Catálogo de publicaciones - libros

This reference chapter has described every command, option and public DB:: variable provided by the Perl debugger. You will be able to use any of these tools to control your program’s execution, study its behavior, and inspect or change any data during the runtime of the program. Finally, you learned how to call the debugger in several different cases, depending on the context required.

Finally, you now know how to create shiny, professional–looking software with fancy GUI installers—or how to automate the generation of those precious .tar.gz files. Here is a summary of the specific concepts covered:

. The Distutils toolkit lets you write installer scripts, conventionally called setup.py, which let you install modules, packages, and extensions, and which let you build distributable archives and simple Windows installers.

. You can run your setup.py script with several commands, such as build, build_ext, install, sdist, and bdist.

Installers. There are many installer generators available, and you can use many of them to install your Python programs, making the process easier for your users.

. You can use Distutils to have your C extensions compiled automatically, with Distutils automatically locating your Python installation and figuring out which compiler to use. You can even have it run SWIG automatically.

py2exe. The py2exe extension to Distutils can be used to create executable binaries from your Python programs. Along with a couple of extra files (which can be conveniently installed with an installer), these .exe files can be run without installing a Python interpreter separately.

This reference chapter has described every command, option and public DB:: variable provided by the Perl debugger. You will be able to use any of these tools to control your program’s execution, study its behavior, and inspect or change any data during the runtime of the program. Finally, you learned how to call the debugger in several different cases, depending on the context required.

This reference chapter has described every command, option and public DB:: variable provided by the Perl debugger. You will be able to use any of these tools to control your program’s execution, study its behavior, and inspect or change any data during the runtime of the program. Finally, you learned how to call the debugger in several different cases, depending on the context required.

As always, new topics were covered—and here they are again:

. This is the practice of downloading Web pages automatically, and extracting information from them. The Tidy program and its library version are useful tools for fixing ill–formed HTML before using an HTML parser. Another option is to use Beautiful Soup, which is very forgiving of messy input.

. The Common Gateway Interface is a way of creating dynamic Web pages, by making a Web server run and communicate with your programs and display the results. The cgi and cgitb modules are useful for writing CGI scripts. CGI scripts are usually invoked from HTML forms.

. The mod_python handler framework makes it possible to write Apache handlers in Python. It includes three useful standard handlers: the CGI handler, the PSP handler, and the publisher handler.

. Web services are to programs what (dynamic) Web pages are to people. You may see them as a way of making it possible to do network programming at a higher level of abstraction. Two example Web service standards discussed in this chapter are RSS and XML–RPC.

Here are the main topics covered in the chapter:

. Basically: Test first, code later. Tests let you rewrite your code with confidence, making your development and maintenance more flexible.

. These are indispensible tools if you want to do unit testing in Python. The doctest module is designed to check examples in docstrings, but can easily be used to design test suites. For more flexibility and structure in your suites, the unittest framework is very useful.

. These two tools read source code and point out potential (and actual) problems. They check everything from short variable names to unreachable pieces of code. With a little coding you can make them (or one of them) part of your test suite, to make sure all of your rewrites and refactorings conform to your coding standards.

. If you really care about speed and want to optimize your program (only do this if it’s absolutely necessary), you should profile it first. Use the profile (or hotshot) module to find bottlenecks in your code.

This reference chapter has described every command, option and public DB:: variable provided by the Perl debugger. You will be able to use any of these tools to control your program’s execution, study its behavior, and inspect or change any data during the runtime of the program. Finally, you learned how to call the debugger in several different cases, depending on the context required.

Finally, you now know how to create shiny, professional–looking software with fancy GUI installers—or how to automate the generation of those precious .tar.gz files. Here is a summary of the specific concepts covered:

. The Distutils toolkit lets you write installer scripts, conventionally called setup.py, which let you install modules, packages, and extensions, and which let you build distributable archives and simple Windows installers.

. You can run your setup.py script with several commands, such as build, build_ext, install, sdist, and bdist.

Installers. There are many installer generators available, and you can use many of them to install your Python programs, making the process easier for your users.

. You can use Distutils to have your C extensions compiled automatically, with Distutils automatically locating your Python installation and figuring out which compiler to use. You can even have it run SWIG automatically.

py2exe. The py2exe extension to Distutils can be used to create executable binaries from your Python programs. Along with a couple of extra files (which can be conveniently installed with an installer), these .exe files can be run without installing a Python interpreter separately.

This reference chapter has described every command, option and public DB:: variable provided by the Perl debugger. You will be able to use any of these tools to control your program’s execution, study its behavior, and inspect or change any data during the runtime of the program. Finally, you learned how to call the debugger in several different cases, depending on the context required.

Here are the main topics covered in the chapter:

. Basically: Test first, code later. Tests let you rewrite your code with confidence, making your development and maintenance more flexible.

. These are indispensible tools if you want to do unit testing in Python. The doctest module is designed to check examples in docstrings, but can easily be used to design test suites. For more flexibility and structure in your suites, the unittest framework is very useful.

. These two tools read source code and point out potential (and actual) problems. They check everything from short variable names to unreachable pieces of code. With a little coding you can make them (or one of them) part of your test suite, to make sure all of your rewrites and refactorings conform to your coding standards.

. If you really care about speed and want to optimize your program (only do this if it’s absolutely necessary), you should profile it first. Use the profile (or hotshot) module to find bottlenecks in your code.