Mailman 3 August 2003 - Python-announce-list

ANN: soprano 0.003
by frank 19 Aug '03

19 Aug '03

Soprano is a GUI app that scans a selected range of ip addresses and try to get info about the hosts such as users, localgroups, shares, operating system. This program only runs under windows. changes 0.002 > 0.003:. added settings window setting are saved in xml and are stored under data\setting.xml setting include: "logon as" with username and password or use null request resolv hostname shares users groups info portscanner improved right click menu\submenu new functions: add user add group add share send msg (NetMessageBufferSend) Source code and windows binary at http://sourceforge.net/projects/soprano/

1 0

python-dev Summary for 2003-08-01 through 2003-08-15
by Brett C. 18 Aug '03

18 Aug '03

python-dev Summary for 2003-08-01 through 2003-08-15 ++++++++++++++++++++++++++++++++++++++++++++++++++++ This is a summary of traffic on the `python-dev mailing list`_ from August 1, 2003 through August 15, 2003. It is intended to inform the wider Python community of on-going developments on the list. To comment on anything mentioned here, just post to python-list(a)python.org or `comp.lang.python`_ with a subject line mentioning what you are discussing. All python-dev members are interested in seeing ideas discussed by the community, so don't hesitate to take a stance on something. And if all of this really interests you then get involved and join `python-dev`_! This is the twenty-third summary written by Brett Cannon (about to move for the umpteenth time). All summaries are archived at http://www.python.org/dev/summary/ . Please note that this summary is written using reStructuredText_ which can be found at http://docutils.sf.net/rst.html . Any unfamiliar punctuation is probably markup for reST_ (otherwise it is probably regular expression syntax or a typo =); you can safely ignore it, although I suggest learning reST; its simple and is accepted for `PEP markup`_ and gives some perks for the HTML output. Also, because of the wonders of programs that like to reformat text, I cannot guarantee you will be able to run the text version of this summary through Docutils_ as-is unless it is from the original text file. .. _PEP Markup: http://www.python.org/peps/pep-0012.html The in-development version of the documentation for Python can be found at http://www.python.org/dev/doc/devel/ and should be used when looking up any documentation on something mentioned here. Python PEPs (Python Enhancement Proposals) are located at http://www.python.org/peps/ . To view files in the Python CVS online, go to http://cvs.sourceforge.net/cgi-bin/viewcvs.cgi/python/ . .. _python-dev: http://www.python.org/dev/ .. _python-dev mailing list: http://mail.python.org/mailman/listinfo/python-dev .. _comp.lang.python: http://groups.google.com/groups?q=comp.lang.python .. _Docutils: http://docutils.sf.net/ .. _reST: .. _reStructuredText: http://docutils.sf.net/rst.html .. contents:: .. _last summary: http://www.python.org/dev/summary/2003-07-01_2003-07-31.html ===================== Summary Announcements ===================== Well, Michael Chermside responded to my question from the last summary about whether the new format and style of the Summaries was good. Once again a single person has led to how the summaries will be handled. You guys need to speak up (although I like the side that won this time =)! I am playing with layout once again. This time I am changing how the "contributing threads" lists are formatted. I know some of you hate inlined links in reST markup, but when these lists become huge it becomes really hard to keep track of the URIs when I have to list them away from the actual item on a separate line below the list of thread names. With `Python 2.3` out the door bug reports have started to come in. Work on 2.3.1 has begun. Please keep running the regression tests (easiest way is to run either ``make test`` or run regrtest.py in the test package; see the docs for the test package for help). On a personal note, if anyone knows of any Python users and such in the San Luis Obispo area of California, drop me a line at brett at python.org. ========= Summaries ========= ----------------------------------------- Python user helping Parrot? Treacherous! ----------------------------------------- Michal Wallace decided to get AM Kuchling's `previous work <http://www.amk.ca/conceit/parrot.html>`__ on getting Python code to run on the Parrot_ virtual machine (which is what Perl 6 will use). Well, the rather nutty fellow managed to get pretty damn far with it as shown at http://pirate.versionhost.com/viewcvs.cgi/pirate/ . Michal was actually almost done with handling pure Python code and was getting ready to try to figure out how to get Parrot to handle C extension modules with that being the biggest sticking point. Since Parrot is not Python it does not have a parser for Python code; problem if your code has an exec statement. This turned out to not be a worry, though, since there are pure Python parsers out there. All of this has direct relevance to python-dev because of the bet between Guido and Dan Sugalski, developer of Parrot. The rules are outlined at http://www.sidhe.org/~dan/blog/archives/2003_07.html#000219 . What is going to happen at OSCON 2004 is a benchmark program written in pure Python will be run using a CVS checkout of Python against a Parrot (after converting the bytecode to Parrot's own bytecode) checkout; slowest implementation's author gets a pie in the face, buy the winner's dev team a round of beer, and $10. So why have this bet? This was discussed and basically came down to finding out whether Parrot really can run Python fast. Parrot wants to be the VM for as many languages as possible, including Python. This acts as a way to motivate people to see how feasible this is. And don't think that the CPython interpreter will disappear if Parrot wins. Dan pointed out that even if he did win the bet that Guido would probably want to keep CPython around since that is under his control and allows testing out new language features much easier then having to deal with Parrot and an external dev team. In other words, let other people worry about forcing a Python-shaped peg into a Parrot-sized hole. .. _Parrot: http://www.parrotcode.org/ Contributing threads: * `pirate (python+parrot) <http://mail.python.org/pipermail/python-dev/2003-August/037407.html>`__ ---------------------------------------------------- python-mode gets its own SF project; Vim users laugh ---------------------------------------------------- Barry Warsaw, citing lack of time to "properly maintain python-mode.el", has created a SourceForge project for the Emacs mode at http://sf.net/projects/python-mode . This means all bug reports, patches, etc. should be done at that project. Martin v. Löwis suggested removing `python-mode.el`_ from Python itself and to get it distributed with Emacs_ and XEmacs_. This way there does not have to be any synchronization between the new SF project and the Python CVS tree. As of right now, though, python-mode.el is still in the Python CVS. And to give equal billing to Vim_, my code editor of choice, since it does not get as much coverage on python-dev as XEmacs does, here are some scripts you might want to check out: taglist.vim : http://vim.sourceforge.net/scripts/script.php?script_id=273 "provides an overview of the structure of source code files" by splitting the window. python_fold.vim : http://vim.sourceforge.net/scripts/script.php?script_id=515 "This script uses the expr fold-method to create folds for python source code." vimDebug : http://vim.sourceforge.net/scripts/script.php?script_id=663 " integrates your favorite debugger with vim." .. _python-mode.el: http://sf.net/projects/python-mode .. _Emacs: http://www.gnu.org/software/emacs/emacs.html .. _XEmacs: http://www.xemacs.org/ .. _Vim: http://www.vim.org/ Contributing threads: * `New python-mode project at SourceForge <http://mail.python.org/pipermail/python-dev/2003-August/037410.html>`__ * New place for python-mode bug reports and patches <http://mail.python.org/pipermail/python-dev/2003-August/037451.html>`__ -------------------- Caching tuple hashes -------------------- Raymond Hettinger asked if there was any reason why tuples, being immutable, didn't cache their hash values. Strings cache their hashes and they are immutable, so it seem to make sense. It was pointed out, though, that tuples could contain an object that changed its hash value between hash calls. Guido said, though, that it was the responsibility of the object and not tuples to worry about keeping a consistent hash value. Guido also explained why strings cache their hashes. It turns out that since strings are used so often for keys in dicts that caching their hashes gave a large performance boost for almost any program, so the effort was felt justified. But Guido did not see this same justification for tuples. Thus tuples will not cache their hash values. Contributing threads: * `Caching tuple hashes <http://mail.python.org/pipermail/python-dev/2003-August/037416.html>`__ ------------------------------- PyCon 2004 is under development ------------------------------- Preparation for PyCon_ 2004 have now begun. With us getting the ball rolling much earlier this conference should turn out to be even better than last year (which, in my opinion, was great)! You can go to http://www.python.org/pycon/dc2004/ to find links to lists to get involved in organizing or just to be kept abreast of new developments. .. _PyCon: http://www.python.org/pycon/dc2004/ Contributing threads: * `PyCon DC 2004 Kickoff! <http://mail.python.org/pipermail/python-dev/2003-August/037437.html>`__ ---------------------------- Let the fixing of 2.3 begin! ---------------------------- The maintenance branch of Python 2.3 (named release23-maint) has been created in CVS. Several bugs have already been fixed. For instructions on how to check out a copy of the branch, read http://www.python.org/dev/devfaq.html#c10 . Contributing threads: * `Python 2.3 maintenance branch is now open <http://mail.python.org/pipermail/python-dev/2003-August/037440.html>`__ ------------------------------------ When a void doesn't equal an integer ------------------------------------ After clearing up the confusing issue of the difference between a Python int and a Python Integer (the former is <type 'int'> while the latter is the union of <type 'int'> and <type 'long'> which is what Python is moving towards so that the distinction practically disappears), the discussion of how to handle a quirk of Win64 commenced. It turns out that Win64 thinks that ``sizeof(void *) > sizeof(long)`` is a reasonable thing to do. Well, all other platforms now and most likely for the rest of Tim Peter's life (at least according to Tim's guess) don't and won't hold this to be true. As of right now Python claims that a void pointer can be held in a Python int, but Win64 breaks that claim. Do we muck around with Python's internals for this one strange exception that does not make sense, such as making Python ints use long long? No, of course not. Code would break, let alone the added complexity. So the needed changes to the failing tests were dealt with and all seems to be fine with the world again ... well, Win64 is still thinking on crack, but that is someone else's problem. Contributing threads: * `sizeof(long) != sizeof(void*) <http://mail.python.org/pipermail/python-dev/2003-August/037465.html>`__ ------------------------------------ Where do I put all of my packages?!? ------------------------------------ As it stands now there are four places where packages can reside: 1. standard library 2. site-packages 3. site-python (on UNIX this is the same directory where your python2.3 directory exists) 4. PYTHONPATH environment variable It was pointed out that this does not necessarily give one all the options one might want. The above covers the Python core easily, but there is not clear distinction for vendor packages, network-installed packages, system-wide packages or user-installed packages; they are covered by 2-4 above. The suggestion was to make more distinct places available for installation and to make distutils aware of them. A good way to see how this would be useful is to look at how OS X's Panther will handle Python 2.3 . It will have the standard library in the standard location of /usr/local/python2.4 . In that directory, the site-packages directory is a symlink to a more system-aware location. This is fine but what about a sysadmin who would rather avoid the possibility of breaking OS X by messing with the OS's Python installation? What about a user on that system who does not have root but wants to have their own place to put their packages? There is definitely room for adding more standard path locations for package installations. A PEP was being mentioned but appears to not have been written yet. Contributing threads: * `Multiple levels of site-packages <http://mail.python.org/pipermail/python-dev/2003-August/037487.html>`__ ------------------------- Be careful with __slots__ ------------------------- Raymond Hettinger observed that using __slots__ or overriding __getattribute__ fails silently when mistakenly used with old-style classes. This has bitten him and others in the bum so he wanted to add warning/error messages. Guido recommended passing on the warnings because 1) those are "expert use only" tools, 2) PyChecker can already detect the issue, and 3) there are other new-style/classic issues cannot as readily be flagged. It should be known that "__slots__ is a terrible hack with nasty, hard-to-fathom side effects that should only be used by programmers at grandmaster and wizard levels". So only use __slots__ if you can apply the label of "programmer at grandmaster or wizard level" to yourself without your programming peers laughting their bums off; you have been warned. Contributing threads: * `Make it an error to use __slots__ with classic classes <http://mail.python.org/pipermail/python-dev/2003-August/037537.html>`__ -------------- Plugging leaks -------------- Michael Hudson thought he had discovered a leak somewhere and went off on a little hunt. It turned out to be a red herring more or less, but there was some discussion on the best way to find leaks through regression tests. The basic scheme that everyone seemed to use was to run the regression test once to get any caching out of the way and then run the test a set number of times and see if the reference counts seemed to grow. Michael Hudson posted a diff to add such a testing feature to test/regrtest.py at http://mail.python.org/pipermail/python-dev/2003-August/037617.html . Tim Peters also posted a link to Zope's test driver at http://cvs.zope.org/Zope3/test.py which includes a class named TrackRefs which can help keep track of the leaked references as well as leaked objects. Contributing threads: * `CALL_ATTR patch <http://mail.python.org/pipermail/python-dev/2003-August/037485.html>`__ * `refleak hunting fun! <http://mail.python.org/pipermail/python-dev/2003-August/037617.html>`__ ----------------------------------------- Making the interpreter its own executable ----------------------------------------- As it stands now the Python interpreter is distributed as a bunch of files mostly made up of the standard library. But wouldn't it be nice if you could make the interpreter just a single executable that was easy to distribute with your code? Well, that discussion cropped up on `comp.lang.python`_ at http://groups.google.com/groups?hl=en&lr=&ie=UTF-8&safe=off&threadm=ptji8wg… . The idea was to somehow introduce a hook into Py_Main() that could harness the new zipimport facility. The idea came up of appending the stdlib to the end of the Python interpreter and to have a flag set to signal that the appending had occurred. The problem is that this could cause unzipping problems. But setting the flag is not necessarily simple either. One suggestion was to literally patch the interpreter to set the flag. But there was some confusion over the use of the term "patch"; Thomas Heller thought more of "link with an object file defining this global variable". This thread was still going as of this writing and had not yet reached a clear solution. Contributing threads: * `hook for standalone executable <http://mail.python.org/pipermail/python-dev/2003-August/037528.html>`__

1 0

Python 2.3 for RISC OS
by Dietmar Schwertberger 18 Aug '03

18 Aug '03

============================================================================ Python 2.3 for RISC OS release 2003-08-03 ============================================================================ I'm pleased to announce that binaries of Python 2.3 for RISC OS are available from http://www.schwertberger.de/python.html . RISC OS Python includes the following highlights: * An integrated interface to the SWI system * Drawfile support * Interfaces to the RISC OS WIMP and toolbox (with examples) * Numeric extension * PeerBoard: share your clipboard contents between multiple RISC OS and win32 computers over TCP/IP connections * SSLRelay: a simple SSL proxy server For use of Python you will need a filing system with long filename and >77 files/directory support. Bug reports etc. ================ RISC OS specific bug reports, contributions, comments, critics, links to RISC OS compatible Python libraries to dietmar(a)schwertberger.de

1 0

SC-Track Roundup 0.6.0 - an issue tracking system
by Richard Jones 18 Aug '03

18 Aug '03

================================================= SC-Track Roundup 0.6.0 - an issue tracking system ================================================= I'm pleased to announce the latest feature-packed release of Roundup. See below for a list of some of the goodies included in this release. If you're upgrading from an older version of Roundup you *must* follow the "Software Upgrade" guidelines given in the maintenance documentation. Unfortunately, the Zope frontend for Roundup is currently broken. I hope to revive it in a future 0.6 bugfix release. The gadfly backend has now been removed, having served its purpose as a template for other RDBMS implementations. It is replaced by the sqlite and mysql backends. Roundup requires python 2.1.3 or later for correct operation. The 0.6 release has lots of new goodies including: - new instant-gratification Demo Mode ("python demo.py" :) - added mysql backend (see doc/mysql.txt for details) - web interface cleanups including nicer history display, nicer index navigation and nicer popup list windows - searching of date ranges - better international support, including utf-8 email handling and ability to display localized dates in web interface. - more documentation including revamped design document, unix manual pages and some FAQ entries - significantly more powerful form handling allowing editing of multiple items and creation of multiple items - tracker templates can contain subdirectories and static files (e.g. images) and we may now distribute templates separately from Roundup. Template HTML files now have a .html extension too. - user registration is now a two-step process, with confirmation from the email address supplied in the registration form, and we also have a password reset feature for forgotten password / login - Windows Service mode for roundup-server when daemonification is attempted on Windows - lots of speed enhancements, making the web interface much more responsive - fixed issues with dumb email or web clients - email system handles more SMTP and POP features (TLS, APOP, ...) - lots more little tweaks and back-end work... Source and documentation is available at the website: http://roundup.sourceforge.net/ Release Info (via download page): http://sourceforge.net/projects/roundup Mailing lists - the place to ask questions: http://sourceforge.net/mail/?group_id=31577 About Roundup ============= Roundup is a simple-to-use and -install issue-tracking system with command-line, web and e-mail interfaces. It is based on the winning design from Ka-Ping Yee in the Software Carpentry "Track" design competition. Note: Ping is not responsible for this project. The contact for this project is richard(a)users.sourceforge.net. Roundup manages a number of issues (with flexible properties such as "description", "priority", and so on) and provides the ability to: (a) submit new issues, (b) find and edit existing issues, and (c) discuss issues with other participants. The system will facilitate communication among the participants by managing discussions and notifying interested parties when issues are edited. One of the major design goals for Roundup that it be simple to get going. Roundup is therefore usable "out of the box" with any python 2.1+ installation. It doesn't even need to be "installed" to be operational, though a disutils-based install script is provided. It comes with two issue tracker templates (a classic bug/feature tracker and a minimal skeleton) and six database back-ends (anydbm, bsddb, bsddb3, sqlite, metakit and mysql).

1 1

ANN: PyQt v3.8 Released
by Phil Thompson 17 Aug '03

17 Aug '03

PyQt v3.8 has been released and can be downloaded from http://www.riverbankcomputing.co.uk/pyqt/ Highlights of this release include the addition of many operators to existing classes and full support for Qt v3.2.0. PyQt is a comprehensive set of Python bindings for Trolltech's Qt GUI toolkit. It includes approximately 300 classes and 5,750 methods including OpenGL, SQL and XML support as well as a rich set of GUI widgets. It also includes a utility to generate Python code from Qt Designer, Qt's GUI builder. PyQt runs on UNIX/Linux, Windows and the Sharp Zaurus. PyQt is licensed under the GPL, commercial, educational and non-commercial licenses. Phil

1 0

Python on Windows FAQ
by amk＠nyman.amk.ca 16 Aug '03

16 Aug '03

This FAQ collects questions about using Python on Windows. Many of the more specific questions deal with one Windows bug or another; it's not clear how many of these bugs are still relevant for users of Windows XP or 2000. Please *don't* send me comments about the questions, because I can't tell which comments are correct and which aren't, so I'm not planning to make any changes to the file. A Windows-using maintainer is desperately needed. If you want to be the maintainer, just grab a copy of the reStructured Text source from http://www.python.org/doc/faq/windows.ht, edit away, and send your updated draft to the python.org webmaster address. --amk Title: Python Windows FAQ Content-type: text/x-rst ==================================== Python Windows FAQ ==================================== :Date: $Date: 2003/08/14 20:41:20 $ :Version: $Revision: 1.2 $ :Web site: http://www.python.org/ .. contents:: .. sectnum:: How do I run a Python program under Windows? ---------------------------------------------------- This is not necessarily a straightforward question. If you are already familiar with running programs from the Windows command line then everything will seem obvious; otherwise, you might need a little more guidance. There are also differences between Windows 95, 98, NT, ME, 2000 and XP which can add to the confusion. Unless you use some sort of integrated development environment, you will end up *typing* Windows commands into what is variously referred to as a "DOS window" or "Command prompt window". Usually you can create such a window from your Start menu; under Windows 2000 the menu selection is "Start | Programs | Accessories | Command Prompt". You should be able to recognize when you have started such a window because you will see a Windows "command prompt", which usually looks like this:: C:\> The letter may be different, and there might be other things after it, so you might just as easily see something like:: D:\Steve\Projects\Python> depending on how your computer has been set up and what else you have recently done with it. Once you have started such a window, you are well on the way to running Python programs. You need to realize that your Python scripts have to be processed by another program called the Python interpreter. The interpreter reads your script, compiles it into bytecodes, and then executes the bytecodes to run your program. So, how do you arrange for the interpreter to handle your Python? First, you need to make sure that your command window recognises the word "python" as an instruction to start the interpreter. If you have opened a command window, you should try entering the command ``python`` and hitting return. You should then see something like:: Python 2.2 (#28, Dec 21 2001, 12:21:22) [MSC 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> You have started the interpreter in "interactive mode". That means you can enter Python statements or expressions interactively and have them executed or evaluated while you wait. This is one of Python's strongest features. Check it by entering a few expressions of your choice and seeing the results:: >>> print "Hello" Hello >>> "Hello" * 3 HelloHelloHello Many people use the interactive mode as a convenient yet highly programmable calculator. When you want to end your interactive Python session, hold the Ctrl key down while you enter a Z, then hit the "Enter" key to get back to your Windows command prompt. You may also find that you have a Start-menu entry such as "Start | Programs | Python 2.2 | Python (command line)" that results in you seeing the ">>>" prompt in a new window. If so, the window will disappear after you enter the Ctrl-Z character; Windows is running a single "python" command in the window, and closes it when you terminate the interpreter. If the ``python`` command, instead of displaying the interpreter prompt ">>>", gives you a message like:: 'python' is not recognized as an internal or external command, operable program or batch file. or:: Bad command or filename then you need to make sure that your computer knows where to find the Python interpreter. To do this you will have to modify a setting called PATH, which is a list of directories where Windows will look for programs. You should arrange for Python's installation directory to be added to the PATH of every command window as it starts. If you installed Python fairly recently then the command :: dir C:\py* will probably tell you where it is installed; the usual location is something like C:\Python23. Otherwise you will be reduced to a search of your whole disk ... use "Tools | Find" or hit the "Search" button and look for "python.exe". Supposing you discover that Python is installed in the C:\Python23 directory (the default at the time of writing), you should make sure that entering the command :: c:\Python23\python starts up the interpreter as above (and don't forget you'll need a "CTRL-Z" and an "Enter" to get out of it). Once you have verified the directory, you need to add it to the start-up routines your computer goes through. For older versions of Windows the easiest way to do this is to edit the C:\AUTOEXEC.BAT file. You would want to add a line like the following to AUTOEXEC.BAT:: PATH C:\Python23;%PATH% For Windows NT, 2000 and (I assume) XP, you will need to add a string such as :: ;C:\Python23 to the current setting for the PATH environment variable, which you will find in the properties window of "My Computer" under the "Advanced" tab. Note that if you have sufficient privilege you might get a choice of installing the settings either for the Current User or for System. The latter is preferred if you want everybody to be able to run Python on the machine. If you aren't confident doing any of these manipulations yourself, ask for help! At this stage you may want to reboot your system to make absolutely sure the new setting has taken effect. You probably won't need to reboot for Windows NT, XP or 2000. You can also avoid it in earlier versions by editing the file C:\WINDOWS\COMMAND\CMDINIT.BAT instead of AUTOEXEC.BAT. You should now be able to start a new command window, enter ``python`` at the "C:>" (or whatever) prompt, and see the ">>>" prompt that indicates the Python interpreter is reading interactive commands. Let's suppose you have a program called "pytest.py" in directory "C:\Steve\Projects\Python". A session to run that program might look like this:: C:\> cd \Steve\Projects\Python C:\Steve\Projects\Python> python pytest.py Because you added a file name to the command to start the interpreter, when it starts up it reads the Python script in the named file, compiles it, executes it, and terminates, so you see another "C:\>" prompt. You might also have entered :: C:\> python \Steve\Projects\Python\pytest.py if you hadn't wanted to change your current directory. Under NT, 2000 and XP you may well find that the installation process has also arranged that the command ``pytest.py`` (or, if the file isn't in the current directory, ``C:\Steve\Projects\Python\pytest.py``) will automatically recognize the ".py" extension and run the Python interpreter on the named file. Using this feature is fine, but *some* versions of Windows have bugs which mean that this form isn't exactly equivalent to using the interpreter explicitly, so be careful. The important things to remember are: 1. Start Python from the Start Menu, or make sure the PATH is set correctly so Windows can find the Python interpreter. :: python should give you a '>>>" prompt from the Python interpreter. Don't forget the CTRL-Z and ENTER to terminate the interpreter (and, if you started the window from the Start Menu, make the window disappear). 2. Once this works, you run programs with commands:: python {program-file} 3. When you know the commands to use you can build Windows shortcuts to run the Python interpreter on any of your scripts, naming particular working directories, and adding them to your menus. Take a look at :: python --help if your needs are complex. 4. Interactive mode (where you see the ">>>" prompt) is best used for checking that individual statements and expressions do what you think they will, and for developing code by experiment. How do I make python scripts executable? ---------------------------------------------- On Windows 2000, the standard Python installer already associates the .py extension with a file type (Python.File) and gives that file type an open command that runs the interpreter (D:\Program Files\Python\python.exe "%1" %*). This is enough to make scripts executable from the command prompt as 'foo.py'. If you'd rather be able to execute the script by simple typing 'foo' with no extension you need to add .py to the PATHEXT environment variable. On Windows NT, the steps taken by the installer as described above allow you to run a script with 'foo.py', but a longtime bug in the NT command processor prevents you from redirecting the input or output of any script executed in this way. This is often important. The incantation for making a Python script executable under WinNT is to give the file an extension of .cmd and add the following as the first line:: @setlocal enableextensions & python -x %~f0 %* & goto :EOF Where is Freeze for Windows? ------------------------------------ "Freeze" is a program that allows you to ship a Python program as a single stand-alone executable file. It is *not* a compiler; your programs don't run any faster, but they are more easily distributable, at least to platforms with the same OS and CPU. Read the README file of the freeze program for more disclaimers. You can use freeze on Windows, but you must download the source tree (see http://www.python.org/download/download_source.html). The freeze program is in the ``Tools\freeze`` subdirectory of the source tree. You need the Microsoft VC++ compiler, and you probably need to build Python. The required project files are in the PCbuild directory. Is a ``*.pyd`` file the same as a DLL? ------------------------------------------ Yes, .pyd files are dll's, but there are a few differences. If you have a DLL named foo.pyd, then it must have a function initfoo(). You can then write Python "import foo", and Python will search for foo.pyd (as well as foo.py, foo.pyc) and if it finds it, will attempt to call initfoo() to initialize it. You do not link your .exe with foo.lib, as that would cause Windows to require the DLL to be present. Note that the search path for foo.pyd is PYTHONPATH, not the same as the path that Windows uses to search for foo.dll. Also, foo.pyd need not be present to run your program, whereas if you linked your program with a dll, the dll is required. Of course, foo.pyd is required if you want to say "import foo". In a DLL, linkage is declared in the source code with __declspec(dllexport). In a .pyd, linkage is defined in a list of available functions. How can I embed Python into a Windows application? ---------------------------------------------------------- Embedding the Python interpreter in a Windows app can be summarized as follows: 1. Do _not_ build Python into your .exe file directly. On Windows, Python must be a DLL to handle importing modules that are themselves DLL's. (This is the first key undocumented fact.) Instead, link to pythonNN.dll; it is typically installed in c:\Windows\System. NN is the Python version, a number such as "23" for Python 2.3. You can link to Python statically or dynamically. Linking statically means linking against pythonNN.lib, while dynamically linking means linking against pythonNN.dll. The drawback to dynamic linking is that your app won't run if pythonNN.dll does not exist on your system. (General note: pythonNN.lib is the so-called "import lib" corresponding to python.dll. It merely defines symbols for the linker.) Linking dynamically greatly simplifies link options; everything happens at run time. Your code must load pythonNN.dll using the Windows LoadLibraryEx() routine. The code must also use access routines and data in pythonNN.dll (that is, Python's C API's) using pointers obtained by the Windows GetProcAddress() routine. Macros can make using these pointers transparent to any C code that calls routines in Python's C API. Borland note: convert pythonNN.lib to OMF format using Coff2Omf.exe first. 2. If you use SWIG, it is easy to create a Python "extension module" that will make the app's data and methods available to Python. SWIG will handle just about all the grungy details for you. The result is C code that you link *into* your .exe file (!) You do _not_ have to create a DLL file, and this also simplifies linking. 3. SWIG will create an init function (a C function) whose name depends on the name of the extension module. For example, if the name of the module is leo, the init function will be called initleo(). If you use SWIG shadow classes, as you should, the init function will be called initleoc(). This initializes a mostly hidden helper class used by the shadow class. The reason you can link the C code in step 2 into your .exe file is that calling the initialization function is equivalent to importing the module into Python! (This is the second key undocumented fact.) 4. In short, you can use the following code to initialize the Python interpreter with your extension module. :: #include "python.h" ... Py_Initialize(); // Initialize Python. initmyAppc(); // Initialize (import) the helper class. PyRun_SimpleString("import myApp") ; // Import the shadow class. 5. There are two problems with Python's C API which will become apparent if you use a compiler other than MSVC, the compiler used to build pythonNN.dll. Problem 1: The so-called "Very High Level" functions that take FILE * arguments will not work in a multi-compiler environment because each compiler's notion of a struct FILE will be different. From an implementation standpoint these are very _low_ level functions. Problem 2: SWIG generates the following code when generating wrappers to void functions:: Py_INCREF(Py_None); _resultobj = Py_None; return _resultobj; Alas, Py_None is a macro that expands to a reference to a complex data structure called _Py_NoneStruct inside pythonNN.dll. Again, this code will fail in a mult-compiler environment. Replace such code by:: return Py_BuildValue(""); It may be possible to use SWIG's %typemap command to make the change automatically, though I have not been able to get this to work (I'm a complete SWIG newbie). 6. Using a Python shell script to put up a Python interpreter window from inside your Windows app is not a good idea; the resulting window will be independent of your app's windowing system. Rather, you (or the wxPythonWindow class) should create a "native" interpreter window. It is easy to connect that window to the Python interpreter. You can redirect Python's i/o to _any_ object that supports read and write, so all you need is a Python object (defined in your extension module) that contains read() and write() methods. How do I use Python for CGI? ------------------------------------------------------- On the Microsoft IIS server or on the Win95 MS Personal Web Server you set up Python in the same way that you would set up any other scripting engine. Run regedt32 and go to:: HKEY_LOCAL_MACHINE\SYSTEM\CurrentControlSet\Services\W3SVC\Parameters\ScriptMap and enter the following line (making any specific changes that your system may need):: .py :REG_SZ: c:\<path to python>\python.exe -u %s %s This line will allow you to call your script with a simple reference like: http://yourserver/scripts/yourscript.py provided "scripts" is an "executable" directory for your server (which it usually is by default). The "-u" flag specifies unbuffered and binary mode for stdin - needed when working with binary data. In addition, it is recommended that using ".py" may not be a good idea for the file extensions when used in this context (you might want to reserve ``*.py`` for support modules and use ``*.cgi`` or ``*.cgp`` for "main program" scripts). In order to set up Internet Information Services 5 to use Python for CGI processing, please see the following links: http://www.e-coli.net/pyiis_server.html (for Win2k Server) http://www.e-coli.net/pyiis.html (for Win2k pro) Configuring Apache is much simpler. In the Apache configuration file ``httpd.conf``, add the following line at the end of the file:: ScriptInterpreterSource Registry Then, give your Python CGI-scripts the extension .py and put them in the cgi-bin directory. How do I keep editors from inserting tabs into my Python source? ------------------------------------------------------------------ The FAQ does not recommend using tabs, and `the Python style guide <http://www.python.org/peps/pep-0008.html>`_ recommends 4 spaces for distributed Python code; this is also the Emacs python-mode default. Under any editor, mixing tabs and spaces is a bad idea. MSVC is no different in this respect, and is easily configured to use spaces: Take Tools -> Options -> Tabs, and for file type "Default" set "Tab size" and "Indent size" to 4, and select the "Insert spaces" radio button. If you suspect mixed tabs and spaces are causing problems in leading whitespace, run Python with the -t switch or run ``Tools/Scripts/tabnanny.py`` to check a directory tree in batch mode. How do I check for a keypress without blocking? ---------------------------------------------------- Use the msvcrt module. This is a standard Windows-specific extension module. It defines a function kbhit() which checks whether a keyboard hit is present, and getch() which gets one character without echoing it. How do I emulate os.kill() in Windows? --------------------------------------------- Use win32api:: def kill(pid): """kill function for Win32""" import win32api handle = win32api.OpenProcess(1, 0, pid) return (0 != win32api.TerminateProcess(handle, 0)) Why does os.path.isdir() fail on NT shared directories? -------------------------------------------------------------- The solution appears to be always append the "\\" on the end of shared drives. :: >>> import os >>> os.path.isdir( '\\\\rorschach\\public') 0 >>> os.path.isdir( '\\\\rorschach\\public\\') 1 It helps to think of share points as being like drive letters. Example:: k: is not a directory k:\ is a directory k:\media is a directory k:\media\ is not a directory The same rules apply if you substitute "k:" with "\\conky\foo":: \\conky\foo is not a directory \\conky\foo\ is a directory \\conky\foo\media is a directory \\conky\foo\media\ is not a directory cgi.py (or other CGI programming) doesn't work sometimes on NT or win95! ----------------------------------------------------------------------------- Be sure you have the latest python.exe, that you are using python.exe rather than a GUI version of Python and that you have configured the server to execute :: "...\python.exe -u ..." for the CGI execution. The -u (unbuffered) option on NT and Win95 prevents the interpreter from altering newlines in the standard input and output. Without it post/multipart requests will seem to have the wrong length and binary (e.g. GIF) responses may get garbled (resulting in broken images, PDF files, and other binary downloads failing). Why doesn't os.popen() work in PythonWin on NT? ------------------------------------------------------- The reason that os.popen() doesn't work from within PythonWin is due to a bug in Microsoft's C Runtime Library (CRT). The CRT assumes you have a Win32 console attached to the process. You should use the win32pipe module's popen() instead which doesn't depend on having an attached Win32 console. Example:: import win32pipe f = win32pipe.popen('dir /c c:\\') print f.readlines() f.close() Why doesn't os.popen()/win32pipe.popen() work on Win9x? --------------------------------------------------------------- There is a bug in Win9x that prevents os.popen/win32pipe.popen* from working. The good news is there is a way to work around this problem. The Microsoft Knowledge Base article that you need to lookup is: Q150956. You will find links to the knowledge base at: http://www.microsoft.com/kb. PyRun_SimpleFile() crashes on Windows but not on Unix; why? ------------------------------------------------------------ This is very sensitive to the compiler vendor, version and (perhaps) even options. If the FILE* structure in your embedding program isn't the same as is assumed by the Python interpreter it won't work. The Python 1.5.* DLLs (python15.dll) are all compiled with MS VC++ 5.0 and with multithreading-DLL options (``/MD``). If you can't change compilers or flags, try using Py_RunSimpleString(). A trick to get it to run an arbitrary file is to construct a call to execfile() with the name of your file as argument. Also note that you can not mix-and-match Debug and Release versions. If you wish to use the Debug Multithreaded DLL, then your module _must_ have an "_d" appended to the base name. Importing _tkinter fails on Windows 95/98: why? ------------------------------------------------ Sometimes, the import of _tkinter fails on Windows 95 or 98, complaining with a message like the following:: ImportError: DLL load failed: One of the library files needed to run this application cannot be found. It could be that you haven't installed Tcl/Tk, but if you did install Tcl/Tk, and the Wish application works correctly, the problem may be that its installer didn't manage to edit the autoexec.bat file correctly. It tries to add a statement that changes the PATH environment variable to include the Tcl/Tk 'bin' subdirectory, but sometimes this edit doesn't quite work. Opening it with notepad usually reveals what the problem is. (One additional hint, noted by David Szafranski: you can't use long filenames here; e.g. use C:\PROGRA~1\Tcl\bin instead of C:\Program Files\Tcl\bin.) How do I extract the downloaded documentation on Windows? ------------------------------------------------------------ Sometimes, when you download the documentation package to a Windows machine using a web browser, the file extension of the saved file ends up being .EXE. This is a mistake; the extension should be .TGZ. Simply rename the downloaded file to have the .TGZ extension, and WinZip will be able to handle it. (If your copy of WinZip doesn't, get a newer one from http://www.winzip.com.) Missing cw3215mt.dll (or missing cw3215.dll) ---------------------------------------------------- Sometimes, when using Tkinter on Windows, you get an error that cw3215mt.dll or cw3215.dll is missing. Cause: you have an old Tcl/Tk DLL built with cygwin in your path (probably C:\Windows). You must use the Tcl/Tk DLLs from the standard Tcl/Tk installation (Python 1.5.2 comes with one). Warning about CTL3D32 version from installer ---------------------------------------------------- The Python installer issues a warning like this:: This version uses CTL3D32.DLL whitch is not the correct version. This version is used for windows NT applications only. [Tim Peters] This is a Microsoft DLL, and a notorious source of problems. The message means what it says: you have the wrong version of this DLL for your operating system. The Python installation did not cause this -- something else you installed previous to this overwrote the DLL that came with your OS (probably older shareware of some sort, but there's no way to tell now). If you search for "CTL3D32" using any search engine (AltaVista, for example), you'll find hundreds and hundreds of web pages complaining about the same problem with all sorts of installation programs. They'll point you to ways to get the correct version reinstalled on your system (since Python doesn't cause this, we can't fix it). David A Burton has written a little program to fix this. Go to http://www.burtonsys.com/download.html and click on "ctl3dfix.zip"

1 0

GUI FAQ
by amk＠nyman.amk.ca 16 Aug '03

16 Aug '03

The GUI FAQ is really minimal; there weren't many questions in the old FAQ about GUIs, so this FAQ consists of two general questions about what GUI toolkit are available from Python, and two very specific Tkinter questions. --amk Title: Graphic User Interface FAQ Content-type: text/x-rst ==================================== Graphic User Interface FAQ ==================================== :Date: $Date: 2003/08/15 21:14:43 $ :Version: $Revision: 1.2 $ :Web site: http://www.python.org/ .. contents:: .. sectnum:: General GUI Questions ============================ What platform-independent GUI toolkits exist for Python? ---------------------------------------------------------------- Depending on what platform(s) you are aiming at, there are several. Tkinter '''''''''''' Standard builds of Python include an object-oriented interface to the Tcl/Tk widget set, called Tkinter. This is probably the easiest to install and use. For more info about Tk, including pointers to the source, see the Tcl/Tk home page at http://www.tcl.tk. Tcl/Tk is fully portable to the MacOS, Windows, and Unix platforms. wxWindows ''''''''''''' wxWindows is a portable GUI class library written in C++ that's a portable interface to various platform-specific libraries; wxPython is a Python interface to wxWindows. wxWindows supports Windows and MacOS; on Unix variants, it supports both GTk+ and Motif toolkits. wxWindows preserves the look and feel of the underlying graphics toolkit, and there is quite a rich widget set and collection of GDI classes. See `the wxWindows page <http://www.wxwindows.org>`_ for more details. `wxPython <http://alldunn.com/wxPython>`_ is an extension module that wraps many of the wxWindows C++ classes, and is quickly gaining popularity amongst Python developers. You can get wxPython as part of the source or CVS distribution of wxWindows, or directly from its home page. GTk+ ''''''''''' PyGTk bindings for the GTk+ Toolkit by James Henstridge are available; see ftp://ftp.daa.com.au/pub/james/python. Qt '''''' There are bindings available for the Qt toolkit (PyQt). and for KDE (PyKDE); see http://www.thekompany.com/projects/pykde. If you're writing open source software, you don't need to pay for PyQt, but if you want to write proprietary applications, you must buy a license from XXX. For OpenGL bindings, see `PyOpenGL <http://pyopengl.sourceforge.net>`_. What platform-specific GUI toolkits exist for Python? ---------------------------------------------------------------- `The Mac port <http://www.python.org/download/download_mac.html>`_ by Jack Jansen has a rich and ever-growing set of modules that support the native Mac toolbox calls. The port includes support for MacOS9 and MacOS X's Carbon libraries. By installing the `PyObjc Objective-C bridge <http://pyobjc.sourceforge.net>`_, Python programs can use MacOS X's Cocoa libraries. See the documentation that comes with the Mac port. `Pythonwin <http://www.python.org/windows>`_ by Mark Hammond includes an interface to the Microsoft Foundation Classes and a Python programming environment using it that's written mostly in Python. Tkinter ===================== How do I freeze Tkinter applications? --------------------------------------------- Freeze is a tool to create stand-alone applications. When freezing Tkinter applications, the applications will not be truly stand-alone, as the application will still need the Tcl and Tk libraries. One solution is to ship the application with the tcl and tk libraries, and point to them at run-time using the TCL_LIBRARY and TK_LIBRARY environment variables. To get truly stand-alone applications, the Tcl scripts that form the library have to be integrated into the application as well. One tool supporting that is SAM (stand-alone modules), which is part of the Tix distribution (http://tix.mne.com). Build Tix with SAM enabled, perform the appropriate call to Tclsam_init etc inside Python's Modules/tkappinit.c, and link with libtclsam and libtksam (you might include the Tix libraries as well). Can I have Tk events handled while waiting for I/O? ----------------------------------------------------------- Yes, and you don't even need threads! But you'll have to restructure your I/O code a bit. Tk has the equivalent of Xt's XtAddInput() call, which allows you to register a callback function which will be called from the Tk mainloop when I/O is possible on a file descriptor. Here's what you need:: from Tkinter import tkinter tkinter.createfilehandler(file, mask, callback) The file may be a Python file or socket object (actually, anything with a fileno() method), or an integer file descriptor. The mask is one of the constants tkinter.READABLE or tkinter.WRITABLE. The callback is called as follows:: callback(file, mask) You must unregister the callback when you're done, using :: tkinter.deletefilehandler(file) Note: since you don't know *how many bytes* are available for reading, you can't use the Python file object's read or readline methods, since these will insist on reading a predefined number of bytes. For sockets, the recv() or recvfrom() methods will work fine; for other files, use os.read(file.fileno(), maxbytecount). I can't get key bindings to work in Tkinter: why? --------------------------------------------------- An often-heard complaint is that event handlers bound to events with the bind() method don't get handled even when the appropriate key is pressed. The most common cause is that the widget to which the binding applies doesn't have "keyboard focus". Check out the Tk documentation for the focus command. Usually a widget is given the keyboard focus by clicking in it (but not for labels; see the takefocus option).

1 0

Extending/Embedding FAQ
by amk＠nyman.amk.ca 16 Aug '03

16 Aug '03

The FAQ parade continues with the Extending/Embedding FAQ, covering Python's C API. Comments are welcome. (Volunteers to maintain any of these FAQs would be even more welcome.) --amk Title: Python Extending/Embedding FAQ Content-type: text/x-rst ==================================== Extending/Embedding FAQ ==================================== :Date: $Date: 2003/08/14 20:47:18 $ :Version: $Revision: 1.2 $ :Web site: http://www.python.org/ .. contents:: .. sectnum:: Can I create my own functions in C? ------------------------------------------ Yes, you can create built-in modules containing functions, variables, exceptions and even new types in C. This is explained in the document "Extending and Embedding the Python Interpreter" (http://www.python.org/doc/current/ext/ext.html). Most intermediate or advanced Python books will also cover this topic. Can I create my own functions in C++? -------------------------------------------- Yes, using the C compatibility features found in C++. Place ``extern "C" { ... }`` around the Python include files and put ``extern "C"`` before each function that is going to be called by the Python interpreter. Global or static C++ objects with constructors are probably not a good idea. Writing C is hard; are there any alternatives? --------------------------------------------------- There are a number of alternatives to writing your own C extensions, depending on what you're trying to do. If you need more speed, `Psyco <http://psyco.sourceforge.net/>`_ generates x86 assembly code from Python bytecode. You can use Psyco to compile the most time-critical functions in your code, and gain a significant improvement with very little effort, as long as you're running on a machine with an x86-compatible processor. `Pyrex <http://www.cosc.canterbury.ac.nz/~greg/python/Pyrex/>`_ is a compiler that accepts a slightly modified form of Python and generates the corresponding C code. Pyrex makes it possible to write an extension without having to learn Python's C API. If you need to interface to some C library for which no Python extension currently exists, you can try wrapping the library's data types and functions with a tool such as `SWIG <http://www.swig.org>`_. For C++ libraries, you can look at `SIP <http://www.riverbankcomputing.co.uk/sip/>`_, `CXX <http://cxx.sourceforge.net/>`_, `Boost <http://www.boost.org/libs/python/doc/index.html>`_, or `Weave <http://www.scipy.org/site_content/weave>`_. How can I execute arbitrary Python statements from C? ------------------------------------------------------------ The highest-level function to do this is ``PyRun_SimpleString()`` which takes a single string argument to be executed in the context of the module ``__main__`` and returns 0 for success and -1 when an exception occurred (including ``SyntaxError``). If you want more control, use ``PyRun_String()``; see the source for ``PyRun_SimpleString()`` in Python/pythonrun.c. How can I evaluate an arbitrary Python expression from C? ---------------------------------------------------------------- Call the function ``PyRun_String()`` from the previous question with the start symbol ``Py_eval_input``; it parses an expression, evaluates it and returns its value. How do I extract C values from a Python object? ------------------------------------------------------ That depends on the object's type. If it's a tuple, ``PyTupleSize(o)`` returns its length and ``PyTuple_GetItem(o, i)`` returns its i'th item. Lists have similar functions, ``PyListSize(o)`` and ``PyList_GetItem(o, i)``. For strings, ``PyString_Size(o)`` returns its length and ``PyString_AsString(o)`` a pointer to its value. Note that Python strings may contain null bytes so C's ``strlen()`` should not be used. To test the type of an object, first make sure it isn't NULL, and then use ``PyString_Check(o)``, ``PyTuple_Check(o)``, ``PyList_Check(o)``, etc. There is also a high-level API to Python objects which is provided by the so-called 'abstract' interface -- read ``Include/abstract.h`` for further details. It allows interfacing with any kind of Python sequence using calls like ``PySequence_Length()``, ``PySequence_GetItem()``, etc.) as well as many other useful protocols. How do I use Py_BuildValue() to create a tuple of arbitrary length? -------------------------------------------------------------------------- You can't. Use ``t = PyTuple_New(n)`` instead, and fill it with objects using ``PyTuple_SetItem(t, i, o)`` -- note that this "eats" a reference count of ``o``, so you have to ``Py_INCREF`` it. Lists have similar functions ``PyList_New(n)`` and ``PyList_SetItem(l, i, o)``. Note that you *must* set all the tuple items to some value before you pass the tuple to Python code -- ``PyTuple_New(n)`` initializes them to NULL, which isn't a valid Python value. How do I call an object's method from C? ----------------------------------------------- The ``PyObject_CallMethod()`` function can be used to call an arbitrary method of an object. The parameters are the object, the name of the method to call, a format string like that used with ``Py_BuildValue()``, and the argument values:: PyObject * PyObject_CallMethod(PyObject *object, char *method_name, char *arg_format, ...); This works for any object that has methods -- whether built-in or user-defined. You are responsible for eventually ``Py_DECREF``'ing the return value. To call, e.g., a file object's "seek" method with arguments 10, 0 (assuming the file object pointer is "f"):: res = PyObject_CallMethod(f, "seek", "(ii)", 10, 0); if (res == NULL) { ... an exception occurred ... } else { Py_DECREF(res); } Note that since ``PyObject_CallObject()`` *always* wants a tuple for the argument list, to call a function without arguments, pass "()" for the format, and to call a function with one argument, surround the argument in parentheses, e.g. "(i)". How do I catch the output from PyErr_Print() (or anything that prints to stdout/stderr)? ----------------------------------------------------------------------------------------------- In Python code, define an object that supports the ``write()`` method. Assign this object to ``sys.stdout`` and ``sys.stderr``. Call print_error, or just allow the standard traceback mechanism to work. Then, the output will go wherever your ``write()`` method sends it. The easiest way to do this is to use the StringIO class in the standard library. Sample code and use for catching stdout:: >>> class StdoutCatcher: ... def __init__(self): ... self.data = '' ... def write(self, stuff): ... self.data = self.data + stuff ... >>> import sys >>> sys.stdout = StdoutCatcher() >>> print 'foo' >>> print 'hello world!' >>> sys.stderr.write(sys.stdout.data) foo hello world! How do I access a module written in Python from C? --------------------------------------------------------- You can get a pointer to the module object as follows:: module = PyImport_ImportModule("<modulename>"); If the module hasn't been imported yet (i.e. it is not yet present in ``sys.modules``), this initializes the module; otherwise it simply returns the value of ``sys.modules["<modulename>"]``. Note that it doesn't enter the module into any namespace -- it only ensures it has been initialized and is stored in ``sys.modules``. You can then access the module's attributes (i.e. any name defined in the module) as follows:: attr = PyObject_GetAttrString(module, "<attrname>"); Calling ``PyObject_SetAttrString()`` to assign to variables in the module also works. How do I interface to C++ objects from Python? ------------------------------------------------------ Depending on your requirements, there are many approaches. To do this manually, begin by reading `the "Extending and Embedding" document <http://www.python.org/doc/ext/>`_. Realize that for the Python run-time system, there isn't a whole lot of difference between C and C++ -- so the strategy of building a new Python type around a C structure (pointer) type will also work for C++ objects. For C++ libraries, you can look at `SIP <http://www.riverbankcomputing.co.uk/sip/>`_, `CXX <http://cxx.sourceforge.net/>`_, `Boost <http://www.boost.org/libs/python/doc/index.html>`_, or `Weave <http://www.scipy.org/site_content/weave>`_. `SWIG <http://www.swig.org>`_ is a similar automated tool that only supports C libraries. I added a module using the Setup file and the make fails; why? ---------------------------------------------------------------------- Setup must end in a newline, if there is no newline there, the build process fails. (Fixing this requires some ugly shell script hackery, and this bug is so minor that it doesn't seem worth the effort.) How do I debug an extension? ------------------------------------ When using GDB with dynamically loaded extensions, you can't set a breakpoint in your extension until your extension is loaded. In your ``.gdbinit`` file (or interactively), add the command:: br _PyImport_LoadDynamicModule Then, when you run GDB:: $ gdb /local/bin/python gdb) run myscript.py gdb) continue # repeat until your extension is loaded gdb) finish # so that your extension is loaded gdb) br myfunction.c:50 gdb) continue I want to compile a Python module on my Linux system, but some files are missing. Why? ------------------------------------------------------------------------------------------------- Most packaged versions of Python don't include the /usr/lib/python2.x/config/ directory, which contains various files required for compiling Python extensions. For Red Hat, install the python-devel RPM to get the necessary files. For Debian, run ``apt-get install python-devel``. What does "SystemError: _PyImport_FixupExtension: module yourmodule not loaded" mean? ------------------------------------------------------------------------------------------------------- This means that you have created an extension module named "yourmodule", but your module init function does not initialize with that name. Every module init function will have a line similar to:: module = Py_InitModule("yourmodule", yourmodule_functions); If the string passed to this function is not the same name as your extenion module, the ``SystemError`` exception will be raised. How do I tell "incomplete input" from "invalid input"? -------------------------------------------------------------------------------- Sometimes you want to emulate the Python interactive interpreter's behavior, where it gives you a continuation prompt when the input is incomplete (e.g. you typed the start of an "if" statement or you didn't close your parentheses or triple string quotes), but it gives you a syntax error message immediately when the input is invalid. In Python you can use the ``codeop`` module, which approximates the parser's behavior sufficiently. IDLE uses this, for example. The easiest way to do it in C is to call ``PyRun_InteractiveLoop()`` (perhaps in a separate thread) and let the Python interpreter handle the input for you. You can also set the ``PyOS_ReadlineFunctionPointer`` to point at your custom input function. See ``Modules/readline.c`` and ``Parser/myreadline.c`` for more hints. However sometimes you have to run the embedded Python interpreter in the same thread as your rest application and you can't allow the ``PyRun_InteractiveLoop()`` to stop while waiting for user input. The one solution then is to call ``PyParser_ParseString()`` and test for ``e.error`` equal to ``E_EOF``, which means the input is incomplete). Here's a sample code fragment, untested, inspired by code from Alex Farber:: #include <Python.h> #include <node.h> #include <errcode.h> #include <grammar.h> #include <parsetok.h> #include <compile.h> int testcomplete(char *code) /* code should end in \n */ /* return -1 for error, 0 for incomplete, 1 for complete */ { node *n; perrdetail e; n = PyParser_ParseString(code, &_PyParser_Grammar, Py_file_input, &e); if (n == NULL) { if (e.error == E_EOF) return 0; return -1; } PyNode_Free(n); return 1; } Another solution is trying to compile the received string with ``Py_CompileString()``. If it compiles without errors, try to execute the returned code object by calling ``PyEval_EvalCode()``. Otherwise save the input for later. If the compilation fails, find out if it's an error or just more input is required - by extracting the message string from the exception tuple and comparing it to the string "unexpected EOF while parsing". Here is a complete example using the GNU readline library (you may want to ignore SIGINT while calling readline()):: #include <stdio.h> #include <readline.h> #include <Python.h> #include <object.h> #include <compile.h> #include <eval.h> int main (int argc, char* argv[]) { int i, j, done = 0; /* lengths of line, code */ char ps1[] = ">>> "; char ps2[] = "... "; char *prompt = ps1; char *msg, *line, *code = NULL; PyObject *src, *glb, *loc; PyObject *exc, *val, *trb, *obj, *dum; Py_Initialize (); loc = PyDict_New (); glb = PyDict_New (); PyDict_SetItemString (glb, "__builtins__", PyEval_GetBuiltins ()); while (!done) { line = readline (prompt); if (NULL == line) /* CTRL-D pressed */ { done = 1; } else { i = strlen (line); if (i > 0) add_history (line); /* save non-empty lines */ if (NULL == code) /* nothing in code yet */ j = 0; else j = strlen (code); code = realloc (code, i + j + 2); if (NULL == code) /* out of memory */ exit (1); if (0 == j) /* code was empty, so */ code[0] = '\0'; /* keep strncat happy */ strncat (code, line, i); /* append line to code */ code[i + j] = '\n'; /* append '\n' to code */ code[i + j + 1] = '\0'; src = Py_CompileString (code, "<stdin>", Py_single_input); if (NULL != src) /* compiled just fine - */ { if (ps1 == prompt || /* ">>> " or */ '\n' == code[i + j - 1]) /* "... " and double '\n' */ { /* so execute it */ dum = PyEval_EvalCode ((PyCodeObject *)src, glb, loc); Py_XDECREF (dum); Py_XDECREF (src); free (code); code = NULL; if (PyErr_Occurred ()) PyErr_Print (); prompt = ps1; } } /* syntax error or E_EOF? */ else if (PyErr_ExceptionMatches (PyExc_SyntaxError)) { PyErr_Fetch (&exc, &val, &trb); /* clears exception! */ if (PyArg_ParseTuple (val, "sO", &msg, &obj) && !strcmp (msg, "unexpected EOF while parsing")) /* E_EOF */ { Py_XDECREF (exc); Py_XDECREF (val); Py_XDECREF (trb); prompt = ps2; } else /* some other syntax error */ { PyErr_Restore (exc, val, trb); PyErr_Print (); free (code); code = NULL; prompt = ps1; } } else /* some non-syntax error */ { PyErr_Print (); free (code); code = NULL; prompt = ps1; } free (line); } } Py_XDECREF(glb); Py_XDECREF(loc); Py_Finalize(); exit(0); } How do I find undefined g++ symbols __builtin_new or __pure_virtual? ----------------------------------------------------------------------------------- To dynamically load g++ extension modules, you must recompile Python, relink it using g++ (change LINKCC in the python Modules Makefile), and link your extension module using g++ (e.g., "g++ -shared -o mymodule.so mymodule.o"). Can I create an object class with some methods implemented in C and others in Python (e.g. through inheritance)? ----------------------------------------------------------------------------------------------------------------------------------------------------- In Python 2.2, you can inherit from builtin classes such as int, list, dict, etc. The Boost Python Library (BPL, http://www.boost.org/libs/python/doc/index.html) provides a way of doing this from C++ (i.e. you can inherit from an extension class written in C++ using the BPL). When importing module X, why do I get "undefined symbol: PyUnicodeUCS2*"? -------------------------------------------------------------------------------------------------- You are using a version of Python that uses a 4-byte representation for Unicode characters, but some C extension module you are importing was compiled using a Python that uses a 2-byte representation for Unicode characters (the default). If instead the name of the undefined symbol starts with ``PyUnicodeUCS4``, the problem is the reverse: Python was built using 2-byte Unicode characters, and the extension module was compiled using a Python with 4-byte Unicode characters. This can easily occur when using pre-built extension packages. RedHat Linux 7.x, in particular, provided a "python2" binary that is compiled with 4-byte Unicode. This only causes the link failure if the extension uses any of the ``PyUnicode_*()`` functions. It is also a problem if an extension uses any of the Unicode-related format specifiers for ``Py_BuildValue`` (or similar) or parameter specifications for ``PyArg_ParseTuple()``. You can check the size of the Unicode character a Python interpreter is using by checking the value of sys.maxunicode:: >>> import sys >>> if sys.maxunicode > 65535: ... print 'UCS4 build' ... else: ... print 'UCS2 build' The only way to solve this problem is to use extension modules compiled with a Python binary built using the same size for Unicode characters.

1 0

Python Programming FAQ
by amk＠nyman.amk.ca 16 Aug '03

16 Aug '03

Here's another one of the new FAQ documents, about basic Python programming and data types. --amk ==================================== Programming FAQ ==================================== :Date: $Date: 2003/08/14 20:49:08 $ :Version: $Revision: 1.8 $ :Web site: http://www.python.org/ .. contents:: .. sectnum:: General Questions =========================== Is there a source code level debugger with breakpoints, single-stepping, etc.? ------------------------------------------------------------------------------- Yes. The pdb module is a simple but adequate console-mode debugger for Python. It is part of the standard Python library, and is `documented in the Library Reference Manual <http://www.python.org/doc/current/lib/module-pdb.html>`_. You can also write your own debugger by using the code for pdb as an example. The IDLE interactive development environment, which is part of the standard Python distribution (normally available as Tools/scripts/idle), includes a graphical debugger. There is documentation for the IDLE debugger at http://www.python.org/idle/doc/idle2.html#Debugger PythonWin is a Python IDE that includes a GUI debugger based on pdb. The Pythonwin debugger colors breakpoints and has quite a few cool features such as debugging non-Pythonwin programs. A reference can be found at http://www.python.org/ftp/python/pythonwin/pwindex.html More recent versions of PythonWin are available as a part of the ActivePython distribution (see http://www.activestate.com/Products/ActivePython/index.html). Pydb is a version of the standard Python debugger pdb, modified for use with DDD (Data Display Debugger), a popular graphical debugger front end. Pydb can be found at http://packages.debian.org/unstable/devel/pydb.html> and DDD can be found at http://www.gnu.org/software/ddd. There are a number of commmercial Python IDEs that include graphical debuggers. They include: * Wing IDE (http://wingide.com) * Komodo IDE (http://www.activestate.com/Products/Komodo) Is there a tool to help find bugs or perform static analysis? ---------------------------------------------------------------------- Yes. PyChecker is a static analysis tool that finds bugs in Python source code and warns about code complexity and style. You can get PyChecker from http://pychecker.sf.net. How can I create a stand-alone binary from a Python script? ------------------------------------------------------------------- You don't need the ability to compile Python to C code, if all you want is a stand-alone program that users can download and run without having to install the Python distribution first. There are a number of tools that determine the set of modules required by a program and bind these modules together with a Python binary to produce a single executable. One is to use the freeze tool, which is included in the Python source tree as ``Tools/freeze``. It converts Python byte code to C arrays; a C compiler you can embed all your modules into a new program, which is then linked with the standard Python modules. It works by scanning your source recursively for import statements (in both forms) and looking for the modules in the standard Python path as well as in the source directory (for built-in modules). It then turns the bytecode for modules written in Python into C code (array initializers that can be turned into code objects using the marshal module) and creates a custom-made config file that only contains those built-in modules which are actually used in the program. It then compiles the generated C code and links it with the rest of the Python interpreter to form a self-contained binary which acts exactly like your script. Obviously, freeze requires a C compiler. There are several other utilities which don't. The first is Gordon McMillan's installer at http://www.mcmillan-inc.com/install1.html which works on Windows, Linux and at least some forms of Unix. Another is Thomas Heller's py2exe (Windows only) at http://starship.python.net/crew/theller/py2exe A third is Christian Tismer's `SQFREEZE <http://starship.python.net/crew/pirx>`_ which appends the byte code to a specially-prepared Python interpreter that can find the byte code in the executable. A fourth is Fredrik Lundh's `Squeeze <http://www.pythonware.com/products/python/squeeze>`_. Are there coding standards or a style guide for Python programs? ------------------------------------------------------------------------ Yes. The coding style required for standard library modules is documented as `PEP 8 <http://www.python.org/peps/pep-0008.html>`_. My program is too slow. How do I speed it up? ---------------------------------------------------- That's a tough one, in general. There are many tricks to speed up Python code; consider rewriting parts in C as a last resort. One thing to notice is that function and (especially) method calls are rather expensive; if you have designed a purely OO interface with lots of tiny functions that don't do much more than get or set an instance variable or call another method, you might consider using a more direct way such as directly accessing instance variables. Also see the standard module "profile" (`described in the Library Reference manual <http://www.python.org/doc/current/lib/module-profile.html>`_) which makes it possible to find out where your program is spending most of its time (if you have some patience -- the profiling itself can slow your program down by an order of magnitude). Remember that many standard optimization heuristics you may know from other programming experience may well apply to Python. For example it may be faster to send output to output devices using larger writes rather than smaller ones in order to reduce the overhead of kernel system calls. Thus CGI scripts that write all output in "one shot" may be faster than those that write lots of small pieces of output. Also, be sure to use Python's core features where appropriate. For example, slicing allows programs to chop up lists and other sequence objects in a single tick of the interpreter's mainloop using highly optimized C implementations. Thus to get the same effect as:: L2 = [] for i in range[3]: L2.append(L1[i]) it is much shorter and far faster to use :: L2 = list(L1[:3]) # "list" is redundant if L1 is a list. Note that the functionally-oriented builtins such as ``map()``, ``zip()``, and friends can be a convenient accelerator for loops that perform a single task. For example to pair the elements of two lists together:: >>> zip([1,2,3], [4,5,6]) [(1, 4), (2, 5), (3, 6)] or to compute a number of sines:: >>> map( math.sin, (1,2,3,4)) [0.841470984808, 0.909297426826, 0.14112000806, -0.756802495308] The operation completes very quickly in such cases. Other examples include the ``join()`` and ``split()`` methods of string objects. For example if s1..s7 are large (10K+) strings then ``"".join([s1,s2,s3,s4,s5,s6,s7])` may be far faster than the more obvious ``s1+s2+s3+s4+s5+s6+s7``, since the "summation" will compute many subexpressions, whereas ``join()`` does all the copying in one pass. For manipulating strings, use the ``replace()`` method on string objects. Use regular expressions only when you're not dealing with constant string patterns. Consider using the string formatting operations ``string % tuple`` and ``string % dictionary``. Be sure to use the ``list.sort()`` builtin method to do sorting, and see the `sorting mini-HOWTO <http://www.amk.ca/python/howto/sorting/XXX>`_ for examples of moderately advanced usage. ``list.sort()`` beats other techniques for sorting in all but the most extreme circumstances. Another common trick is to "push loops into functions or methods." For example suppose you have a program that runs slowly and you use the profiler to determine that a Python function ``ff()`` is being called lots of times. If you notice that ``ff ()``:: def ff(x): ...do something with x computing result... return result tends to be called in loops like:: list = map(ff, oldlist) or:: for x in sequence: value = ff(x) ...do something with value... then you can often eliminate function call overhead by rewriting ``ff()`` to:: def ffseq(seq): resultseq = [] for x in seq: ...do something with x computing result... resultseq.append(result) return resultseq and rewrite the two examples to ``list = ffseq(oldlist)`` and to:: for value in ffseq(sequence): ...do something with value... Single calls to ff(x) translate to ffseq([x])[0] with little penalty. Of course this technique is not always appropriate and there are other variants which you can figure out. You can gain some performance by explicitly storing the results of a function or method lookup into a local variable. A loop like:: for key in token: dict[key] = dict.get(key, 0) + 1 resolves dict.get every iteration. If the method isn't going to change, a slightly faster implementation is:: dict_get = dict.get # look up the method once for key in token: dict[key] = dict_get(key, 0) + 1 Default arguments can be used to determine values once, at compile time instead of at run time. This can only be done for functions or objects which will not be changed during program execution, such as replacing :: def degree_sin(deg): return math.sin(deg * math.pi / 180.0) with :: def degree_sin(deg, factor = math.pi/180.0, sin = math.sin): return sin(deg * factor) Because this trick uses default arguments for terms which should not be changed, it should only be used when you are not concerned with presenting a possibly confusing API to your users. Don't bother applying these optimization tricks until you know you need them, after profiling has indicated that a particular function is the heavily executed hot spot in the code. Optimizations almost always make the code less clear, and you shouldn't pay the costs of reduced clarity (increased development time, greater likelihood of bugs) unless the resulting performance benefit is worth it. For an anecdote related to optimization, see http://www.python.org/doc/essays/list2str.html. Core Language ================== How do you set a global variable in a function? ---------------------------------------------------------- Did you do something like this? :: x = 1 # make a global def f(): print x # try to print the global ... for j in range(100): if q>3: x=4 Any variable assigned in a function is local to that function. unless it is specifically declared global. Since a value is bound to ``x`` as the last statement of the function body, the compiler assumes that ``x`` is local. Consequently the ``print x`` attempts to print an uninitialized local variable and will trigger a ``NameError``. The solution is to insert an explicit global declaration at the start of the function:: def f(): global x print x # try to print the global ... for j in range(100): if q>3: x=4 In this case, all references to ``x`` are interpreted as references to the ``x`` from the module namespace. What are the rules for local and global variables in Python? -------------------------------------------------------------------------- In Python, variables that are only referenced inside a function are implicitly global. If a variable is assigned a new value anywhere within the function's body, it's assumed to be a local. If a variable is ever assigned a new value inside the function, the variable is implicitly local, and you need to explicitly declare it as 'global'. Though a bit surprising at first, a moment's consideration explains this. On one hand, requiring ``global`` for assigned variables provides a bar against unintended side-effects. On the other hand, if ``global`` was required for all global references, you'd be using ``global`` all the time. You'd have to declare as global every reference to a builtin function or to a component of an imported module. This clutter would defeat the usefulness of the ``global`` declaration for identifying side-effects. How do I share global variables across modules? ------------------------------------------------ The canonical way to share information across modules within a single program is to create a special module (often called config or cfg). Just import the config module in all modules of your application; the module then becomes available as a global name. Because there is only one instance of each module, any changes made to the module object get reflected everywhere. For example: config.py:: x = 0 # Default value of the 'x' configuration setting mod.py:: import config config.x = 1 main.py:: import config import mod print config.x Note that using a module is also the basis for implementing the Singleton design pattern, for the same reason. What are the "best practices" for using import in a module? ------------------------------------------------------------------------------ In general, don't use ``from modulename import *``. Doing so clutters the importer's namespace. Some people avoid this idiom even with the few modules that were designed to be imported in this manner. Modules designed in this manner include ``Tkinter``, ``threading``, and ``wxPython``. Import modules at the top of a file. Doing so makes it clear what other modules your code requires and avoids questions of whether the module name is in scope. Using one import per line makes it easy to add and delete module imports, but using multiple imports per line uses less screen space. It's good practice if you import modules in the following order: 1. standard libary modules -- e.g. ``sys``, ``os``, ``getopt``, ``re``) 2. third-party library modules (anything installed in Python's site-packages directory) -- e.g. mx.DateTime, ZODB, PIL.Image, etc. 3. locally-developed modules Never use relative package imports. If you're writing code that's in the ``package.sub.m1`` module and want to import ``package.sub.m2``, do not just write ``import m2``, even though it's legal. Write ``from package.sub import m2`` instead. Relative imports can lead to a module being initialized twice, leading to confusing bugs. It is sometimes necessary to move imports to a function or class to avoid problems with circular imports. Gordon McMillan says: Circular imports are fine where both modules use the "import <module>" form of import. They fail when the 2nd module wants to grab a name out of the first ("from module import name") and the import is at the top level. That's because names in the 1st are not yet available, because the first module is busy importing the 2nd. In this case, if the second module is only used in one function, then the import can easily be moved into that function. By the time the import is called, the first module will have finished initializing, and the second module can do its import. It may also be necessary to move imports out of the top level of code if some of the modules are platform-specific. In that case, it may not even be possible to import all of the modules at the top of the file. In this case, importing the correct modules in the corresponding platform-specific code is a good option. Only move imports into a local scope, such as inside a function definition, if it's necessary to solve a problem such as avoiding a circular import or are trying to reduce the initialization time of a module. This technique is especially helpful if many of the imports are unnecessary depending on how the program executes. You may also want to move imports into a function if the modules are only ever used in that function. Note that loading a module the first time may be expensive because of the one time initialization of the module, but loading a module multiple times is virtually free, costing only a couple of dictionary lookups. Even if the module name has gone out of scope, the module is probably available in sys.modules. If only instances of a specific class use a module, then it is reasonable to import the module in the class's ``__init__`` method and then assign the module to an instance variable so that the module is always available (via that instance variable) during the life of the object. Note that to delay an import until the class is instantiated, the import must be inside a method. Putting the import inside the class but outside of any method still causes the import to occur when the module is initialized. How can I pass optional or keyword parameters from one function to another? ------------------------------------------------------------------------------- Collect the arguments using the ``*`` and ``**`` specifiers in the function's parameter list; this gives you the positional arguments as a tuple and the keyword arguments as a dictionary. You can then pass these arguments when calling another function by using ``*`` and ``**``:: def f(x, *tup, **kwargs): ... kwargs['width']='14.3c' ... g(x, *tup, **kwargs) In the unlikely case that you care about Python versions older than 2.0, use 'apply':: def f(x, *tup, **kwargs): ... kwargs['width']='14.3c' ... apply(g, (x,)+tup, kwargs) How do I write a function with output parameters (call by reference)? ----------------------------------------------------------------------------- Remember that arguments are passed by assignment in Python. Since assignment just creates references to objects, there's no alias between an argument name in the caller and callee, and so no call-by-reference per se. You can achieve the desired effect in a number of ways. 1) By returning a tuple of the results:: def func2(a, b): a = 'new-value' # a and b are local names b = b + 1 # assigned to new objects return a, b # return new values x, y = 'old-value', 99 x, y = func2(x, y) print x, y # output: new-value 100 This is almost always the clearest solution. 2) By using global variables. This isn't thread-safe, and is not recommended. 3) By passing a mutable (changeable in-place) object:: def func1(a): a[0] = 'new-value' # 'a' references a mutable list a[1] = a[1] + 1 # changes a shared object args = ['old-value', 99] func1(args) print args[0], args[1] # output: new-value 100 4) By passing in a dictionary that gets mutated:: def func3(args): args['a'] = 'new-value' # args is a mutable dictionary args['b'] = args['b'] + 1 # change it in-place args = {'a':' old-value', 'b': 99} func3(args) print args['a'], args['b'] 5) Or bundle up values in a class instance:: class callByRef: def __init__(self, **args): for (key, value) in args.items(): setattr(self, key, value) def func4(args): args.a = 'new-value' # args is a mutable callByRef args.b = args.b + 1 # change object in-place args = callByRef(a='old-value', b=99) func4(args) print args.a, args.b There's almost never a good reason to get this complicated. Your best choice is to return a tuple containing the multiple results. How do you make a higher order function in Python? ---------------------------------------------------------- You have two choices: you can use nested scopes or you can use callable objects. For example, suppose you wanted to define ``linear(a,b)`` which returns a function ``f(x)`` that computes the value ``a*x+b``. Using nested scopes:: def linear(a,b): def result(x): return a*x + b return result Or using a callable object:: class linear: def __init__(self, a, b): self.a, self.b = a,b def __call__(self, x): return self.a * x + self.b In both cases:: taxes = linear(0.3,2) gives a callable object where taxes(10e6) == 0.3 * 10e6 + 2. The callable object approach has the disadvantage that it is a bit slower and results in slightly longer code. However, note that a collection of callables can share their signature via inheritance:: class exponential(linear): # __init__ inherited def __call__(self, x): return self.a * (x ** self.b) Object can encapsulate state for several methods:: class counter: value = 0 def set(self, x): self.value = x def up(self): self.value=self.value+1 def down(self): self.value=self.value-1 count = counter() inc, dec, reset = count.up, count.down, count.set Here ``inc()``, ``dec()`` and ``reset()`` act like functions which share the same counting variable. How do I copy an object in Python? ------------------------------------------ In general, try copy.copy() or copy.deepcopy() for the general case. Not all objects can be copied, but most can. Some objects can be copied more easily. Dictionaries have a ``copy()`` method:: newdict = olddict.copy() Sequences can be copied by slicing:: new_l = l[:] How can I find the methods or attributes of an object? -------------------------------------------------------------- For an instance x of a user-defined class, ``dir(x)`` returns an alphabetized list of the names containing the instance attributes and methods and attributes defined by its class. How can my code discover the name of an object? ------------------------------------------------------- Generally speaking, it can't, because objects don't really have names. Essentially, assignment always binds a name to a value; The same is true of ``def`` and ``class`` statements, but in that case the value is a callable. Consider the following code:: class A: pass B = A a = B() b = a print b <__main__.A instance at 016D07CC> print a <__main__.A instance at 016D07CC> Arguably the class has a name: even though it is bound to two names and invoked through the name B the created instance is still reported as an instance of class A. However, it is impossible to say whether the instance's name is a or b, since both names are bound to the same value. Generally speaking it should not be necessary for your code to "know the names" of particular values. Unless you are deliberately writing introspective programs, this is usually an indication that a change of approach might be beneficial. In comp.lang.python, Fredrik Lundh once gave an excellent analogy in answer to this question: The same way as you get the name of that cat you found on your porch: the cat (object) itself cannot tell you its name, and it doesn't really care -- so the only way to find out what it's called is to ask all your neighbours (namespaces) if it's their cat (object)... ....and don't be surprised if you'll find that it's known by many names, or no name at all! Is there an equivalent of C's "?:" ternary operator? ---------------------------------------------------------------------- No. In many cases you can mimic a?b:c with "a and b or c", but there's a flaw: if b is zero (or empty, or None -- anything that tests false) then c will be selected instead. In many cases you can prove by looking at the code that this can't happen (e.g. because b is a constant or has a type that can never be false), but in general this can be a problem. Tim Peters (who wishes it was Steve Majewski) suggested the following solution: (a and [b] or [c])[0]. Because [b] is a singleton list it is never false, so the wrong path is never taken; then applying [0] to the whole thing gets the b or c that you really wanted. Ugly, but it gets you there in the rare cases where it is really inconvenient to rewrite your code using 'if'. The best course is usually to write a simple ``if...else`` statement. Another solution is to implement the "?:" operator as a function:: def q(cond,on_true,on_false): if cond: if not isfunction(on_true): return on_true else: return apply(on_true) else: if not isfunction(on_false): return on_false else: return apply(on_false) In most cases you'll pass b and c directly: ``q(a,b,c)``. To avoid evaluating b or c when they shouldn't be, encapsulate them within a lambda function, e.g.: ``q(a,lambda: b, lambda: c)``. It has been asked *why* Python has no if-then-else expression. There are several answers: many languages do just fine without one; it can easily lead to less readable code; no sufficiently "Pythonic" syntax has been discovered; a search of the standard library found remarkably few places where using an if-then-else expression would make the code more understandable. In 2002, `PEP 308 <http://www.python.org/peps/pep-0308.html>`_ was written proposing several possible syntaxes and the community was asked to vote on the issue. The vote was inconclusive. Most people liked one of the syntaxes, but also hated other syntaxes; many votes implied that people preferred no ternary operator rather than having a syntax they hated. Is it possible to write obfuscated one-liners in Python? ---------------------------------------------------------------- Yes. Usually this is done by nesting `lambda` within `lambda`. See the following three examples, due to Ulf Bartelt:: # Primes < 1000 print filter(None,map(lambda y:y*reduce(lambda x,y:x*y!=0, map(lambda x,y=y:y%x,range(2,int(pow(y,0.5)+1))),1),range(2,1000))) # First 10 Fibonacci numbers print map(lambda x,f=lambda x,f:(x<=1) or (f(x-1,f)+f(x-2,f)): f(x,f), range(10)) # Mandelbrot set print (lambda Ru,Ro,Iu,Io,IM,Sx,Sy:reduce(lambda x,y:x+y,map(lambda y, Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,Sy=Sy,L=lambda yc,Iu=Iu,Io=Io,Ru=Ru,Ro=Ro,i=IM, Sx=Sx,Sy=Sy:reduce(lambda x,y:x+y,map(lambda x,xc=Ru,yc=yc,Ru=Ru,Ro=Ro, i=i,Sx=Sx,F=lambda xc,yc,x,y,k,f=lambda xc,yc,x,y,k,f:(k<=0)or (x*x+y*y >=4.0) or 1+f(xc,yc,x*x-y*y+xc,2.0*x*y+yc,k-1,f):f(xc,yc,x,y,k,f):chr( 64+F(Ru+x*(Ro-Ru)/Sx,yc,0,0,i)),range(Sx))):L(Iu+y*(Io-Iu)/Sy),range(Sy ))))(-2.1, 0.7, -1.2, 1.2, 30, 80, 24) # \___ ___ \___ ___ | | |__ lines on screen # V V | |______ columns on screen # | | |__________ maximum of "iterations" # | |_________________ range on y axis # |____________________________ range on x axis Don't try this at home, kids! Numbers and strings ========================== How do I specify hexadecimal and octal integers? -------------------------------------------------------- To specify an octal digit, precede the octal value with a zero. For example, to set the variable "a" to the octal value "10" (8 in decimal), type:: >>> a = 010 >>> a 8 Hexadecimal is just as easy. Simply precede the hexadecimal number with a zero, and then a lower or uppercase "x". Hexadecimal digits can be specified in lower or uppercase. For example, in the Python interpreter:: >>> a = 0xa5 >>> a 165 >>> b = 0XB2 >>> b 178 How do I convert a string to a number? ---------------------------------------------- For integers, use the built-in ``int()`` type constructor, e.g. int('144') == 144. Similarly, ``float()`` converts to floating-point, e.g. ``float('144') == 144.0``. By default, these interpret the number as decimal, so that ``int('0144') == 144`` and ``int('0x144')`` raises ``ValueError``. ``int(string, base)`` takes the base to convert from as a second optional argument, so ``int('0x144', 16) == 324``. If the base is specified as 0, the number is interpreted using Python's rules: a leading '0' indicates octal, and '0x' indicates a hex number. Do not use the built-in function ``eval()`` if all you need is to convert strings to numbers. ``eval()`` will be significantly slower and it presents a security risk: someone could pass you a Python expression that might have unwanted side effects. For example, someone could pass ``__import__('os').system("rm -rf $HOME")`` which would erase your home directory. ``eval()`` also has the effect of interpreting numbers as Python expressions, so that e.g. eval('09') gives a syntax error because Python regards numbers starting with '0' as octal (base 8). How do I convert a number to a string? ---------------------------------------------- To convert, e.g., the number 144 to the string '144', use the built-in function ``str()``. If you want a hexadecimal or octal representation, use the built-in functions ``hex()`` or ``oct()``. For fancy formatting, use `the % operator <http://www.python.org/doc/lib/typesseq-strings.html>`_ on strings, e.g. ``"%04d" % 144`` yields '0144' and ``"%.3f" % (1/3.0)`` yields '0.333'. See the library reference manual for details. How do I modify a string in place? ------------------------------------------ You can't, because strings are immutable. If you need an object with this ability, try converting the string to a list or use the array module:: >>> s = "Hello, world" >>> a = list(s) >>> print a ['H', 'e', 'l', 'l', 'o', ',', ' ', 'w', 'o', 'r', 'l', 'd'] >>> a[7:] = list("there!") >>> ''.join(a) 'Hello, there!' >>> import array >>> a = array.array('c', s) >>> print a array('c', 'Hello, world') >>> a[0] = 'y' ; print a array('c', 'yello world') >>> a.tostring() 'yello, world' How do I use strings to call functions/methods? ---------------------------------------------------------- There are various techniques. * The best is to use a dictionary that maps strings to functions. The primary advantage of this technique is that the strings do not need to match the names of the functions. This is also the primary technique used to emulate a case construct:: def a(): pass def b(): pass dispatch = {'go': a, 'stop': b} # Note lack of parens for funcs dispatch[get_input()]() # Note trailing parens to call function * Use the built-in function ``getattr()``:: import foo getattr(foo, 'bar')() Note that getattr() works on any object, including classes, class instances, modules, and so on. This is used in several places in the standard library, like this:: class Foo: def do_foo(self): ... def do_bar(self): ... f = getattr(foo_instance, 'do_' + opname) f() * Use ``locals()`` or ``eval()`` to resolve the function name:: def myFunc(): print "hello" fname = "myFunc" f = locals()[fname] f() f = eval(fname) f() Note: Using ``eval()`` is slow and dangerous. If you don't have absolute control over the contents of the string, someone could pass a string that resulted in an arbitrary function being executed. Is there an equivalent to Perl's chomp() for removing trailing newlines from strings? -------------------------------------------------------------------------------------------- There are two partial substitutes. If you want to remove all trailing whitespace, use the ``rstrip()`` method of string objects. This removes all trailing whitespace, not just a single newline. Otherwise, if there is only one line in the string ``S``, use ``S.splitlines()[0]``. Is there a scanf() or sscanf() equivalent? -------------------------------------------------- Not as such. For simple input parsing, the easiest approach is usually to split the line into whitespace-delimited words using the ``split()`` method of string objects and then convert decimal strings to numeric values using ``int()`` or ``float()``. ``split()`` supports an optional "sep" parameter which is useful if the line uses something other than whitespace as a separator. For more complicated input parsing, regular expressions more powerful than C's ``sscanf()`` and better suited for the task. What does 'UnicodeError: ASCII [decoding,encoding] error: ordinal not in range(128)' mean? ----------------------------------------------------------------------------------------------------- This error indicates that your Python installation can handle only 7-bit ASCII strings. There are a couple ways to fix or work around the problem. If your programs must handle data in arbitary character set encodings, the environment the application runs in will generally identify the encoding of the data it is handing you. You need to convert the input to Unicode data using that encoding. For example, a program that handles email or web input will typically find character set encoding information in Content-Type headers. This can then be used to properly convert input data to Unicode. Assuming the string referred to by ``value`` is encoded as UTF-8:: value = unicode(value, "utf-8") will return a Unicode object. If the data is not correctly encoded as UTF-8, the above call will raise a ``UnicodeError`` exception. If you only want strings coverted to Unicode which have non-ASCII data, you can try converting them first assuming an ASCII encoding, and then generate Unicode objects if that fails:: try: x = unicode(value, "ascii") except UnicodeError: value = unicode(value, "utf-8") else: # value was valid ASCII data pass It's possible to set a default encoding in a file called ``sitecustomize.py`` that's part of the Python library. However, this isn't recommended because changing the Python-wide default encoding may cause third-party extension modules to fail. Note that on Windows, there is an encoding known as "mbcs", which uses an encoding specific to your current locale. In many cases, and particularly when working with COM, this may be an appropriate default encoding to use. Sequences (Tuples/Lists) ================================= How do I convert between tuples and lists? ------------------------------------------------ The function ``tuple(seq)`` converts any sequence (actually, any iterable) into a tuple with the same items in the same order. For example, ``tuple([1, 2, 3])`` yields ``(1, 2, 3)`` and ``tuple('abc')`` yields ``('a', 'b', 'c')``. If the argument is a tuple, it does not make a copy but returns the same object, so it is cheap to call ``tuple()`` when you aren't sure that an object is already a tuple. The function ``list(seq)`` converts any sequence or iterable into a list with the same items in the same order. For example, ``list((1, 2, 3))`` yields ``[1, 2, 3]`` and ``list('abc')`` yields ``['a', 'b', 'c']``. If the argument is a list, it makes a copy just like ``seq[:]`` would. What's a negative index? -------------------------------------------------------------------- Python sequences are indexed with positive numbers and negative numbers. For positive numbers 0 is the first index 1 is the second index and so forth. For negative indices -1 is the last index and -2 is the pentultimate (next to last) index and so forth. Think of ``seq[-n]`` as the same as ``seq[len(seq)-n]``. Using negative indices can be very convenient. For example ``S[:-1]`` is all of the string except for its last character, which is useful for removing the trailing newline from a string. How do I iterate over a sequence in reverse order? --------------------------------------------------------- If it is a list, the fastest solution is :: list.reverse() try: for x in list: "do something with x" finally: list.reverse() This has the disadvantage that while you are in the loop, the list is temporarily reversed. If you don't like this, you can make a copy. This appears expensive but is actually faster than other solutions:: rev = list[:] rev.reverse() for x in rev: <do something with x> If it's not a list, a more general but slower solution is:: for i in range(len(sequence)-1, -1, -1): x = sequence[i] <do something with x> A more elegant solution, is to define a class which acts as a sequence and yields the elements in reverse order (solution due to Steve Majewski):: class Rev: def __init__(self, seq): self.forw = seq def __len__(self): return len(self.forw) def __getitem__(self, i): return self.forw[-(i + 1)] You can now simply write:: for x in Rev(list): <do something with x> Unfortunately, this solution is slowest of all, due to the method call overhead. How do you remove duplicates from a list? ------------------------------------------------- See the Python Cookbook for a long discussion of many ways to do this: http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52560 If you don't mind reordering the list, sort it and then scan from the end of the list, deleting duplicates as you go:: if List: List.sort() last = List[-1] for i in range(len(List)-2, -1, -1): if last==List[i]: del List[i] else: last=List[i] If all elements of the list may be used as dictionary keys (i.e. they are all hashable) this is often faster :: d = {} for x in List: d[x]=x List = d.values() How do you make an array in Python? ---------------------------------------------------- Use a list:: ["this", 1, "is", "an", "array"] Lists are equivalent to C or Pascal arrays in their time complexity; the primary difference is that a Python list can contain objects of many different types. The ``array`` module also provides methods for creating arrays of fixed types with compact representations, but they are slower to index than lists. Also note that the Numeric extensions and others define array-like structures with various characteristics as well. To get Lisp-style linked lists, you can emulate cons cells using tuples:: lisp_list = ("like", ("this", ("example", None) ) ) If mutability is desired, you could use lists instead of tuples. Here the analogue of lisp car is ``lisp_list[0]`` and the analogue of cdr is ``lisp_list[1]``. Only do this if you're sure you really need to, because it's usually a lot slower than using Python lists. How do I create a multidimensional list? --------------------------------------------------------------- You probably tried to make a multidimensional array like this:: A = [[None] * 2] * 3 This looks correct if you print it:: >>> A [[None, None], [None, None], [None, None]] But when you assign a value, it shows up in multiple places: >>> A[0][0] = 5 >>> A [[5, None], [5, None], [5, None]] The reason is that replicating a list with ``*`` doesn't create copies, it only creates references to the existing objects. The ``*3`` creates a list containing 3 references to the same list of length two. Changes to one row will show in all rows, which is almost certainly not what you want. The suggested approach is to create a list of the desired length first and then fill in each element with a newly created list:: A = [None]*3 for i in range(3): A[i] = [None] * 2 This generates a list containing 3 different lists of length two. You can also use a list comprehension:: w,h = 2,3 A = [ [None]*w for i in range(h) ] Or, you can use an extension that provides a matrix datatype; `Numeric Python <XXX>`_ is the best known. How do I apply a method to a sequence of objects? -------------------------------------------------------------------------- Use a list comprehension:: result = [obj.method() for obj in List] More generically, you can try the following function:: def method_map(objects, method, arguments): """method_map([a,b], "meth", (1,2)) gives [a.meth(1,2), b.meth(1,2)]""" nobjects = len(objects) methods = map(getattr, objects, [method]*nobjects) return map(apply, methods, [arguments]*nobjects) Dictionaries ================== How can I get a dictionary to display its keys in a consistent order? ----------------------------------------------------------------------------- You can't. Dictionaries store their keys in an unpredictable order, so the display order of a dictionary's elements will be similarly unpredictable. This can be frustrating if you want to save a printable version to a file, make some changes and then compare it with some other printed dictionary. In this case, use the ``pprint`` module to pretty-print the dictionary; the items will be presented in order sorted by the key. A more complicated solution is to subclass ``UserDict.UserDict`` to create a ``SortedDict`` class that prints itself in a predictable order. Here's one simpleminded implementation of such a class:: import UserDict, string class SortedDict(UserDict.UserDict): def __repr__(self): result = [] append = result.append keys = self.data.keys() keys.sort() for k in keys: append("%s: %s" % (`k`, `self.data[k]`)) return "{%s}" % string.join(result, ", ") ___str__ = __repr__ This will work for many common situations you might encounter, though it's far from a perfect solution. The largest flaw is that if some values in the dictionary are also dictionaries, their values won't be presented in any particular order. I want to do a complicated sort: can you do a Schwartzian Transform in Python? -------------------------------------------------------------------------------------- Yes, it's quite simple with list comprehensions. The technique, attributed to Randal Schwartz of the Perl community, sorts the elements of a list by a metric which maps each element to its "sort value". To sort a list of strings by their uppercase values:: tmp1 = [ (x.upper(), x) for x in L ] # Schwartzian transform tmp1.sort() Usorted = [ x[1] for x in tmp1 ] To sort by the integer value of a subfield extending from positions 10-15 in each string:: tmp2 = [ (int(s[10:15]), s) for s in L ] # Schwartzian transform tmp2.sort() Isorted = [ x[1] for x in tmp2 ] Note that Isorted may also be computed by :: def intfield(s): return int(s[10:15]) def Icmp(s1, s2): return cmp(intfield(s1), intfield(s2)) Isorted = L[:] Isorted.sort(Icmp) but since this method calls ``intfield()`` many times for each element of L, it is slower than the Schwartzian Transform. How can I sort one list by values from another list? ------------------------------------------------------------ Merge them into a single list of tuples, sort the resulting list, and then pick out the element you want. :: >>> list1 = ["what", "I'm", "sorting", "by"] >>> list2 = ["something", "else", "to", "sort"] >>> pairs = zip(list1, list2) >>> pairs [('what', 'something'), ("I'm", 'else'), ('sorting', 'to'), ('by', 'sort')] >>> pairs.sort() >>> result = [ x[1] for x in pairs ] >>> result ['else', 'sort', 'to', 'something'] An alternative for the last step is:: result = [] for p in pairs: result.append(p[1]) If you find this more legible, you might prefer to use this instead of the final list comprehension. However, it is almost twice as slow for long lists. Why? First, the ``append()`` operation has to reallocate memory, and while it uses some tricks to avoid doing that each time, it still has to do it occasionally, and that costs quite a bit. Second, the expression "result.append" requires an extra attribute lookup, and third, there's a speed reduction from having to make all those function calls. Objects ============= What is a class? ------------------------ A class is the particular object type created by executing a class statement. Class objects are used as templates to create instance objects, which embody both the data (attributes) and code (methods) specific to a datatype. A class can be based on one or more other classes, called its base class(es). It then inherits the attributes and methods of its base classes. This allows an object model to be successively refined by inheritance. You might have a generic ``Mailbox`` class that provides basic accessor methods for a mailbox, and subclasses such as ``MboxMailbox``, ``MaildirMailbox``, ``OutlookMailbox`` that handle various specific mailbox formats. What is a method? ------------------------- A method is a function on some object ``x`` that you normally call as ``x.name(arguments...)``. Methods are defined as functions inside the class definition:: class C: def meth (self, arg): return arg*2 + self.attribute What is self? --------------------- Self is merely a conventional name for the first argument of a method. A method defined as ``meth(self, a, b, c)`` should be called as ``x.meth(a, b, c)`` for some instance ``x`` of the class in which the definition occurs; the called method will think it is called as ``meth(x, a, b, c)``. How do I check if an object is an instance of a given class or of a subclass of it? ------------------------------------------------------------------------------------------- Use the built-in function ``isinstance(obj, cls)``. You can check if an object is an instance of any of a number of classes by providing a tuple instead of a single class, e.g. ``isinstance(obj, (class1, class2, ...))``, and can also check whether an object is one of Python's built-in types, e.g. ``isinstance(obj, str)`` or ``isinstance(obj, (int, long, float, complex))``. Note that most programs do not use ``isinstance()`` on user-defined classes very often. If you are developing the classes yourself, a more proper object-oriented style is to define methods on the classes that encapsulate a particular behaviour, instead of checking the object's class and doing a different thing based on what class it is. For example, if you have a function that does something:: def search (obj): if isinstance(obj, Mailbox): # ... code to search a mailbox elif isinstance(obj, Document): # ... code to search a document elif ... A better approach is to define a ``search()`` method on all the classes and just call it:: class Mailbox: def search(self): # ... code to search a mailbox class Document: def search(self): # ... code to search a document obj.search() What is delegation? --------------------------- Delegation is an object oriented technique (also called a design pattern). Let's say you have an object ``x`` and want to change the behaviour of just one of its methods. You can create a new class that provides a new implementation of the method you're interested in changing and delegates all other methods to the corresponding method of ``x``. Python programmers can easily implement delegation. For example, the following class implements a class that behaves like a file but converts all written data to uppercase:: class UpperOut: def __init__(self, outfile): self.__outfile = outfile def write(self, s): self.__outfile.write(s.upper()) def __getattr__(self, name): return getattr(self.__outfile, name) Here the ``UpperOut`` class redefines the ``write()`` method to convert the argument string to uppercase before calling the underlying ``self.__outfile.write()`` method. All other methods are delegated to the underlying ``self.__outfile`` object. The delegation is accomplished via the ``__getattr__`` method; consult `the language reference <http://www.python.org/doc/ref/attribute-access.html>`_ for more information about controlling attribute access. Note that for more general cases delegation can get trickier. When attributes must be set as well as retrieved, the class must define a ``__settattr__`` method too, and it must do so carefully. The basic implementation of __setattr__ is roughly equivalent to the following:: class X: ... def __setattr__(self, name, value): self.__dict__[name] = value ... Most __setattr__ implementations must modify self.__dict__ to store local state for self without causing an infinite recursion. How do I call a method defined in a base class from a derived class that overrides it? ---------------------------------------------------------------------------------------------- If you're using new-style classes, use the built-in ``super()`` function:: class Derived(Base): def meth (self): super(Derived, self).meth() If you're using classic classes: For a class definition such as ``class Derived(Base): ...`` you can call method ``meth()`` defined in ``Base`` (or one of ``Base``'s base classes) as ``Base.meth(self, arguments...)``. Here, ``Base.meth`` is an unbound method, so you need to provide the ``self`` argument. How can I organize my code to make it easier to change the base class? ------------------------------------------------------------------------------ You could define an alias for the base class, assign the real base class to it before your class definition, and use the alias throughout your class. Then all you have to change is the value assigned to the alias. Incidentally, this trick is also handy if you want to decide dynamically (e.g. depending on availability of resources) which base class to use. Example:: BaseAlias = <real base class> class Derived(BaseAlias): def meth(self): BaseAlias.meth(self) ... How do I create static class data and static class methods? ------------------------------------------------------------------- Static data (in the sense of C++ or Java) is easy; static methods (again in the sense of C++ or Java) are not supported directly. For static data, simply define a class attribute. To assign a new value to the attribute, you have to explicitly use the class name in the assignment:: class C: count = 0 # number of times C.__init__ called def __init__(self): C.count = C.count + 1 def getcount(self): return C.count # or return self.count ``c.count`` also refers to ``C.count`` for any ``c`` such that ``isinstance(c, C)`` holds, unless overridden by ``c`` itself or by some class on the base-class search path from ``c.__class__`` back to ``C``. Caution: within a method of C, an assignment like ``self.count = 42`` creates a new and unrelated instance vrbl named "count" in ``self``'s own dict. Rebinding of a class-static data name must always specify the class whether inside a method or not:: C.count = 314 Static methods are possible when you're using new-style classes:: class C: def static(arg1, arg2, arg3): # No 'self' parameter! ... static = staticmethod(static) However, a far more straightforward way to get the effect of a static method is via a simple module-level function:: def getcount(): return C.count If your code is structured so as to define one class (or tightly related class hierarchy) per module, this supplies the desired encapsulation. How can I overload constructors (or methods) in Python? --------------------------------------------------------------- This answer actually applies to all methods, but the question usually comes up first in the context of constructors. In C++ you'd write :: class C { C() { cout << "No arguments\n"; } C(int i) { cout << "Argument is " << i << "\n"; } } in Python you have to write a single constructor that catches all cases using default arguments. For example:: class C: def __init__(self, i=None): if i is None: print "No arguments" else: print "Argument is", i This is not entirely equivalent, but close enough in practice. You could also try a variable-length argument list, e.g. :: def __init__(self, *args): .... The same approach works for all method definitions. I try to use __spam and I get an error about _SomeClassName__spam. -------------------------------------------------------------------------- Variables with double leading underscore are "mangled" to provide a simple but effective way to define class private variables. Any identifier of the form ``__spam`` (at least two leading underscores, at most one trailing underscore) is textually replaced with ``_classname__spam``, where ``classname`` is the current class name with any leading underscores stripped. This doesn't guarantee privacy: an outside user can still deliberately access the "_classname__spam" attribute, and private values are visible in the object's ``__dict__``. Many Python programmers never bother to use private variable names at all. My class defines __del__ but it is not called when I delete the object. ------------------------------------------------------------------------------- There are several possible reasons for this. The del statement does not necessarily call __del__ -- it simply decrements the object's reference count, and if this reaches zero __del__ is called. If your data structures contain circular links (e.g. a tree where each child has a parent reference and each parent has a list of children) the reference counts will never go back to zero. Once in a while Python runs an algorithm to detect such cycles, but the garbage collector might run some time after the last reference to your data structure vanishes, so your __del__ method may be called at an inconvenient and random time. This is inconvenient if you're trying to reproduce a problem. Worse, the order in which object's __del__ methods are executed is arbitrary. You can run ``gc.collect()`` to force a collection, but there *are* pathological cases where objects will never be collected. Despite the cycle collector, it's still a good idea to define an explicit ``close()`` method on objects to be called whenever you're done with them. The ``close()`` method can then remove attributes that refer to subobjecs. Don't call ``__del__`` directly -- ``__del__`` should call ``close()`` and ``close()`` should make sure that it can be called more than once for the same object. Another way to avoid cyclical references is to use the "weakref" module, which allows you to point to objects without incrementing their reference count. Tree data structures, for instance, should use weak references for their parent and sibling references (if they need them!). If the object has ever been a local variable in a function that caught an expression in an except clause, chances are that a reference to the object still exists in that function's stack frame as contained in the stack trace. Normally, calling ``sys.exc_clear()`` will take care of this by clearing the last recorded exception. Finally, if your __del__ method raises an exception, a warning message is printed to sys.stderr. How do I get a list of all instances of a given class? -------------------------------------------------------------- Python does not keep track of all instances of a class (or of a built-in type). You can program the class's constructor to keep track of all instances by keeping a list of weak references to each instance. Modules ============= How do I create a .pyc file? ------------------------------------- When a module is imported for the first time (or when the source is more recent than the current compiled file) a ``.pyc`` file containing the compiled code should be created in the same directory as the ``.py`` file. One reason that a ``.pyc`` file may not be created is permissions problems with the directory. This can happen, for example, if you develop as one user but run as another, such as if you are testing with a web server. Creation of a .pyc file is automatic if you're importing a module and Python has the ability (permissions, free space, etc...) to write the compiled module back to the directory. Running Python on a top level script is not considered an import and no ``.pyc`` will be created. For example, if you have a top-level module ``abc.py`` that imports another module ``xyz.py``, when you run abc, ``xyz.pyc`` will be created since xyz is imported, but no ``abc.pyc`` file will be created since ``abc.py`` isn't being imported. If you need to create abc.pyc -- that is, to create a .pyc file for a module that is not imported -- you can, using the py_compile and compileall modules. The ``py_compile`` module can manually compile any module. One way is to use the ``compile()`` function in that module interactively:: >>> import py_compile >>> py_compile.compile('abc.py') This will write the ``.pyc`` to the same location as ``abc.py`` (or you can override that with the optional parameter ``cfile``). You can also automatically compile all files in a directory or directories using the ``compileall`` module. You can do it from the shell prompt by running ``compileall.py`` and providing the path of a directory containing Python files to compile:: python compileall.py . How do I find the current module name? --------------------------------------------- A module can find out its own module name by looking at the predefined global variable ``__name__``. If this has the value '__main__', the program is running as a script. Many modules that are usually used by importing them also provide a command-line interface or a self-test, and only execute this code after checking ``__name__``:: def main(): print 'Running test...' ... if __name__ == '__main__': main() How can I have modules that mutually import each other? --------------------------------------------------------------- Suppose you have the following modules: foo.py:: from bar import bar_var foo_var=1 bar.py:: from foo import foo_var bar_var=2 The problem is that the interpreter will perform the following steps: * main imports foo * Empty globals for foo are created * foo is compiled and starts executing * foo imports bar * Empty globals for bar are created * bar is compiled and starts executing * bar imports foo (which is a no-op since there already is a module named foo) * bar.foo_var = foo.foo_var The last step fails, because Python isn't done with interpreting ``foo`` yet and the global symbol dictionary for ``foo`` is still empty. The same thing happens when you use ``import foo``, and then try to access ``foo.foo_var`` in global code. There are (at least) three possible workarounds for this problem. Guido van Rossum recommends avoiding all uses of ``from <module> import ...``, and placing all code inside functions. Initializations of global variables and class variables should use constants or built-in functions only. This means everything from an imported module is referenced as ``<module>.<name>``. Jim Roskind suggests performing steps in the following order in each module: * exports (globals, functions, and classes that don't need imported base classes) * ``import`` statements * active code (including globals that are initialized from imported values). van Rossum doesn't like this approach much because the imports appear in a strange place, but it does work. Matthias Urlichs recommends restructuring your code so that the recursive import is not necessary in the first place. These solutions are not mutually exclusive. __import__('x.y.z') returns <module 'x'>; how do I get z? ----------------------------------------------------------------------- Try:: __import__('x.y.z').y.z For more realistic situations, you may have to do something like :: m = __import__(s) for i in s.split(".")[1:]: m = getattr(m, i) When I edit an imported module and reimport it, the changes don't show up. Why does this happen? -------------------------------------------------------------------------------------------------------------------------------------------- For reasons of efficiency as well as consistency, Python only reads the module file on the first time a module is imported. If it didn't, in a program consisting of many modules where each one imports the same basic module, the basic module would be parsed and re-parsed many times. To force rereading of a changed module, do this:: import modname reload(modname) Warning: this technique is not 100% fool-proof. In particular, modules containing statements like :: from modname import some_objects will continue to work with the old version of the imported objects. If the module contains class definitions, existing class instances will *not* be updated to use the new class definition. This can result in the following paradoxical behaviour:: >>> import cls >>> c = cls.C() # Create an instance of C >>> reload(cls) <module 'cls' from 'cls.pyc'> >>> isinstance(c, cls.C) # isinstance is false?!? False The nature of the problem is made clear if you print out the class objects: >>> c.__class__ <class cls.C at 0x7352a0> >>> cls.C <class cls.C at 0x4198d0>

1 0

ANNOUNCE: KirbyBase 1.3
by Jamey Cribbs 16 Aug '03

16 Aug '03

KirbyBase 1.3 is now available at: http://www.netpromi.com/files/KirbyBase-1.3.zip What is KirbyBase? KirbyBase is a simple, pure-Python, plain-text, flat-file database management system that can be used either embedded in your application or in a client/server, multi-user mode. To find out more about KirbyBase, go to: http://www.netpromi.com/kirbybase.html Changes: Added ability to pass field values to update and insert using a dictionary. Added ability to specify field to sort on and sort direction for the results of a select. Added len method. Fixed bug in validateMatchCriteria where script was not restricting other match criteria if already attempting to match by recno. Fixed bug in validateMatchCriteria where script was not checking to see if pattern argument was an integer when attempting to match by recno. Changed the way field types are handled internally. This should not change any of the api or interfaces, EXCEPT for the getFieldTypes method, which now returns a list of types, instead of a list of strings. I hope this doesn't screw anyone's programs up. Corrected version number to conform to guidelines in distutils documentation.

1 0