advantage is the simple interface, which relieves the need to explicitly specify many low-level operations; the main advantage, however, is speed. Performing many common operations on every element in a numeric array is much, much faster than doing something equivalent with lists and for-loops, because the implicit loops are implemented directly in C. Numeric arrays work well with both Pyrex and Weave. ctypes (http://starship.python.net/crew/theller/ctypes). The ctypes library takes a very direct approach—it simply lets you import preexisting (shared) C libraries. While there are some restrictions, this is, perhaps, one of the simplest ways of accessing C code. No need for wrappers or special APIs; you just import the library and use it. subprocess. Okay, this one’s a bit different. It’s a module that can be found in the standard library, along with the older modules and functions with similar functionality, and it allows you to have Python run external programs, and communicate with them through command-line arguments, and the standard input, output, and error streams. If your speed-critical code can do much of its work in a few long-running batch jobs, little time will be lost starting the program and communicating with it. In that case, simply placing your C code in a completely separate program and running it as a subprocess could well be the cleanest solution of all. modulator. Found in the Tools directory of your Python distribution, this script can be used to generate some of the boilerplate code needed for C extensions. A Swig of . . . SWIG SWIG (http://www.swig.org), short for Simple Wrapper and Interface Generator, is a tool that works with several languages. On the one hand, it lets you write your extension code in C or C++; on the other hand, it automatically wraps these so that you can use them in several highlevel languages such as Python, Perl, Tcl/Tk, Ruby, C#, Common Lisp, Java, Modula-3, OCAML, Scheme, PHP—the list goes on and on (and you can read it at http://www.swig.org/compat.html). This means that if you decide to write some of your system as a C extension, rather than implement it directly in Python, the C extension library can also be made available (using SWIG) to a host of other languages. This can be very useful if you want several subsystems written in
362 CHAPTER 17 ■ EXTENDING PYTHON different languages to work together; your C (or C++) extension can then become a hub for the cooperation. INSTALLING SWIG By now, I guess you ought to be quite savvy about installing things. As before . . . • You can get SWIG from the Web site, http://www.swig.org. • Many UNIX/Linux distributions come with SWIG. Many package managers will let you install it directly. • There is a binary installer for Windows. • Compiling the sources yourself is again simply a matter of calling configure and make install. If you have problems installing SWIG, you should be able to find helpful information on the Web page. What Does It Do? Using SWIG is a simple process, provided that you have some C code: 1. Write an interface file for your code. This is quite similar to C header files (and, for simple cases, you can use your header file directly). 2. Run SWIG on the interface file, in order to automatically produce some more C code (wrapper code). 3. Compile the original C code together with the generated wrapper code in order to generate a shared library. In the following, I discuss each of these steps, starting with a bit of C code . . . I Prefer Pi A palindrome (such as the title of this section) is a sentence that is the same when read backwards, if you ignore spaces and punctuation and the like. Let’s say you want to recognize huge palindromes, without the allowance for whitespace and friends. (Perhaps you need it for analyzing a protein sequence or something.) Of course, the string would have to be really big for this to be a problem for a pure Python program, but let’s say the strings are really big, and that you have to do lots and lots of these checks. You decide to write a piece of C code to deal with it (or perhaps you find some finished code—as mentioned, using existing C code in Python is one of the main uses of SWIG). Listing 17-3 shows a possible implementation. Listing 17-3. A Simple C Function for Detecting a Palindrome (palindrome.c) #include int is_palindrome(char *text) { int i, n=strlen(text);
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Beginning Python From Novice to Pro
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viii ■CONTENTS Strings . . . . .
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256 CHAPTER 11 ■ FILES AND STUFF
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270 CHAPTER 12 ■ GRAPHICAL USER I
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298 CHAPTER 14 ■ NETWORK PROGRAMM
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Index ■Symbols - operator 558 !=
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