(Entries marked with ** were changed within the last 24 hours; entries marked with * were changed within the last 7 days.)
To find out more, the best thing to do is to start reading the tutorial from the documentation set (see a few questions further down).
See also question 1.17 (what is Python good for).
Edit this entry / Log info / Last changed on Mon May 26 16:05:18 1997 by GvR
By now I don't care any more whether you use a Python, some other snake, a foot or 16-ton weight, or a wood rat as a logo for Python!
Edit this entry / Log info / Last changed on Thu Aug 24 00:50:41 2000 by GvR
The source distribution is a gzipped tar file containing the complete C source, LaTeX documentation, Python library modules, example programs, and several useful pieces of freely distributable software. This will compile and run out of the box on most UNIX platforms. (See section 7 for non-UNIX information.)
Older versions of Python are also available from python.org.
Edit this entry / Log info / Last changed on Tue Apr 9 17:06:16 2002 by A.M. Kuchling
The LaTeX source for the documentation is part of the source distribution. If you don't have LaTeX, the latest Python documentation set is available, in various formats like postscript and html, by anonymous ftp - visit the above URL for links to the current versions.
PostScript for a high-level description of Python is in the file nluug-paper.ps (a separate file on the ftp site).
Edit this entry / Log info / Last changed on Wed Jan 21 12:02:55 1998 by Ken Manheimer
USA:
ftp://ftp.python.org/pub/python/ ftp://gatekeeper.dec.com/pub/plan/python/ ftp://ftp.uu.net/languages/python/ ftp://ftp.wustl.edu/graphics/graphics/sgi-stuff/python/ ftp://ftp.sterling.com/programming/languages/python/ ftp://uiarchive.cso.uiuc.edu/pub/lang/python/ ftp://ftp.pht.com/mirrors/python/python/ ftp://ftp.cdrom.com/pub/python/Europe:
ftp://ftp.cwi.nl/pub/python/ ftp://ftp.funet.fi/pub/languages/python/ ftp://ftp.sunet.se/pub/lang/python/ ftp://unix.hensa.ac.uk/mirrors/uunet/languages/python/ ftp://ftp.lip6.fr/pub/python/ ftp://sunsite.cnlab-switch.ch/mirror/python/ ftp://ftp.informatik.tu-muenchen.de/pub/comp/programming/languages/python/Australia:
ftp://ftp.dstc.edu.au/pub/python/
Edit this entry / Log info / Last changed on Wed Mar 24 09:20:49 1999 by A.M. Kuchling
More info about the newsgroup and mailing list, and about other lists, can be found at http://www.python.org/psa/MailingLists.html.
Archives of the newsgroup are kept by Deja News and accessible through the "Python newsgroup search" web page, http://www.python.org/search/search_news.html. This page also contains pointer to other archival collections.
Edit this entry / Log info / Last changed on Wed Jun 23 09:29:36 1999 by GvR
Edit this entry / Log info / Last changed on Fri May 23 14:42:59 1997 by Ken Manheimer
Edit this entry / Log info / Last changed on Tue Jan 2 03:14:08 2001 by Moshe Zadka
You can also search online bookstores for "Python" (and filter out the Monty Python references; or perhaps search for "Python" and "language").
Edit this entry / Log info / Last changed on Mon Aug 5 19:08:49 2002 by amk
Most publications about Python are collected on the Python web site:
http://www.python.org/doc/Publications.htmlIt is no longer recommended to reference this very old article by Python's author:
Guido van Rossum and Jelke de Boer, "Interactively Testing Remote Servers Using the Python Programming Language", CWI Quarterly, Volume 4, Issue 4 (December 1991), Amsterdam, pp 283-303.
Edit this entry / Log info / Last changed on Sat Jul 4 20:52:31 1998 by GvR
Edit this entry / Log info / Last changed on Fri May 23 15:04:05 1997 by Ken Manheimer
Not all releases have bugfix releases. Note that in the past (ending with 1.5.2), micro releases have added significant changes; in fact the changeover from 0.9.9 to 1.0.0 was the first time that either A or B changed!
Alpha, beta and release candidate versions have an additional suffixes. The suffix for an alpha version is "aN" for some small number N, the suffix for a beta version is "bN" for some small number N, and the suffix for a release candidate version is "cN" for some small number N.
Note that (for instance) all versions labeled 2.0aN precede the versions labeled 2.0bN, which precede versions labeled 2.0cN, and those precede 2.0.
As a rule, no changes are made between release candidates and the final release unless there are show-stopper bugs.
You may also find version numbers with a "+" suffix, e.g. "2.2+". These are unreleased versions, built directly from the CVS trunk.
See also the documentation for sys.version, sys.hexversion, and sys.version_info.
Edit this entry / Log info / Last changed on Mon Jan 14 06:34:17 2002 by GvR
You can also access the development version of Python through CVS. See http://sourceforge.net/cvs/?group_id=5470 for details. If you're not familiar with CVS, documents like http://linux.oreillynet.com/pub/a/linux/2002/01/03/cvs_intro.html provide an introduction.
Edit this entry / Log info / Last changed on Mon Jun 3 00:57:08 2002 by Neal Norwitz
In particular, if you honor the copyright rules, it's OK to use Python for commercial use, to sell copies of Python in source or binary form, or to sell products that enhance Python or incorporate Python (or part of it) in some form. I would still like to know about all commercial use of Python!
I had extensive experience with implementing an interpreted language in the ABC group at CWI, and from working with this group I had learned a lot about language design. This is the origin of many Python features, including the use of indentation for statement grouping and the inclusion of very-high-level data types (although the details are all different in Python).
I had a number of gripes about the ABC language, but also liked many of its features. It was impossible to extend the ABC language (or its implementation) to remedy my complaints -- in fact its lack of extensibility was one of its biggest problems. I had some experience with using Modula-2+ and talked with the designers of Modula-3 (and read the M3 report). M3 is the origin of the syntax and semantics used for exceptions, and some other Python features.
I was working in the Amoeba distributed operating system group at CWI. We needed a better way to do system administration than by writing either C programs or Bourne shell scripts, since Amoeba had its own system call interface which wasn't easily accessible from the Bourne shell. My experience with error handling in Amoeba made me acutely aware of the importance of exceptions as a programming language feature.
It occurred to me that a scripting language with a syntax like ABC but with access to the Amoeba system calls would fill the need. I realized that it would be foolish to write an Amoeba-specific language, so I decided that I needed a language that was generally extensible.
During the 1989 Christmas holidays, I had a lot of time on my hand, so I decided to give it a try. During the next year, while still mostly working on it in my own time, Python was used in the Amoeba project with increasing success, and the feedback from colleagues made me add many early improvements.
In February 1991, after just over a year of development, I decided to post to USENET. The rest is in the Misc/HISTORY file.
Edit this entry / Log info / Last changed on Fri May 23 00:06:23 1997 by GvR
The two main reasons to use Python are:
- Portable - Easy to learnThe three main reasons to use Python are:
- Portable - Easy to learn - Powerful standard library(And nice red uniforms.)
And remember, there is no rule six.
Edit this entry / Log info / Last changed on Wed May 28 10:39:21 1997 by GvR
In the area of basic text manipulation core Python (without any non-core extensions) is easier to use and is roughly as fast as just about any language, and this makes Python good for many system administration type tasks and for CGI programming and other application areas that manipulate text and strings and such.
When augmented with standard extensions (such as PIL, COM, Numeric, oracledb, kjbuckets, tkinter, win32api, etc.) or special purpose extensions (that you write, perhaps using helper tools such as SWIG, or using object protocols such as ILU/CORBA or COM) Python becomes a very convenient "glue" or "steering" language that helps make heterogeneous collections of unrelated software packages work together. For example by combining Numeric with oracledb you can help your SQL database do statistical analysis, or even Fourier transforms. One of the features that makes Python excel in the "glue language" role is Python's simple, usable, and powerful C language runtime API.
Many developers also use Python extensively as a graphical user interface development aide.
Edit this entry / Log info / Last changed on Sat May 24 10:13:11 1997 by Aaron Watters
Edit this entry / Log info / Last changed on Fri Mar 29 06:50:32 2002 by Aahz
http://www.python.org/emacs/python-mode/index.htmlThere are many other choices, for Unix, Windows or Macintosh. Richard Jones compiled a table from postings on the Python newsgroup:
http://www.bofh.asn.au/~richard/editors.htmlSee also FAQ question 7.10 for some more Mac and Win options.
Edit this entry / Log info / Last changed on Mon Jun 15 23:21:04 1998 by Gvr
http://www.python.org/doc/Newbies.html
Edit this entry / Log info / Last changed on Wed Sep 5 05:34:07 2001 by GvR
http://www.xs4all.nlThanks to Thomas Wouters for setting this up!!!!
Edit this entry / Log info / Last changed on Fri Aug 3 21:49:27 2001 by GvR
Jacek Artymiak has created a Python Users Counter; you can see the current count by visiting http://www.wszechnica.safenet.pl/cgi-bin/checkpythonuserscounter.py (this will not increment the counter; use the link there if you haven't added yourself already). Most Python users appear not to have registered themselves.
Edit this entry / Log info / Last changed on Thu Feb 21 23:29:18 2002 by GvR
At CNRI (Python's new home), we have written two large applications: Grail, a fully featured web browser (see http://grail.cnri.reston.va.us), and the Knowbot Operating Environment, a distributed environment for mobile code.
The University of Virginia uses Python to control a virtual reality engine. See http://alice.cs.cmu.edu.
The ILU project at Xerox PARC can generate Python glue for ILU interfaces. See ftp://ftp.parc.xerox.com/pub/ilu/ilu.html. ILU is a free CORBA compliant ORB which supplies distributed object connectivity to a host of platforms using a host of languages.
Mark Hammond and Greg Stein and others are interfacing Python to Microsoft's COM and ActiveX architectures. This means, among other things, that Python may be used in active server pages or as a COM controller (for example to automatically extract from or insert information into Excel or MSAccess or any other COM aware application). Mark claims Python can even be a ActiveX scripting host (which means you could embed JScript inside a Python application, if you had a strange sense of humor). Python/AX/COM is distributed as part of the PythonWin distribution.
The University of California, Irvine uses a student administration system called TELE-Vision written entirely in Python. Contact: Ray Price rlprice@uci.edu.
The Melbourne Cricket Ground (MCG) in Australia (a 100,000+ person venue) has it's scoreboard system written largely in Python on MS Windows. Python expressions are used to create almost every scoring entry that appears on the board. The move to Python/C++ away from exclusive C++ has provided a level of functionality that would simply not have been viable otherwise.
See also the next question.
Note: this FAQ entry is really old. See http://www.python.org/psa/Users.html for a more recent list.
Edit this entry / Log info / Last changed on Wed Oct 25 13:24:15 2000 by GvR
Edit this entry / Log info / Last changed on Wed Oct 14 18:17:33 1998 by ken
With the introduction of retrospective "bugfix" releases the stability of the language implementations can be, and is being, improved independently of the new features offered by more recent major or minor releases. Bugfix releases, indicated by a third component of the version number, only fix known problems and do not gratuitously introduce new and possibly incompatible features or modified library functionality.
Release 2.2 got its first bugfix on April 10, 2002. The new version number is now 2.2.1. The 2.1 release, at 2.1.3, can probably be considered the "most stable" platform because it has been bugfixed twice.
Edit this entry / Log info / Last changed on Tue Jul 23 10:20:04 2002 by Jens Kubieziel
Also, follow the discussions on the python-dev mailing list.
Edit this entry / Log info / Last changed on Tue Apr 9 17:09:51 2002 by A.M. Kuchling
See http://www.python.org/peps/pep-0005.html for the proposed mechanism for creating backwards-incompatibilities.
Edit this entry / Log info / Last changed on Mon Apr 1 22:13:47 2002 by Fred Drake
Edit this entry / Log info / Last changed on Mon Apr 1 22:15:46 2002 by Fred Drake
The PSA has been superseded by the Python Software Foundation, an independent non-profit organization. The PSF's home page is at http://www.python.org/psf/.
Some pages created by the PSA still live at http://www.python.org/psa/
Edit this entry / Log info / Last changed on Thu Jul 25 18:19:44 2002 by GvR
Edit this entry / Log info / Last changed on Tue Jan 2 02:51:30 2001 by Moshe Zadka
Edit this entry / Log info / Last changed on Tue Jan 2 02:52:19 2001 by Moshe Zadka
Since Python is available free of charge, there are no absolute guarantees. If there are unforeseen problems, liability is the user's rather than the developers', and there is nobody you can sue for damages.
Python does few date manipulations, and what it does is all based on the Unix representation for time (even on non-Unix systems) which uses seconds since 1970 and won't overflow until 2038.
Edit this entry / Log info / Last changed on Mon Jan 8 17:19:32 2001 by Steve Holden
It is still common to start students with a procedural (subset of a) statically typed language such as Pascal, C, or a subset of C++ or Java. I think that students may be better served by learning Python as their first language. Python has a very simple and consistent syntax and a large standard library. Most importantly, using Python in a beginning programming course permits students to concentrate on important programming skills, such as problem decomposition and data type design.
With Python, students can be quickly introduced to basic concepts such as loops and procedures. They can even probably work with user-defined objects in their very first course. They could implement a tree structure as nested Python lists, for example. They could be introduced to objects in their first course if desired. For a student who has never programmed before, using a statically typed language seems unnatural. It presents additional complexity that the student must master and slows the pace of the course. The students are trying to learn to think like a computer, decompose problems, design consistent interfaces, and encapsulate data. While learning to use a statically typed language is important, it is not necessarily the best topic to address in the students' first programming course.
Many other aspects of Python make it a good first language. Python has a large standard library (like Java) so that students can be assigned programming projects very early in the course that do something. Assignments aren't restricted to the standard four-function calculator and check balancing programs. By using the standard library, students can gain the satisfaction of working on realistic applications as they learn the fundamentals of programming. Using the standard library also teaches students about code reuse.
Python's interactive interpreter also enables students to test language features while they're programming. They can keep a window with the interpreter running while they enter their programs' source in another window. If they can't remember the methods for a list, they can do something like this:
>>> L = [] >>> dir(L) ['append', 'count', 'extend', 'index', 'insert', 'pop', 'remove', 'reverse', 'sort'] >>> print L.append.__doc__ L.append(object) -- append object to end >>> L.append(1) >>> L [1]With the interpreter, documentation is never far from the student as he's programming.
There are also good IDEs for Python. Guido van Rossum's IDLE is a cross-platform IDE for Python that is written in Python using Tk. There is also a Windows specific IDE called PythonWin. Emacs users will be happy to know that there is a very good Python mode for Emacs. All of these programming environments provide syntax highlighting, auto-indenting, and access to the interactive interpreter while coding. For more information about IDEs, see XXX.
If your department is currently using Pascal because it was designed to be a teaching language, then you'll be happy to know that Guido van Rossum designed Python to be simple to teach to everyone but powerful enough to implement real world applications. Python makes a good language for first time programmers because that was one of Python's design goals. There are papers at http://www.python.org/doc/essays/ on the Python website by Python's creator explaining his objectives for the language. One that may interest you is titled "Computer Programming for Everybody" http://www.python.org/doc/essays/cp4e.html
If you're seriously considering Python as a language for your school, Guido van Rossum may even be willing to correspond with you about how the language would fit in your curriculum. See http://www.python.org/doc/FAQ.html#2.2 for examples of Python's use in the "real world."
While Python, its source code, and its IDEs are freely available, this consideration should not rule out other languages. There are other free languages (Java, free C compilers), and many companies are willing to waive some or all of their fees for student programming tools if it guarantees that a whole graduating class will know how to use their tools. That is, if one of the requirements for the language that will be taught is that it be freely available, then Python qualifies, but this requirement does not preclude other languages.
While Python jobs may not be as prevalent as C/C++/Java jobs, teachers should not worry about teaching students critical job skills in their first course. The skills that win students a job are those they learn in their senior classes and internships. Their first programming courses are there to lay a solid foundation in programming fundamentals. The primary question in choosing the language for such a course should be which language permits the students to learn this material without hindering or limiting them.
Another argument for Python is that there are many tasks for which something like C++ is overkill. That's where languages like Python, Perl, Tcl, and Visual Basic thrive. It's critical for students to know something about these languages. (Every employer for whom I've worked used at least one such language.) Of the languages listed above, Python probably makes the best language in a programming curriculum since its syntax is simple, consistent, and not unlike other languages (C/C++/Java) that are probably in the curriculum. By starting students with Python, a department simultaneously lays the foundations for other programming courses and introduces students to the type of language that is often used as a "glue" language. As an added bonus, Python can be used to interface with Microsoft's COM components (thanks to Mark Hammond). There is also Jython, a Java implementation of the Python interpreter, that can be used to connect Java components.
If you currently start students with Pascal or C/C++ or Java, you may be worried they will have trouble learning a statically typed language after starting with Python. I think that this fear most often stems from the fact that the teacher started with a statically typed language, and we tend to like to teach others in the same way we were taught. In reality, the transition from Python to one of these other languages is quite simple.
To motivate a statically typed language such as C++, begin the course by explaining that unlike Python, their first language, C++ is compiled to a machine dependent executable. Explain that the point is to make a very fast executable. To permit the compiler to make optimizations, programmers must help it by specifying the "types" of variables. By restricting each variable to a specific type, the compiler can reduce the book-keeping it has to do to permit dynamic types. The compiler also has to resolve references at compile time. Thus, the language gains speed by sacrificing some of Python's dynamic features. Then again, the C++ compiler provides type safety and catches many bugs at compile time instead of run time (a critical consideration for many commercial applications). C++ is also designed for very large programs where one may want to guarantee that others don't touch an object's implementation. C++ provides very strong language features to separate an object's implementation from its interface. Explain why this separation is a good thing.
The first day of a C++ course could then be a whirlwind introduction to what C++ requires and provides. The point here is that after a semester or two of Python, students are hopefully competent programmers. They know how to handle loops and write procedures. They've also worked with objects, thought about the benefits of consistent interfaces, and used the technique of subclassing to specialize behavior. Thus, a whirlwind introduction to C++ could show them how objects and subclassing looks in C++. The potentially difficult concepts of object-oriented design were taught without the additional obstacles presented by a language such as C++ or Java. When learning one of these languages, the students would already understand the "road map." They understand objects; they would just be learning how objects fit in a statically typed languages. Language requirements and compiler errors that seem unnatural to beginning programmers make sense in this new context. Many students will find it helpful to be able to write a fast prototype of their algorithms in Python. Thus, they can test and debug their ideas before they attempt to write the code in the new language, saving the effort of working with C++ types for when they've discovered a working solution for their assignments. When they get annoyed with the rigidity of types, they'll be happy to learn about containers and templates to regain some of the lost flexibility Python afforded them. Students may also gain an appreciation for the fact that no language is best for every task. They'll see that C++ is faster, but they'll know that they can gain flexibility and development speed with a Python when execution speed isn't critical.
If you have any concerns that weren't addressed here, try posting to the Python newsgroup. Others there have done some work with using Python as an instructional tool. Good luck. We'd love to hear about it if you choose Python for your course.
Edit this entry / Log info / Last changed on Mon Dec 2 19:32:35 2002 by Bill Sconce
import test.autotestIn Python 1.4 or earlier, use
import autotestThe test set doesn't test all features of Python, but it goes a long way to confirm that Python is actually working.
NOTE: if "make test" fails, don't just mail the output to the newsgroup -- this doesn't give enough information to debug the problem. Instead, find out which test fails, and run that test manually from an interactive interpreter. For example, if "make test" reports that test_spam fails, try this interactively:
import test.test_spamThis generally produces more verbose output which can be diagnosed to debug the problem. If you find a bug in Python or the libraries, or in the tests, please report this in the Python bug tracker at SourceForge:
http://sourceforge.net/tracker/?func=add&group_id=5470&atid=105470
Edit this entry / Log info / Last changed on Fri Apr 27 10:29:36 2001 by Fred Drake
#! /usr/local/bin/python --You can also use this interactively:
python -- script.py [options]Note that a working getopt implementation is provided in the Python distribution (in Python/getopt.c) but not automatically used.
#readline readline.c -lreadline -ltermcap
in Modules/Setup. The configuration option --with-readline is no longer supported, at least in Python 2.0. Some hints on building and using the readline library: On SGI IRIX 5, you may have to add the following to rldefs.h:
#ifndef sigmask #define sigmask(sig) (1L << ((sig)-1)) #endifOn some systems, you will have to add #include "rldefs.h" to the top of several source files, and if you use the VPATH feature, you will have to add dependencies of the form foo.o: foo.c to the Makefile for several values of foo. The readline library requires use of the termcap library. A known problem with this is that it contains entry points which cause conflicts with the STDWIN and SGI GL libraries. The STDWIN conflict can be solved by adding a line saying '#define werase w_erase' to the stdwin.h file (in the STDWIN distribution, subdirectory H). The GL conflict has been solved in the Python configure script by a hack that forces use of the static version of the termcap library. Check the newsgroup gnu.bash.bug news:gnu.bash.bug for specific problems with the readline library (I don't read this group but I've been told that it is the place for readline bugs).
Edit this entry / Log info / Last changed on Sat Dec 2 18:23:48 2000 by Issac Trotts
Note that this FAQ entry only applies to Linux kernel versions 1.x.y; these are hardly around any more.
Edit this entry / Log info / Last changed on Tue Jul 30 20:05:52 2002 by Jens Kubieziel
http://sourceforge.net/tracker/?group_id=5470&atid=105470and we'll look into it. Please provide as many details as possible. In particular, if you don't tell us what type of computer and what operating system (and version) you are using it will be difficult for us to figure out what is the matter. If you have compilation output logs, please use file uploads -- don't paste everything in the message box.
In many cases, we won't have access to the same hardware or operating system version, so please, if you have a SourceForge account, log in before filing your report, or if you don't have an account, include an email address at which we can reach you for further questions. Logging in to SourceForge first will also cause SourceForge to send you updates as we act on your report.
Edit this entry / Log info / Last changed on Fri Apr 27 10:53:18 2001 by Fred Drake
Edit this entry / Log info / Last changed on Wed May 21 15:45:03 1997 by GvR
*shared*in the Setup file. Shared library code must be compiled with "-fpic". If a .o file for the module already exist that was compiled for static linking, you must remove it or do "make clean" in the Modules directory.
Edit this entry / Log info / Last changed on Fri May 23 13:42:30 1997 by GvR
Edit this entry / Log info / Last changed on Sun Jun 2 17:27:13 2002 by Erno Kuusela
Edit this entry / Log info / Last changed on Tue Sep 11 16:02:22 2001 by GvR
Edit this entry / Log info / Last changed on Tue Sep 11 15:54:57 2001 by GvR
(Also note that when compiling unpatched Python 1.5.1 against Tcl/Tk 7.6/4.2 or older, you get an error on Tcl_Finalize. See the 1.5.1 patch page at http://www.python.org/1.5/patches-1.5.1/.)
Edit this entry / Log info / Last changed on Thu Jun 11 00:49:14 1998 by Gvr
Edit this entry / Log info / Last changed on Mon Jun 3 16:46:23 2002 by Erno Kuusela
set PYTHONPATH=c:\python;c:\python\lib;c:\python\scripts
(assuming Python was installed in c:\python)
This shows up when building DLL under MSVC. There's two ways to address this: either compile the module as C++, or change your code to something like:
statichere PyTypeObject bstreamtype = { PyObject_HEAD_INIT(NULL) /* must be set by init function */ 0, "bstream", sizeof(bstreamobject),
...
void initbstream() { /* Patch object type */ bstreamtype.ob_type = &PyType_Type; Py_InitModule("bstream", functions); ... }
Edit this entry / Log info / Last changed on Sun May 25 14:58:05 1997 by Aaron Watters
% python script.py ...some output... % python script.py >file % cat file % # no output % python script.py | cat % # no output %This was a bug in Linux kernel. It is fixed and should not appear anymore. So most Linux users are not affected by this.
If redirection doesn't work on your Linux system, check what shell you are using. Shells like (t)csh doesn't support redirection.
Edit this entry / Log info / Last changed on Thu Jan 16 13:38:30 2003 by Jens Kubieziel
Edit this entry / Log info / Last changed on Mon Jun 3 16:48:08 2002 by Erno Kuusela
Edit this entry / Log info / Last changed on Mon Jun 3 16:49:08 2002 by Erno Kuusela
python >>> import _tkinter >>> import Tkinter >>> Tkinter._test()This should pop up a window with two buttons, one "Click me" and one "Quit".
If the first statement (import _tkinter) fails, your Python installation probably has not been configured to support Tcl/Tk. On Unix, if you have installed Tcl/Tk, you have to rebuild Python after editing the Modules/Setup file to enable the _tkinter module and the TKPATH environment variable.
It is also possible to get complaints about Tcl/Tk version number mismatches or missing TCL_LIBRARY or TK_LIBRARY environment variables. These have to do with Tcl/Tk installation problems.
A common problem is to have installed versions of tcl.h and tk.h that don't match the installed version of the Tcl/Tk libraries; this usually results in linker errors or (when using dynamic loading) complaints about missing symbols during loading the shared library.
Edit this entry / Log info / Last changed on Thu Aug 28 17:01:46 1997 by Guido van Rossum
On Unix, if you have enabled the readline module (i.e. if Emacs-style command line editing and bash-style history works for you), you can add this by importing the undocumented standard library module "rlcompleter". When completing a simple identifier, it completes keywords, built-ins and globals in __main__; when completing NAME.NAME..., it evaluates (!) the expression up to the last dot and completes its attributes.
This way, you can do "import string", type "string.", hit the completion key twice, and see the list of names defined by the string module.
Tip: to use the tab key as the completion key, call
readline.parse_and_bind("tab: complete")You can put this in a ~/.pythonrc file, and set the PYTHONSTARTUP environment variable to ~/.pythonrc. This will cause the completion to be enabled whenever you run Python interactively.
Notes (see the docstring for rlcompleter.py for more information):
* The evaluation of the NAME.NAME... form may cause arbitrary application defined code to be executed if an object with a __getattr__ hook is found. Since it is the responsibility of the application (or the user) to enable this feature, I consider this an acceptable risk. More complicated expressions (e.g. function calls or indexing operations) are not evaluated.
* GNU readline is also used by the built-in functions input() and raw_input(), and thus these also benefit/suffer from the complete features. Clearly an interactive application can benefit by specifying its own completer function and using raw_input() for all its input.
* When stdin is not a tty device, GNU readline is never used, and this module (and the readline module) are silently inactive.
Edit this entry / Log info / Last changed on Fri Jun 12 09:55:24 1998 by A.M. Kuchling
It's just a nightmare to get this to work on all different platforms. Shared library portability is a pain. And yes, I know about GNU libtool -- but it requires me to use its conventions for filenames etc, and it would require a complete and utter rewrite of all the makefile and config tools I'm currently using.
In practice, few applications embed Python -- it's much more common to have Python extensions, which already are shared libraries. Also, serious embedders often want total control over which Python version and configuration they use so they wouldn't want to use a standard shared library anyway. So while the motivation of saving space when lots of apps embed Python is nice in theory, I doubt that it will save much in practice. (Hence the low priority I give to making a shared library.)
For Linux systems, the simplest method of producing libpython1.5.so seems to be (originally from the Minotaur project web page, http://www.equi4.com/minotaur/minotaur.html):
make distclean ./configure make OPT="-fpic -O2" mkdir .extract (cd .extract; ar xv ../libpython1.5.a) gcc -shared -o libpython1.5.so .extract/*.o rm -rf .extractIn Python 2.3 this will be supported by the standard build routine (at least on Linux) with --enable-shared. Note however that there is little advantage, and it slows down Python because of the need for PIC code and the extra cost at startup time to find the library.
Edit this entry / Log info / Last changed on Thu May 30 13:36:55 2002 by GvR
In file included from /usr/include/sys/stream.h:26, from /usr/include/netinet/in.h:38, from /usr/include/netdb.h:96, from ./socketmodule.c:121: /usr/include/sys/model.h:32: #error "No DATAMODEL_NATIVE specified"Solution: rebuild GCC for Solaris 2.6. You might be able to simply re-run fixincludes, but people have had mixed success with doing that.
Edit this entry / Log info / Last changed on Wed Oct 21 11:18:46 1998 by GvR
Use "make clean" to reduce the size of the source/build directory after you're happy with your build and installation. If you have already tried to build python and you'd like to start over, you should use "make clobber". It does a "make clean" and also removes files such as the partially built Python library from a previous build.
Edit this entry / Log info / Last changed on Thu Jun 24 20:39:26 1999 by TAB
Bugs: http://sourceforge.net/tracker/?group_id=5470&atid=105470
Patches: http://sourceforge.net/tracker/?group_id=5470&atid=305470
If you have a SourceForge account, please log in before submitting your bug report; this will make it easier for us to contact you regarding your report in the event we have follow-up questions. It will also enable SourceForge to send you update information as we act on your bug. If you do not have a SourceForge account, please consider leaving your name and email address as part of the report.
Edit this entry / Log info / Last changed on Fri Apr 27 10:58:26 2001 by Fred Drake
symbol PyExc_RuntimeError: referenced symbol not found
There is a problem with the configure script for Python 1.5.2 under Solaris 7 with gcc 2.95 . configure should set the make variable LINKFORSHARED=-Xlinker -export-dynamic
in Modules/Makefile,
Manually add this line to the Modules/Makefile. This builds a Python executable that can load shared library extensions (xxx.so) .
Edit this entry / Log info / Last changed on Mon Feb 19 10:37:05 2001 by GvR
http://www.python.org/doc/current/lib/profile-calibration.html
then it is possible that the regression test "test___all__" will fail if you run the regression test manually rather than using "make test" in the Python source directory. This will happen if you have set your PYTHONPATH environment variable to include the directory containing your calibrated profile module. You have probably calibrated the profiler using an older version of the profile module which does not define the __all__ value, added to the module as of Python 2.1.
The problem can be fixed by removing the old calibrated version of the profile module and using the latest version to do a fresh calibration. In general, you will need to re-calibrate for each version of Python anyway, since the performance characteristics can change in subtle ways that impact profiling.
Edit this entry / Log info / Last changed on Fri Apr 27 10:44:10 2001 by Fred Drake
The following solutions and work-arounds are known:
1. Rebuild the libraries (libreadline, libcrypto) with -fPIC (-KPIC if using the system compiler). This is recommended; all object files in a shared library should be position-independent.
2. Statically link the extension module and its libraries into the Python interpreter, by editing Modules/Setup.
3. Use GNU ld instead of /usr/ccs/bin/ld; GNU ld will accept non-PIC code in shared libraries (and mark the section writable)
4. Pass -mimpure-text to GCC when linking the module. This will force gcc to not pass -z text to ld; in turn, ld will make all text sections writable.
Options 3 and 4 are not recommended, since the ability to share code across processes is lost.
Edit this entry / Log info / Last changed on Tue Jan 29 12:05:11 2002 by Martin v. Löwis
Module pdb is a rudimentary but adequate console-mode debugger for Python. It is part of the standard Python library, and is documented in the Library Reference Manual. (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 in Tools/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 bdb. The Pythonwin debugger colors breakpoints and has quite a few cool features (including 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/)
Edit this entry / Log info / Last changed on Tue Jan 28 01:43:41 2003 by Stephen Ferg
In previous versions of Python, you can easily create a Python class which serves as a wrapper around a built-in object, e.g. (for dictionaries):
# A user-defined class behaving almost identical # to a built-in dictionary. class UserDict: def __init__(self): self.data = {} def __repr__(self): return repr(self.data) def __cmp__(self, dict): if type(dict) == type(self.data): return cmp(self.data, dict) else: return cmp(self.data, dict.data) def __len__(self): return len(self.data) def __getitem__(self, key): return self.data[key] def __setitem__(self, key, item): self.data[key] = item def __delitem__(self, key): del self.data[key] def keys(self): return self.data.keys() def items(self): return self.data.items() def values(self): return self.data.values() def has_key(self, key): return self.data.has_key(key)A2. See Jim Fulton's ExtensionClass for an example of a mechanism which allows you to have superclasses which you can inherit from in Python -- that way you can have some methods from a C superclass (call it a mixin) and some methods from either a Python superclass or your subclass. ExtensionClass is distributed as a part of Zope (see http://www.zope.org), but will be phased out with Zope 3, since Zope 3 uses Python 2.2 or later which supports direct inheritance from built-in types. Here's a link to the original paper about ExtensionClass: http://debian.acm.ndsu.nodak.edu/doc/python-extclass/ExtensionClass.html
A3. 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).
Edit this entry / Log info / Last changed on Tue May 28 21:09:52 2002 by GvR
In Python versions before 2.0 the module only supported plain curses; you couldn't use ncurses features like colors with it (though it would link with ncurses).
In Python 2.0, the curses module has been greatly extended, starting from Oliver Andrich's enhanced version, to provide many additional functions from ncurses and SYSV curses, such as colour, alternative character set support, pads, and mouse support. This means the module is no longer compatible with operating systems that only have BSD curses, but there don't seem to be any currently maintained OSes that fall into this category.
Edit this entry / Log info / Last changed on Sun Jun 23 20:24:06 2002 by Tim Peters
For Python 1.5.2: You need to import sys and assign a function to sys.exitfunc, it will be called when your program exits, is killed by an unhandled exception, or (on UNIX) receives a SIGHUP or SIGTERM signal.
Edit this entry / Log info / Last changed on Thu Dec 28 12:14:55 2000 by Bjorn Pettersen
Edit this entry / Log info / Last changed on Thu Mar 21 05:18:22 2002 by Erno Kuusela
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...
Edit this entry / Log info / Last changed on Sun May 25 21:10:50 1997 by GvR
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 avoid the overhead of kernel system calls. Thus CGI scripts that write all output in "one shot" may be notably faster than those that write lots of small pieces of output.
Also, be sure to use "aggregate" operations where appropriate. For example the "slicing" feature allows programs to chop up lists and other sequence objects in a single tick of the interpreter 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 map() function, particularly used with builtin methods or builtin functions can be a convenient accelerator. For example to pair the elements of two lists together:
>>> map(None, [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 map operation completes very quickly in such cases.
Other examples of aggregate operations 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 copying in one pass. For manipulating strings also consider the regular expression libraries and the "substitution" operations String % tuple and String % dictionary. Also be sure to use the list.sort builtin method to do sorting, and see FAQ's 4.51 and 4.59 for examples of moderately advanced usage -- list.sort beats other techniques for sorting in all but the most extreme circumstances.
There are many other aggregate operations available in the standard libraries and in contributed libraries and extensions.
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 (profile.run) 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 resulttends to be called in loops like (A)
list = map(ff, oldlist)or (B)
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 resultseqand rewrite (A) to
list = ffseq(oldlist)and (B) to
for value in ffseq(sequence): ...do something with value...Other single calls 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) + 1resolves dict.get every iteration. If the method isn't going to change, a faster implementation is
dict_get = dict.get # look up the method once for key in token: dict[key] = dict_get(key, 0) + 1Default 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.
For an anecdote related to optimization, see
http://www.python.org/doc/essays/list2str.html
Edit this entry / Log info / Last changed on Mon Jun 3 01:03:54 2002 by Neal Norwitz
import modname reload(modname)Warning: this technique is not 100% fool-proof. In particular, modules containing statements like
from modname import some_objectswill continue to work with the old version of the imported objects.
if __name__ == '__main__': main()
NOTE: if the complaint is about "Tkinter" (upper case T) and you have already configured module "tkinter" (lower case t), the solution is not to rename tkinter to Tkinter or vice versa. There is probably something wrong with your module search path. Check out the value of sys.path.
For X-related modules (Xt and Xm) you will have to do more work: they are currently not part of the standard Python distribution. You will have to ftp the Extensions tar file, i.e. ftp://ftp.python.org/pub/python/src/X-extension.tar.gz and follow the instructions there.
Edit this entry / Log info / Last changed on Wed Feb 12 21:31:08 2003 by Jens Kubieziel
Edit this entry / Log info / Last changed on Thu Mar 21 08:30:13 2002 by Erno Kuusela
Currently supported solutions:
Cross-platform:
Tk:
There's a neat object-oriented interface to the Tcl/Tk widget set, called Tkinter. It is part of the standard Python distribution and well-supported -- all you need to do is build and install Tcl/Tk and enable the _tkinter module and the TKPATH definition in Modules/Setup when building Python. This is probably the easiest to install and use, and the most complete widget set. It is also very likely that in the future the standard Python GUI API will be based on or at least look very much like the Tkinter interface. For more info about Tk, including pointers to the source, see the Tcl/Tk home page at http://www.scriptics.com. Tcl/Tk is now fully portable to the Mac and Windows platforms (NT and 95 only); you need Python 1.4beta3 or later and Tk 4.1patch1 or later.
wxWindows:
There's an interface to wxWindows called wxPython. wxWindows is a portable GUI class library written in C++. It supports GTK, Motif, MS-Windows and Mac as targets. Ports to other platforms are being contemplated or have already had some work done on them. 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 at http://www.wxwindows.org/ for more details. wxPython is a python 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 at http://alldunn.com/wxPython/.
Gtk+:
PyGtk bindings for the Gtk+ Toolkit by James Henstridge exist; see ftp://ftp.daa.com.au/pub/james/python/. Note that there are two incompatible bindings. If you are using Gtk+ 1.2.x you should get the 0.6.x PyGtk bindings from
ftp://ftp.gtk.org/pub/python/v1.2If you plan to use Gtk+ 2.0 with Python (highly recommended if you are just starting with Gtk), get the most recent distribution from
ftp://ftp.gtk.org/pub/python/v2.0If you are adventurous, you can also check out the source from the Gnome CVS repository. Set your CVS directory to :pserver:anonymous@anoncvs.gnome.org:/cvs/gnome and check the gnome-python module out from the repository.
Other:
There are also bindings available for the Qt toolkit (PyQt), and for KDE (PyKDE); see http://www.thekompany.com/projects/pykde/.
For OpenGL bindings, see http://starship.python.net/~da/PyOpenGL.
Platform specific:
The Mac port has a rich and ever-growing set of modules that support the native Mac toolbox calls. See the documentation that comes with the Mac port. See ftp://ftp.python.org/pub/python/mac. Support by Jack Jansen jack@cwi.nl.
Pythonwin by Mark Hammond (MHammond@skippinet.com.au) includes an interface to the Microsoft Foundation Classes and a Python programming environment using it that's written mostly in Python. See http://www.python.org/windows/.
There's an object-oriented GUI based on the Microsoft Foundation Classes model called WPY, supported by Jim Ahlstrom jim@interet.com. Programs written in WPY run unchanged and with native look and feel on Windows NT/95, Windows 3.1 (using win32s), and on Unix (using Tk). Source and binaries for Windows and Linux are available in ftp://ftp.python.org/pub/python/wpy/.
Obsolete or minority solutions:
There's an interface to X11, including the Athena and Motif widget sets (and a few individual widgets, like Mosaic's HTML widget and SGI's GL widget) available from ftp://ftp.python.org/pub/python/src/X-extension.tar.gz. Support by Sjoerd Mullender sjoerd@cwi.nl.
On top of the X11 interface there's the vpApp toolkit by Per Spilling, now also maintained by Sjoerd Mullender sjoerd@cwi.nl. See ftp://ftp.cwi.nl/pub/sjoerd/vpApp.tar.gz.
For SGI IRIX only, there are unsupported interfaces to the complete GL (Graphics Library -- low level but very good 3D capabilities) as well as to FORMS (a buttons-and-sliders-etc package built on top of GL by Mark Overmars -- ftp'able from ftp://ftp.cs.ruu.nl/pub/SGI/FORMS/). This is probably also becoming obsolete, as OpenGL takes over (see above).
There's an interface to STDWIN, a platform-independent low-level windowing interface for Mac and X11. This is totally unsupported and rapidly becoming obsolete. The STDWIN sources are at ftp://ftp.cwi.nl/pub/stdwin/.
There is an interface to WAFE, a Tcl interface to the X11 Motif and Athena widget sets. WAFE is at http://www.wu-wien.ac.at/wafe/wafe.html.
Edit this entry / Log info / Last changed on Mon May 13 21:40:39 2002 by Skip Montanaro
Edit this entry / Log info / Last changed on Tue Jan 4 20:12:19 2000 by Barney Warplug
# 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 axisDon't try this at home, kids!
Edit this entry / Log info / Last changed on Wed May 21 15:48:33 1997 by GvR
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'.
As a last resort it is possible to implement the "?:" operator as a function:
def q(cond,on_true,on_false): from inspect import isfunction
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, since most language have one; it is a frequently requested feature.
There are several possible answers: just as 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.
Nevertheless, in an effort to decide once and for all whether an if-then-else expression should be added to the language, PEP 308 (http://www.python.org/peps/pep-0308.html) has been put forward, proposing a specific syntax. The community can now vote on this issue.
Edit this entry / Log info / Last changed on Fri Feb 7 19:41:13 2003 by David Goodger
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 pointer and each parent has a list of children) the reference counts will never go back to zero. You'll have to define an explicit close() method which removes those pointers. Please don't ever call __del__ directly -- __del__ should call close() and close() should make sure that it can be called more than once for the same object.
If the object has ever been a local variable (or argument, which is really the same thing) to 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, deleting (better: assigning None to) sys.exc_traceback will take care of this. If a stack was printed for an unhandled exception in an interactive interpreter, delete sys.last_traceback instead.
There is code that deletes all objects when the interpreter exits, but it is not called if your Python has been configured to support threads (because other threads may still be active). You can define your own cleanup function using sys.exitfunc (see question 4.4).
Finally, if your __del__ method raises an exception, a warning message is printed to sys.stderr.
Starting with Python 2.0, a garbage collector periodically reclaims the space used by most cycles with no external references. (See the "gc" module documentation for details.) There are, however, pathological cases where it can be expected to fail. Moreover, the garbage collector runs 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.
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 pointers (if they need them!).
Question 6.14 is intended to explain the new garbage collection algorithm.
Edit this entry / Log info / Last changed on Mon Jun 10 15:27:28 2002 by Matthias Urlichs
Before Python 1.4, modifying the environment passed to subshells was left out of the interpreter because there seemed to be no well-established portable way to do it (in particular, some systems, have putenv(), others have setenv(), and some have none at all). As of Python 1.4, almost all Unix systems do have putenv(), and so does the Win32 API, and thus the os module was modified so that changes to os.environ are trapped and the corresponding putenv() call is made.
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.
The term "classic class" is used to refer to the original class implementation in Python. One problem with classic classes is their inability to use the built-in data types (such as list and dictionary) as base classes. Starting with Python 2.2 an attempt is in progress to unify user-defined classes and built-in types. It is now possible to declare classes that inherit from built-in types.
Edit this entry / Log info / Last changed on Mon May 27 01:31:21 2002 by Steve Holden
Trivia note regarding bound methods: each reference to a bound method of a particular object creates a bound method object. If you have two such references (a = inst.meth; b = inst.meth), they will compare equal (a == b) but are not the same (a is not b).
Edit this entry / Log info / Last changed on Wed May 6 18:07:25 1998 by Clarence Gardner
Often when you want to do this you are forgetting that classes are first class in Python. You can "point to" the class you want to delegate an operation to either at the instance or at the subclass level. For example if you want to use a "glorp" operation of a superclass you can point to the right superclass to use.
class subclass(superclass1, superclass2, superclass3): delegate_glorp = superclass2 ... def glorp(self, arg1, arg2): ... subclass specific stuff ... self.delegate_glorp.glorp(self, arg1, arg2) ...
class subsubclass(subclass): delegate_glorp = superclass3 ...Note, however that setting delegate_glorp to subclass in subsubclass would cause an infinite recursion on subclass.delegate_glorp. Careful! Maybe you are getting too fancy for your own good. Consider simplifying the design (?).
Edit this entry / Log info / Last changed on Mon Jul 28 13:58:22 1997 by aaron watters
BaseAlias = <real base class> class Derived(BaseAlias): def meth(self): BaseAlias.meth(self) ...
Edit this entry / Log info / Last changed on Wed May 21 15:49:57 1997 by GvR
For an instance x of a user-defined class, instance attributes are found in the dictionary x.__dict__, and methods and attributes defined by its class are found in x.__class__.__bases__[i].__dict__ (for i in range(len(x.__class__.__bases__))). You'll have to walk the tree of base classes to find all class methods and attributes.
Many, but not all built-in types define a list of their method names in x.__methods__, and if they have data attributes, their names may be found in x.__members__. However this is only a convention.
For more information, read the source of the standard (but undocumented) module newdir.
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. Using 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 1 the modules written in Python to 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.
(Hint: the freeze program only works if your script's filename ends in ".py".)
There are several utilities which may be helpful. The first is Gordon McMillan's installer at
http://www.mcmillan-inc.com/install1.htmlwhich 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, which will find the byte code in executable.
A fourth is Fredrik Lundh's Squeeze (http://www.pythonware.com/products/python/squeeze/).
Edit this entry / Log info / Last changed on Wed Jun 19 14:01:30 2002 by Gordon McMillan
A summary of available frameworks is maintained by Paul Boddie at
http://thor.prohosting.com/~pboddie/Python/web_modules.htmlCameron Laird maintains a useful set of pages about Python web technologies at
http://starbase.neosoft.com/~claird/comp.lang.python/web_python.html/There was a web browser written in Python, called Grail -- see http://sourceforge.net/project/grail/. This project has been terminated; http://cvs.sourceforge.net/cgi-bin/viewcvs.cgi/grail/grail/README gives more details.
Edit this entry / Log info / Last changed on Mon Nov 11 22:48:25 2002 by GvR
import popen2 fromchild, tochild = popen2.popen2("command") tochild.write("input\n") tochild.flush() output = fromchild.readline()Warning: in general, it is unwise to do this, because you can easily cause a deadlock where your process is blocked waiting for output from the child, while the child is blocked waiting for input from you. This can be caused because the parent expects the child to output more text than it does, or it can be caused by data being stuck in stdio buffers due to lack of flushing. The Python parent can of course explicitly flush the data it sends to the child before it reads any output, but if the child is a naive C program it can easily have been written to never explicitly flush its output, even if it is interactive, since flushing is normally automatic.
Note that a deadlock is also possible if you use popen3 to read stdout and stderr. If one of the two is too large for the internal buffer (increasing the buffersize does not help) and you read() the other one first, there is a deadlock, too.
Note on a bug in popen2: unless your program calls wait() or waitpid(), finished child processes are never removed, and eventually calls to popen2 will fail because of a limit on the number of child processes. Calling os.waitpid with the os.WNOHANG option can prevent this; a good place to insert such a call would be before calling popen2 again.
Another way to produce a deadlock: Call a wait() and there is still more output from the program than what fits into the internal buffers.
In many cases, all you really need is to run some data through a command and get the result back. Unless the data is infinite in size, the easiest (and often the most efficient!) way to do this is to write it to a temporary file and run the command with that temporary file as input. The standard module tempfile exports a function mktemp() which generates unique temporary file names.
import tempfile import os class Popen3: """ This is a deadlock-save version of popen, that returns an object with errorlevel, out (a string) and err (a string). (capturestderr may not work under windows.) Example: print Popen3('grep spam','\n\nhere spam\n\n').out """ def __init__(self,command,input=None,capturestderr=None): outfile=tempfile.mktemp() command="( %s ) > %s" % (command,outfile) if input: infile=tempfile.mktemp() open(infile,"w").write(input) command=command+" <"+infile if capturestderr: errfile=tempfile.mktemp() command=command+" 2>"+errfile self.errorlevel=os.system(command) >> 8 self.out=open(outfile,"r").read() os.remove(outfile) if input: os.remove(infile) if capturestderr: self.err=open(errfile,"r").read() os.remove(errfile)Note that many interactive programs (e.g. vi) don't work well with pipes substituted for standard input and output. You will have to use pseudo ttys ("ptys") instead of pipes. There is some undocumented code to use these in the library module pty.py -- I'm afraid you're on your own here.
A different answer is a Python interface to Don Libes' "expect" library. A Python extension that interfaces to expect is called "expy" and available from http://expectpy.sourceforge.net/.
A pure Python solution that works like expect is pexpect of Noah Spurrier. A beta version is available from http://pexpect.sourceforge.net/
Edit this entry / Log info / Last changed on Tue Sep 3 16:31:31 2002 by Tobias Polzin
func(1, 2, 3)is equivalent to
args = (1, 2, 3) apply(func, args)Note that func(args) is not the same -- it calls func() with exactly one argument, the tuple args, instead of three arguments, the integers 1, 2 and 3.
In Python 2.0, you can also use extended call syntax:
f(*args) is equivalent to apply(f, args)
Edit this entry / Log info / Last changed on Tue Jan 2 03:42:50 2001 by Moshe Zadka
If you are using an older version of XEmacs or Emacs you will need to put this in your .emacs file:
(defun my-python-mode-hook () (setq font-lock-keywords python-font-lock-keywords) (font-lock-mode 1)) (add-hook 'python-mode-hook 'my-python-mode-hook)
Edit this entry / Log info / Last changed on Mon Apr 6 16:18:46 1998 by Barry Warsaw
For simple input parsing, the easiest approach is usually to split the line into whitespace-delimited words using string.split(), and to convert decimal strings to numeric values using int(), long() or float(). (Python's int() is 32-bit and its long() is arbitrary precision.) string.split supports an optional "sep" parameter which is useful if the line uses something other than whitespace as a delimiter.
For more complicated input parsing, regular expressions (see module re) are better suited and more powerful than C's sscanf().
There's a contributed module that emulates sscanf(), by Steve Clift; see contrib/Misc/sscanfmodule.c of the ftp site:
http://www.python.org/ftp/python/contrib-09-Dec-1999/Misc/
Edit this entry / Log info / Last changed on Mon Jun 3 01:07:51 2002 by Neal Norwitz
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).
1) By using global variables; but you probably shouldn't :-)
2) 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 1003) By returning a tuple, holding the final values of arguments:
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 1004) And other ideas that fall-out from Python's object model. For instance, it might be clearer to pass in a mutable dictionary:
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
But there's probably no good reason to get this complicated :-).[Python's author favors solution 3 in most cases.]
Edit this entry / Log info / Last changed on Sun Jun 8 23:49:46 1997 by David Ascher
Though a bit surprising at first, a moment's consideration explains this. On one hand, requirement of 'global' for assigned vars provides a bar against unintended side-effects. On the other hand, if global were required for all global references, you'd be using global all the time. Eg, 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.
Edit this entry / Log info / Last changed on Fri Aug 28 09:53:27 1998 by GvR
foo.py:
from bar import bar_var foo_var=1bar.py:
from foo import foo_var bar_var=2The problem is that the above is processed by the interpreter thus:
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 dict for foo is still empty.
The same thing happens when you use "import foo", and then try to access "foo.one" in global code.
There are (at least) three possible workarounds for this problem.
Guido van Rossum recommends to avoid all uses of "from <module> import ..." (so everything from an imported module is referenced as <module>.<name>) and to place all code inside functions. Initializations of global variables and class variables should use constants or built-in functions only.
Jim Roskind suggests 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).Python's author doesn't like this approach much because the imports appear in a strange place, but has to admit that it works.
Matthias Urlichs recommends to restructure your code so that the recursive import is not necessary in the first place.
These solutions are not mutually exclusive.
Edit this entry / Log info / Last changed on Mon Jun 3 06:52:51 2002 by Matthias Urlichs
Dictionaries have a copy method. Sequences can be copied by slicing:
new_l = l[:]
Edit this entry / Log info / Last changed on Thu Mar 21 05:40:26 2002 by Erno Kuusela
A more awkward way of doing things is to use pickle's little sister, marshal. The marshal module provides very fast ways to store noncircular basic Python types to files and strings, and back again. Although marshal does not do fancy things like store instances or handle shared references properly, it does run extremely fast. For example loading a half megabyte of data may take less than a third of a second (on some machines). This often beats doing something more complex and general such as using gdbm with pickle/shelve.
Edit this entry / Log info / Last changed on Sun Jun 8 22:59:00 1997 by David Ascher
To remove a directory, use os.rmdir(); use os.mkdir() to create one.
To rename a file, use os.rename().
To truncate a file, open it using f = open(filename, "r+"), and use f.truncate(offset); offset defaults to the current seek position. (The "r+" mode opens the file for reading and writing.) There's also os.ftruncate(fd, offset) for files opened with os.open() -- for advanced Unix hacks only.
The shutil module also contains a number of functions to work on files including copyfile, copytree, and rmtree amongst others.
Edit this entry / Log info / Last changed on Thu Dec 28 12:30:01 2000 by Bjorn Pettersen
Edit this entry / Log info / Last changed on Tue Jan 2 02:56:56 2001 by Moshe Zadka
Note that these are restricted to decimal interpretation, so that int('0144') == 144 and int('0x144') raises ValueError. For Python 2.0 int takes the base to convert from as a second optional argument, so int('0x144', 16) == 324.
For greater flexibility, or before Python 1.5, import the module string and use the string.atoi() function for integers, string.atol() for long integers, or string.atof() for floating-point. E.g., string.atoi('100', 16) == string.atoi('0x100', 0) == 256. See the library reference manual section for the string module for more details.
While you could use the built-in function eval() instead of any of those, this is not recommended, because someone could pass you a Python expression that might have unwanted side effects (like reformatting your disk). It also has the effect of interpreting numbers as Python expressions, so that e.g. eval('09') gives a syntax error since Python regards numbers starting with '0' as octal (base 8).
Edit this entry / Log info / Last changed on Thu Dec 28 12:37:34 2000 by Bjorn Pettersen
Edit this entry / Log info / Last changed on Tue Jan 2 02:59:40 2001 by Moshe Zadka
However, there are some legitimate situations where you need to test for class membership.
In Python 1.5, you can use the built-in function isinstance(obj, cls).
The following approaches can be used with earlier Python versions:
An unobvious method is to raise the object as an exception and to try to catch the exception with the class you're testing for:
def is_instance_of(the_instance, the_class): try: raise the_instance except the_class: return 1 except: return 0This technique can be used to distinguish "subclassness" from a collection of classes as well
try: raise the_instance except Audible: the_instance.play(largo) except Visual: the_instance.display(gaudy) except Olfactory: sniff(the_instance) except: raise ValueError, "dunno what to do with this!"This uses the fact that exception catching tests for class or subclass membership.
A different approach is to test for the presence of a class attribute that is presumably unique for the given class. For instance:
class MyClass: ThisIsMyClass = 1 ...
def is_a_MyClass(the_instance): return hasattr(the_instance, 'ThisIsMyClass')This version is easier to inline, and probably faster (inlined it is definitely faster). The disadvantage is that someone else could cheat:
class IntruderClass: ThisIsMyClass = 1 # Masquerade as MyClass ...but this may be seen as a feature (anyway, there are plenty of other ways to cheat in Python). Another disadvantage is that the class must be prepared for the membership test. If you do not "control the source code" for the class it may not be advisable to modify the class to support testability.
Edit this entry / Log info / Last changed on Fri Jan 2 15:16:04 1998 by GvR
from string import upper
class UpperOut: def __init__(self, outfile): self.__outfile = outfile def write(self, str): self.__outfile.write( upper(str) ) def __getattr__(self, name): return getattr(self.__outfile, name)Here the UpperOut class redefines the write method to convert the argument string to upper case before calling the underlying self.__outfile.write method, but all other methods are delegated to the underlying self.__outfile object. The delegation is accomplished via the "magic" __getattr__ method. Please see the language reference for more information on the use of this method.
Note that for more general cases delegation can get trickier. Particularly when attributes must be set as well as gotten 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.
Edit this entry / Log info / Last changed on Wed Aug 13 07:11:24 1997 by aaron watters
http://pyunit.sourceforge.net/For standalone testing, it helps to write the program so that it may be easily tested by using good modular design. In particular your program should have almost all functionality encapsulated in either functions or class methods -- and this sometimes has the surprising and delightful effect of making the program run faster (because local variable accesses are faster than global accesses). Furthermore the program should avoid depending on mutating global variables, since this makes testing much more difficult to do.
The "global main logic" of your program may be as simple as
if __name__=="__main__": main_logic()at the bottom of the main module of your program.
Once your program is organized as a tractable collection of functions and class behaviours you should write test functions that exercise the behaviours. A test suite can be associated with each module which automates a sequence of tests. This sounds like a lot of work, but since Python is so terse and flexible it's surprisingly easy. You can make coding much more pleasant and fun by writing your test functions in parallel with the "production code", since this makes it easy to find bugs and even design flaws earlier.
"Support modules" that are not intended to be the main module of a program may include a "test script interpretation" which invokes a self test of the module.
if __name__ == "__main__": self_test()Even programs that interact with complex external interfaces may be tested when the external interfaces are unavailable by using "fake" interfaces implemented in Python. For an example of a "fake" interface, the following class defines (part of) a "fake" file interface:
import string testdata = "just a random sequence of characters"
class FakeInputFile: data = testdata position = 0 closed = 0
def read(self, n=None): self.testclosed() p = self.position if n is None: result= self.data[p:] else: result= self.data[p: p+n] self.position = p + len(result) return result
def seek(self, n, m=0): self.testclosed() last = len(self.data) p = self.position if m==0: final=n elif m==1: final=n+p elif m==2: final=len(self.data)+n else: raise ValueError, "bad m" if final<0: raise IOError, "negative seek" self.position = final
def isatty(self): return 0
def tell(self): return self.position
def close(self): self.closed = 1
def testclosed(self): if self.closed: raise IOError, "file closed"Try f=FakeInputFile() and test out its operations.
Edit this entry / Log info / Last changed on Mon Jun 3 01:12:10 2002 by Neal Norwitz
A = [[None] * 2] * 3This makes a list containing 3 references to the same list of length two. Changes to one row will show in all rows, which is probably not what you want. The following works much better:
A = [None]*3 for i in range(3): A[i] = [None] * 2This generates a list containing 3 different lists of length two.
If you feel weird, you can also do it in the following way:
w, h = 2, 3 A = map(lambda i,w=w: [None] * w, range(h))For Python 2.0 the above can be spelled using a list comprehension:
w,h = 2,3 A = [ [None]*w for i in range(h) ]
Edit this entry / Log info / Last changed on Thu Dec 28 12:18:35 2000 by Bjorn Pettersen
def st(List, Metric): def pairing(element, M = Metric): return (M(element), element) paired = map(pairing, List) paired.sort() return map(stripit, paired)
def stripit(pair): return pair[1]This technique, attributed to Randal Schwartz, sorts the elements of a list by a metric which maps each element to its "sort value". For example, if L is a list of string then
import string Usorted = st(L, string.upper)
def intfield(s): return string.atoi( string.strip(s[10:15] ) )
Isorted = st(L, intfield)Usorted gives the elements of L sorted as if they were upper case, and Isorted gives the elements of L sorted by the integer values that appear in the string slices starting at position 10 and ending at position 15. In Python 2.0 this can be done more naturally with list comprehensions:
tmp1 = [ (x.upper(), x) for x in L ] # Schwartzian transform tmp1.sort() Usorted = [ x[1] for x in tmp1 ]
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 Icmp(s1, s2): return cmp( intfield(s1), intfield(s2) )
Isorted = L[:] Isorted.sort(Icmp)but since this method computes intfield many times for each element of L, it is slower than the Schwartzian Transform.
Edit this entry / Log info / Last changed on Sat Jun 1 19:18:46 2002 by Neal Norwitz
The function list(seq) converts any sequence 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.
Edit this entry / Log info / Last changed on Sun Jun 14 14:18:53 1998 by Tim Peters
Edit this entry / Log info / Last changed on Mon Jan 8 17:26:18 2001 by Steve Holden
You can program the class's constructor to keep track of all instances, but unless you're very clever, this has the disadvantage that the instances never get deleted,because your list of all instances keeps a reference to them.
(The trick is to regularly inspect the reference counts of the instances you've retained, and if the reference count is below a certain level, remove it from the list. Determining that level is tricky -- it's definitely larger than 1.)
Edit this entry / Log info / Last changed on Tue May 27 23:52:16 1997 by GvR
regex.match('.*x',"x"*5000)will fail.
This is fixed in the re module introduced with Python 1.5; consult the Library Reference section on re for more information.
Edit this entry / Log info / Last changed on Thu Jul 30 12:35:49 1998 by A.M. Kuchling
handler(signum, frame)so it should be declared with two arguments:
def handler(signum, frame): ...
Edit this entry / Log info / Last changed on Wed May 28 09:29:08 1997 by GvR
x = 1 # make a global
def f(): print x # try to print the global ... for j in range(100): if q>3: x=4Any 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.
In such cases the solution is to insert an explicit global declaration at the start of the function, making it
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.
Edit this entry / Log info / Last changed on Mon Feb 12 15:52:12 2001 by Steve Holden
Using negative indices can be very convenient. For example if the string Line ends in a newline then Line[:-1] is all of Line except the newline.
Sadly the list builtin method L.insert does not observe negative indices. This feature could be considered a mistake but since existing programs depend on this feature it may stay around forever. L.insert for negative indices inserts at the start of the list. To get "proper" negative index behaviour use L[n:n] = [x] in place of the insert method.
Edit this entry / Log info / Last changed on Wed Aug 13 07:03:18 1997 by aaron watters
>>> list1 = ["what", "I'm", "sorting", "by"] >>> list2 = ["something", "else", "to", "sort"] >>> pairs = map(None, list1, list2) >>> pairs [('what', 'something'), ("I'm", 'else'), ('sorting', 'to'), ('by', 'sort')] >>> pairs.sort() >>> pairs [("I'm", 'else'), ('by', 'sort'), ('sorting', 'to'), ('what', 'something')] >>> result = pairs[:] >>> for i in xrange(len(result)): result[i] = result[i][1] ... >>> result ['else', 'sort', 'to', 'something']And if you didn't understand the question, please see the example above ;c). Note that "I'm" sorts before "by" because uppercase "I" comes before lowercase "b" in the ascii order. Also see 4.51.
In Python 2.0 this can be done like:
>>> 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'][Followup]
Someone asked, why not this for the last steps:
result = [] for p in pairs: result.append(p[1])This is much more legible. However, a quick test shows that it is almost twice as slow for long lists. Why? First of all, 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 apparently that costs quite a bit. Second, the expression "result.append" requires an extra attribute lookup. The attribute lookup could be done away with by rewriting as follows:
result = [] append = result.append for p in pairs: append(p[1])which gains back some speed, but is still considerably slower than the original solution, and hardly less convoluted.
Edit this entry / Log info / Last changed on Thu Dec 28 12:56:35 2000 by Bjorn Pettersen
Using 1.4, you can find out which methods a given object supports by looking at its __methods__ attribute:
>>> List = [] >>> List.__methods__ ['append', 'count', 'index', 'insert', 'remove', 'reverse', 'sort']
Edit this entry / Log info / Last changed on Thu Sep 16 14:56:42 1999 by Skip Montanaro
Yes. Here's a simple example that uses httplib.
#!/usr/local/bin/python
import httplib, sys, time
### build the query string qs = "First=Josephine&MI=Q&Last=Public"
### connect and send the server a path httpobj = httplib.HTTP('www.some-server.out-there', 80) httpobj.putrequest('POST', '/cgi-bin/some-cgi-script') ### now generate the rest of the HTTP headers... httpobj.putheader('Accept', '*/*') httpobj.putheader('Connection', 'Keep-Alive') httpobj.putheader('Content-type', 'application/x-www-form-urlencoded') httpobj.putheader('Content-length', '%d' % len(qs)) httpobj.endheaders() httpobj.send(qs) ### find out what the server said in response... reply, msg, hdrs = httpobj.getreply() if reply != 200: sys.stdout.write(httpobj.getfile().read())Note that in general for "url encoded posts" (the default) query strings must be "quoted" to, for example, change equals signs and spaces to an encoded form when they occur in name or value. Use urllib.quote to perform this quoting. For example to send name="Guy Steele, Jr.":
>>> from urllib import quote >>> x = quote("Guy Steele, Jr.") >>> x 'Guy%20Steele,%20Jr.' >>> query_string = "name="+x >>> query_string 'name=Guy%20Steele,%20Jr.'
Edit this entry / Log info / Last changed on Mon Jun 21 03:47:07 1999 by TAB
If you have initialized a new bsddb database but not written anything to it before the program crashes, you will often wind up with a zero-length file and encounter an exception the next time the file is opened.
Edit this entry / Log info / Last changed on Mon Jun 3 01:15:01 2002 by Neal Norwitz
The first is done by executing 'chmod +x scriptfile' or perhaps 'chmod 755 scriptfile'.
The second can be done in a number of way. The most straightforward way is to write
#!/usr/local/bin/pythonas the very first line of your file - or whatever the pathname is where the python interpreter is installed on your platform.
If you would like the script to be independent of where the python interpreter lives, you can use the "env" program. On almost all platforms, the following will work, assuming the python interpreter is in a directory on the user's $PATH:
#! /usr/bin/env pythonNote -- *don't* do this for CGI scripts. The $PATH variable for CGI scripts is often very minimal, so you need to use the actual absolute pathname of the interpreter.
Occasionally, a user's environment is so full that the /usr/bin/env program fails; or there's no env program at all. In that case, you can try the following hack (due to Alex Rezinsky):
#! /bin/sh """:" exec python $0 ${1+"$@"} """The disadvantage is that this defines the script's __doc__ string. However, you can fix that by adding
__doc__ = """...Whatever..."""
Edit this entry / Log info / Last changed on Mon Jan 15 09:19:16 2001 by Neal Norwitz
http://aspn.activestate.com/ASPN/Cookbook/Python/Recipe/52560Generally, if you don't mind reordering the List
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 (ie, they are all hashable) this is often faster
d = {} for x in List: d[x]=x List = d.values()Also, for extremely large lists you might consider more optimal alternatives to the first one. The second one is pretty good whenever it can be used.
Edit this entry / Log info / Last changed on Fri May 24 21:56:33 2002 by Tim Peters
Given the nature of freely available software, I have to add that this statement is not legally binding. The Python copyright notice contains the following disclaimer:
STICHTING MATHEMATISCH CENTRUM AND CNRI DISCLAIM ALL WARRANTIES WITH REGARD TO THIS SOFTWARE, INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO EVENT SHALL STICHTING MATHEMATISCH CENTRUM OR CNRI BE LIABLE FOR ANY SPECIAL, INDIRECT OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR PERFORMANCE OF THIS SOFTWARE.The good news is that if you encounter a problem, you have full source available to track it down and fix it!
Edit this entry / Log info / Last changed on Fri Apr 10 14:59:31 1998 by GvR
def method_map(objects, method, arguments): """method_map([a,b], "flog", (1,2)) gives [a.flog(1,2), b.flog(1,2)]""" nobjects = len(objects) methods = map(getattr, objects, [method]*nobjects) return map(apply, methods, [arguments]*nobjects)It's generally a good idea to get to know the mysteries of map and apply and getattr and the other dynamic features of Python.
Edit this entry / Log info / Last changed on Mon Jan 5 14:21:14 1998 by Aaron Watters
import random
random.random()This returns a random floating point number in the range [0, 1).
There are also many other specialized generators in this module, such as
randrange(a, b) chooses an integer in the range [a, b) uniform(a, b) chooses a floating point number in the range [a, b) normalvariate(mean, sdev) sample from normal (Gaussian) distributionSome higher-level functions operate on sequences directly, such as
choice(S) chooses random element from a given sequence shuffle(L) shuffles a list in-place, i.e. permutes it randomlyThere's also a class, Random, which you can instantiate to create independent multiple random number generators.
All this is documented in the library reference manual. Note that the module "whrandom" is obsolete.
Edit this entry / Log info / Last changed on Mon Jun 3 01:16:51 2002 by Neal Norwitz
ftp://ftp.python.org/pub/python/contrib/sio-151.zip http://www.python.org/ftp/python/contrib/sio-151.zipFor DOS, try Hans Nowak's Python-DX, which supports this, at:
http://www.cuci.nl/~hnowak/For Unix, see a usenet post by Mitch Chapman:
http://groups.google.com/groups?selm=34A04430.CF9@ohioee.comFor Win32, POSIX(Linux, BSD, *), Jython, Chris':
http://pyserial.sourceforge.net
Edit this entry / Log info / Last changed on Tue Jul 2 21:11:07 2002 by Chris Liechti
Quoting Fredrik Lundh from the mailinglist:
Well, the Tk button widget keeps a reference to the internal photoimage object, but Tkinter does not. So when the last Python reference goes away, Tkinter tells Tk to release the photoimage. But since the image is in use by a widget, Tk doesn't destroy it. Not completely. It just blanks the image, making it completely transparent...
And yes, there was a bug in the keyword argument handling in 1.4 that kept an extra reference around in some cases. And when Guido fixed that bug in 1.5, he broke quite a few Tkinter programs...
Edit this entry / Log info / Last changed on Tue Feb 3 11:31:03 1998 by Case Roole
Fredrik Lundh (fredrik@pythonware.com) explains (on the python-list):
There are (at least) three kinds of modules in Python: 1) modules written in Python (.py); 2) modules written in C and dynamically loaded (.dll, .pyd, .so, .sl, etc); 3) modules written in C and linked with the interpreter; to get a list of these, type:
import sys print sys.builtin_module_names
Edit this entry / Log info / Last changed on Tue Feb 3 13:55:33 1998 by Aaron Watters
import sys, smtplib
fromaddr = raw_input("From: ") toaddrs = raw_input("To: ").split(',') print "Enter message, end with ^D:" msg = '' while 1: line = sys.stdin.readline() if not line: break msg = msg + line
# The actual mail send server = smtplib.SMTP('localhost') server.sendmail(fromaddr, toaddrs, msg) server.quit()If the local host doesn't have an SMTP listener, you need to find one. The simple method is to ask the user. Alternately, you can use the DNS system to find the mail gateway(s) responsible for the source address.
A Unix-only alternative uses sendmail. The location of the sendmail program varies between systems; sometimes it is /usr/lib/sendmail, sometime /usr/sbin/sendmail. The sendmail manual page will help you out. Here's some sample code:
SENDMAIL = "/usr/sbin/sendmail" # sendmail location import os p = os.popen("%s -t -i" % SENDMAIL, "w") p.write("To: cary@ratatosk.org\n") p.write("Subject: test\n") p.write("\n") # blank line separating headers from body p.write("Some text\n") p.write("some more text\n") sts = p.close() if sts != 0: print "Sendmail exit status", sts
Edit this entry / Log info / Last changed on Mon Jun 3 07:05:12 2002 by Matthias Urlichs
To prevent the TCP connect from blocking, you can set the socket to non-blocking mode. Then when you do the connect(), you will either connect immediately (unlikely) or get an exception that contains the errno. errno.EINPROGRESS indicates that the connection is in progress, but hasn't finished yet. Different OSes will return different errnos, so you're going to have to check. I can tell you that different versions of Solaris return different errno values.
In Python 1.5 and later, you can use connect_ex() to avoid creating an exception. It will just return the errno value.
To poll, you can call connect_ex() again later -- 0 or errno.EISCONN indicate that you're connected -- or you can pass this socket to select (checking to see if it is writeable).
Edit this entry / Log info / Last changed on Tue Feb 24 21:30:45 1998 by GvR
>>> a = 010To verify that this works, you can type "a" and hit enter while in the interpreter, which will cause Python to spit out the current value of "a" in decimal:
>>> a 8Hexadecimal 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
Edit this entry / Log info / Last changed on Tue Mar 3 12:53:16 1998 by GvR
There are several solutions; some involve using curses, which is a pretty big thing to learn. Here's a solution without curses, due to Andrew Kuchling (adapted from code to do a PGP-style randomness pool):
import termios, sys, os fd = sys.stdin.fileno() old = termios.tcgetattr(fd) new = termios.tcgetattr(fd) new[3] = new[3] & ~termios.ICANON & ~termios.ECHO new[6][termios.VMIN] = 1 new[6][termios.VTIME] = 0 termios.tcsetattr(fd, termios.TCSANOW, new) s = '' # We'll save the characters typed and add them to the pool. try: while 1: c = os.read(fd, 1) print "Got character", `c` s = s+c finally: termios.tcsetattr(fd, termios.TCSAFLUSH, old)You need the termios module for any of this to work, and I've only tried it on Linux, though it should work elsewhere. It turns off stdin's echoing and disables canonical mode, and then reads a character at a time from stdin, noting the time after each keystroke.
Edit this entry / Log info / Last changed on Thu Oct 24 00:36:56 2002 by chris
Where 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", iThis 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.
Edit this entry / Log info / Last changed on Mon Apr 20 11:55:55 1998 by GvR
class Account: def __init__(self, **kw): self.accountType = kw.get('accountType') self.balance = kw.get('balance')
class CheckingAccount(Account): def __init__(self, **kw): kw['accountType'] = 'checking' apply(Account.__init__, (self,), kw)
myAccount = CheckingAccount(balance=100.00)In Python 2.0 you can call it directly using the new ** syntax:
class CheckingAccount(Account): def __init__(self, **kw): kw['accountType'] = 'checking' Account.__init__(self, **kw)or more generally:
>>> def f(x, *y, **z): ... print x,y,z ... >>> Y = [1,2,3] >>> Z = {'foo':3,'bar':None} >>> f('hello', *Y, **Z) hello (1, 2, 3) {'foo': 3, 'bar': None}
Edit this entry / Log info / Last changed on Thu Dec 28 13:04:01 2000 by Bjorn Pettersen
It can be found in the FTP contrib area on python.org or on the Starship. Use the search engines there to locate the latest version.
It might also be useful to consider DocumentTemplate, which offers clear separation between Python code and HTML code. DocumentTemplate is part of the Bobo objects publishing system (http:/www.digicool.com/releases) but can be used independantly of course!
Edit this entry / Log info / Last changed on Fri Aug 28 09:54:58 1998 by GvR
http://starship.python.net/crew/danilo/
It can create HTML from the doc strings in your Python source code.
Edit this entry / Log info / Last changed on Mon Oct 7 17:15:51 2002 by Phil Rittenhouse
For example, the following code reads two 2-byte integers and one 4-byte integer in big-endian format from a file:
import struct
f = open(filename, "rb") # Open in binary mode for portability s = f.read(8) x, y, z = struct.unpack(">hhl", s)The '>' in the format string forces bin-endian data; the letter 'h' reads one "short integer" (2 bytes), and 'l' reads one "long integer" (4 bytes) from the string.
For data that is more regular (e.g. a homogeneous list of ints or floats), you can also use the array module, also documented in the library reference.
Edit this entry / Log info / Last changed on Wed Oct 7 09:16:45 1998 by GvR
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 taketocus option).
Edit this entry / Log info / Last changed on Fri Jun 12 09:37:33 1998 by GvR
Starting with Python 1.5, the crypt module is disabled by default. In order to enable it, you must go into the Python source tree and edit the file Modules/Setup to enable it (remove a '#' sign in front of the line starting with '#crypt'). Then rebuild. You may also have to add the string '-lcrypt' to that same line.
Edit this entry / Log info / Last changed on Wed Aug 5 08:57:09 1998 by GvR
Edit this entry / Log info / Last changed on Tue Sep 29 09:50:27 1998 by Joseph VanAndel
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).
Edit this entry / Log info / Last changed on Wed Jan 20 17:35:01 1999 by Martin v. Löwis
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.
STATIC DATA
For example,
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.countc.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,
self.count = 42creates a new and unrelated instance vrbl named "count" in self's own dict. So rebinding of a class-static data name needs the
C.count = 314form whether inside a method or not.
STATIC METHODS
Static methods (as opposed to static data) are unnatural in Python, because
C.getcountreturns an unbound method object, which can't be invoked without supplying an instance of C as the first argument.
The intended way to get the effect of a static method is via a module-level function:
def getcount(): return C.countIf your code is structured so as to define one class (or tightly related class hierarchy) per module, this supplies the desired encapsulation.
Several tortured schemes for faking static methods can be found by searching DejaNews. Most people feel such cures are worse than the disease. Perhaps the least obnoxious is due to Pekka Pessi (mailto:ppessi@hut.fi):
# helper class to disguise function objects class _static: def __init__(self, f): self.__call__ = f
class C: count = 0
def __init__(self): C.count = C.count + 1
def getcount(): return C.count getcount = _static(getcount)
def sum(x, y): return x + y sum = _static(sum)
C(); C() c = C() print C.getcount() # prints 3 print c.getcount() # prints 3 print C.sum(27, 15) # prints 42
Edit this entry / Log info / Last changed on Thu Jan 21 21:35:38 1999 by Tim Peters
__import__('x.y.z').y.zFor more realistic situations, you may have to do something like
m = __import__(s) for i in string.split(s, ".")[1:]: m = getattr(m, i)
Edit this entry / Log info / Last changed on Thu Jan 28 11:01:43 1999 by GvR
If you write a simple test program like this:
import thread def run(name, n): for i in range(n): print name, i for i in range(10): thread.start_new(run, (i, 100))none of the threads seem to run! The reason is that as soon as the main thread exits, all threads are killed.
A simple fix is to add a sleep to the end of the program, sufficiently long for all threads to finish:
import thread, time def run(name, n): for i in range(n): print name, i for i in range(10): thread.start_new(run, (i, 100)) time.sleep(10) # <----------------------------!But now (on many platforms) the threads don't run in parallel, but appear to run sequentially, one at a time! The reason is that the OS thread scheduler doesn't start a new thread until the previous thread is blocked.
A simple fix is to add a tiny sleep to the start of the run function:
import thread, time def run(name, n): time.sleep(0.001) # <---------------------! for i in range(n): print name, i for i in range(10): thread.start_new(run, (i, 100)) time.sleep(10)Some more hints:
Instead of using a time.sleep() call at the end, it's better to use some kind of semaphore mechanism. One idea is to use a the Queue module to create a queue object, let each thread append a token to the queue when it finishes, and let the main thread read as many tokens from the queue as there are threads.
Use the threading module instead of the thread module. It's part of Python since version 1.5.1. It takes care of all these details, and has many other nice features too!
Edit this entry / Log info / Last changed on Fri Feb 7 16:21:55 2003 by GvR
For most file objects f you create in Python via the builtin "open" function, f.close() marks the Python file object as being closed from Python's point of view, and also arranges to close the underlying C stream. This happens automatically too, in f's destructor, when f becomes garbage.
But stdin, stdout and stderr are treated specially by Python, because of the special status also given to them by C: doing
sys.stdout.close() # ditto for stdin and stderrmarks the Python-level file object as being closed, but does not close the associated C stream (provided sys.stdout is still bound to its default value, which is the stream C also calls "stdout").
To close the underlying C stream for one of these three, you should first be sure that's what you really want to do (e.g., you may confuse the heck out of extension modules trying to do I/O). If it is, use os.close:
os.close(0) # close C's stdin stream os.close(1) # close C's stdout stream os.close(2) # close C's stderr stream
Edit this entry / Log info / Last changed on Sat Apr 17 02:22:35 1999 by Tim Peters
A global interpreter lock (GIL) is used internally to ensure that only one thread runs in the Python VM at a time. In general, Python offers to switch among threads only between bytecode instructions (how frequently it offers to switch can be set via sys.setcheckinterval). Each bytecode instruction-- and all the C implementation code reached from it --is therefore atomic.
In theory, this means an exact accounting requires an exact understanding of the PVM bytecode implementation. In practice, it means that operations on shared vrbls of builtin data types (ints, lists, dicts, etc) that "look atomic" really are.
For example, these are atomic (L, L1, L2 are lists, D, D1, D2 are dicts, x, y are objects, i, j are ints):
L.append(x) L1.extend(L2) x = L[i] x = L.pop() L1[i:j] = L2 L.sort() x = y x.field = y D[x] = y D1.update(D2) D.keys()These aren't:
i = i+1 L.append(L[-1]) L[i] = L[j] D[x] = D[x] + 1Note: operations that replace other objects may invoke those other objects' __del__ method when their reference count reaches zero, and that can affect things. This is especially true for the mass updates to dictionaries and lists. When in doubt, use a mutex!
Edit this entry / Log info / Last changed on Fri Feb 7 16:21:03 2003 by GvR
>>> s = "Hello, world" >>> a = list(s) >>> print a ['H', 'e', 'l', 'l', 'o', ',', ' ', 'w', 'o', 'r', 'l', 'd'] >>> a[7:] = list("there!") >>> import string >>> print string.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'
Edit this entry / Log info / Last changed on Tue May 18 01:22:47 1999 by Andrew Dalke
def f1(a, *b, **c): ...A: In Python 2.0 and above:
def f2(x, *y, **z): ... z['width']='14.3c' ... f1(x, *y, **z)
Note: y can be any sequence (e.g., list or tuple) and z must be a dict.
A: For versions prior to 2.0, use 'apply', like:
def f2(x, *y, **z): ... z['width']='14.3c' ... apply(f1, (x,)+y, z)
Edit this entry / Log info / Last changed on Mon Jun 3 07:20:56 2002 by Matthias Urlichs
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. If you have such needs you can 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. (It won't have any effect on the pprint module and does not transparently handle values that are or contain dictionaries.
Edit this entry / Log info / Last changed on Thu Sep 16 17:31:06 1999 by Skip Montanaro
Edit this entry / Log info / Last changed on Sat Dec 4 16:04:00 1999 by TAB
Edit this entry / Log info / Last changed on Tue May 28 20:40:37 2002 by GvR
import termios, fcntl, sys, os fd = sys.stdin.fileno()
oldterm = termios.tcgetattr(fd) newattr = termios.tcgetattr(fd) newattr[3] = newattr[3] & ~termios.ICANON & ~termios.ECHO termios.tcsetattr(fd, termios.TCSANOW, newattr)
oldflags = fcntl.fcntl(fd, fcntl.F_GETFL) fcntl.fcntl(fd, fcntl.F_SETFL, oldflags | os.O_NONBLOCK)
try: while 1: try: c = sys.stdin.read(1) print "Got character", `c` except IOError: pass finally: termios.tcsetattr(fd, termios.TCSAFLUSH, oldterm) fcntl.fcntl(fd, fcntl.F_SETFL, oldflags)
You need the termios and the fcntl module for any of this to work, and I've only tried it on Linux, though it should work elsewhere.
In this code, characters are read and printed one at a time.
termios.tcsetattr() turns off stdin's echoing and disables canonical mode. fcntl.fnctl() is used to obtain stdin's file descriptor flags and modify them for non-blocking mode. Since reading stdin when it is empty results in an IOError, this error is caught and ignored.
Edit this entry / Log info / Last changed on Thu Oct 24 00:39:06 2002 by chris
-----------------------------------------------------------------------
rstrip() is too greedy, it strips all trailing white spaces. splitlines() takes ControlM as line boundary. Consider these strings as input: "python python \r\n" "python\rpython\r\n" "python python \r\r\r\n" The results from rstrip()/splitlines() are perhaps not what we want.
It seems re can perform this task.
#!/usr/bin/python # requires python2
import re, os, StringIO
lines=StringIO.StringIO( "The Python Programming Language\r\n" "The Python Programming Language \r \r \r\r\n" "The\rProgramming\rLanguage\r\n" "The\rProgramming\rLanguage\r\r\r\r\n" "The\r\rProgramming\r\rLanguage\r\r\r\r\n" )
ln=re.compile("(?:[\r]?\n|\r)$") # dos:\r\n, unix:\n, mac:\r, others: unknown # os.linesep does not work if someone ftps(in binary mode) a dos/mac text file # to your unix box #ln=re.compile(os.linesep + "$")
while 1: s=lines.readline() if not s: break print "1.(%s)" % `s.rstrip()` print "2.(%s)" % `ln.sub( "", s, 1)` print "3.(%s)" % `s.splitlines()[0]` print "4.(%s)" % `s.splitlines()` print
lines.close()
Edit this entry / Log info / Last changed on Wed Aug 8 09:51:34 2001 by Crystal
", ".join(['1', '2', '4', '8', '16'])which gives the result
"1, 2, 4, 8, 16"There are two usual arguments against this usage.
The first runs along the lines of: "It looks really ugly using a method of a string literal (string constant)", to which the answer is that it might, but a string literal is just a fixed value. If the methods are to be allowed on names bound to strings there is no logical reason to make them unavailable on literals. Get over it!
The second objection is typically cast as: "I am really telling a sequence to join its members together with a string constant". Sadly, you aren't. For some reason there seems to be much less difficulty with having split() as a string method, since in that case it is easy to see that
"1, 2, 4, 8, 16".split(", ")is an instruction to a string literal to return the substrings delimited by the given separator (or, by default, arbitrary runs of white space). In this case a Unicode string returns a list of Unicode strings, an ASCII string returns a list of ASCII strings, and everyone is happy.
join() is a string method because in using it you are telling the separator string to iterate over an arbitrary sequence, forming string representations of each of the elements, and inserting itself between the elements' representations. This method can be used with any argument which obeys the rules for sequence objects, inluding any new classes you might define yourself.
Because this is a string method it can work for Unicode strings as well as plain ASCII strings. If join() were a method of the sequence types then the sequence types would have to decide which type of string to return depending on the type of the separator.
If none of these arguments persuade you, then for the moment you can continue to use the join() function from the string module, which allows you to write
string.join(['1', '2', '4', '8', '16'], ", ")You will just have to try and forget that the string module actually uses the syntax you are compaining about to implement the syntax you prefer!
Edit this entry / Log info / Last changed on Fri Aug 2 15:51:58 2002 by Steve Holden
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.
Edit this entry / Log info / Last changed on Thu Mar 8 03:53:39 2001 by Steve Holden
http://www.python.org/doc/current/tut/node14.htmlPeople are often very surprised by results like this:
>>> 1.2-1.0 0.199999999999999996And think it is a bug in Python. It's not. It's a problem caused by the internal representation of a floating point number. A floating point number is stored as a fixed number of binary digits.
In decimal math, there are many numbers that can't be represented with a fixed number of decimal digits, i.e. 1/3 = 0.3333333333.......
In the binary case, 1/2 = 0.1, 1/4 = 0.01, 1/8 = 0.001, etc. There are a lot of numbers that can't be represented. The digits are cut off at some point.
Since Python 1.6, a floating point's repr() function prints as many digits are necessary to make eval(repr(f)) == f true for any float f. The str() function prints the more sensible number that was probably intended:
>>> 0.2 0.20000000000000001 >>> print 0.2 0.2Again, this has nothing to do with Python, but with the way the underlying C platform handles floating points, and ultimately with the inaccuracy you'll always have when writing down numbers of fixed number of digit strings.
One of the consequences of this is that it is dangerous to compare the result of some computation to a float with == ! Tiny inaccuracies may mean that == fails.
Instead try something like this:
epsilon = 0.0000000000001 # Tiny allowed error expected_result = 0.4
if expected_result-epsilon <= computation() <= expected_result+epsilon: ...
Edit this entry / Log info / Last changed on Mon Apr 1 22:18:47 2002 by Fred Drake
Many Linux systems now have all three versions of Berkeley DB available. If you are migrating from version 1 to a newer version use db_dump185 to dump a plain text version of the database. If you are migrating from version 2 to version 3 use db2_dump to create a plain text version of the database. In either case, use db_load to create a new native database for the latest version installed on your computer. If you have version 3 of Berkeley DB installed, you should be able to use db2_load to create a native version 2 database.
You should probably move away from Berkeley DB version 1 files because the hash file code contains known bugs that can corrupt your data.
Edit this entry / Log info / Last changed on Wed Aug 29 16:04:29 2001 by Skip Montanaro
The rest of this answer is largely a matter of personal preference, but here's what some newsgroup posters said (thanks to all who responded)
In general, don't use
from modulename import *Doing so clutters the importer's namespace. Some avoid this idiom even with the few modules that were designed to be imported in this manner. (Modules designed in this manner include Tkinter, thread, and wxPython.)
Import modules at the top of a file, one module per line. 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.
Move imports into a local scope (such as at the top of a function definition) if there are a lot of imports, and you're trying to avoid the cost (lots of initialization time) of many imports. 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 that loading a module multiple times is virtually free (a couple of dictionary lookups). Even if the module name has gone out of scope, the module is probably available in sys.modules. Thus, there isn't really anything wrong with putting no imports at the module level (if they aren't needed) and putting all of the imports at the function level.
It is sometimes necessary to move imports to a function or class to avoid problems with circular imports. Gordon 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, (the first module is busy importing the 2nd).In this case, if the 2nd 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.
If only instances of a specific class uses 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.
Edit this entry / Log info / Last changed on Sat Aug 4 04:44:47 2001 by TAB
You can get PyChecker from: http://pychecker.sf.net.
Edit this entry / Log info / Last changed on Fri Aug 10 15:42:11 2001 by Neal
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 instance, 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.
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
If you normally use a character set encoding other than US-ASCII and only need to handle data in that encoding, the simplest way to fix the problem may be simply to set the encoding in sitecustomize.py. The following code is just a modified version of the encoding setup code from site.py with the relevant lines uncommented.
# Set the string encoding used by the Unicode implementation. # The default is 'ascii' encoding = "ascii" # <= CHANGE THIS if you wish
# Enable to support locale aware default string encodings. import locale loc = locale.getdefaultlocale() if loc[1]: encoding = loc[1] if encoding != "ascii": import sys sys.setdefaultencoding(encoding)
Also 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.
Edit this entry / Log info / Last changed on Sat Apr 13 04:45:41 2002 by Skip Montanaro
* Use a dictionary pre-loaded with strings and 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() can be dangerous. If you don't have absolute control over the contents of the string, all sorts of things could happen...
Edit this entry / Log info / Last changed on Thu Mar 21 08:14:58 2002 by Erno Kuusela
try: value = dict[key] except KeyError: dict[key] = getvalue(key) value = dict[key]This idiom only made sense when you expected the dict to have the key 95% of the time or more; other times, you coded it like this:
if dict.has_key(key): value = dict[key] else: dict[key] = getvalue(key) value = dict[key]In Python 2.0 and higher, of course, you can code this as
value = dict.setdefault(key, getvalue(key))However this evaluates getvalue(key) always, regardless of whether it's needed or not. So if it's slow or has a side effect you should use one of the above variants.
Edit this entry / Log info / Last changed on Mon Dec 9 10:12:30 2002 by Yeti
config.py:
passmod.py:
import config config.x = 1main.py:
import config import mod print config.xNote that using a module is also the basis for implementing the Singleton design pattern, for the same reason.
Edit this entry / Log info / Last changed on Tue Apr 23 23:07:19 2002 by Aahz
largeString = 'z' * (100 * 1024) myPickle = cPickle.dumps(largeString, 1)
Edit this entry / Log info / Last changed on Thu Aug 22 19:54:25 2002 by Aahz
If instead the name of the undefined symbol starts with PyUnicodeUCS4_, the problem is the same by the relationship is reversed: 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, provides 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 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.
Edit this entry / Log info / Last changed on Tue Aug 27 15:00:17 2002 by Fred Drake
I have a module and I wish to generate a .pyc file. How do I do it? Everything I read says that generation of a .pyc file is "automatic", but I'm not getting anywhere.
ANSWER:
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.
However, in most cases, that's not the problem.
Creation of a .pyc file is "automatic" if you are importing a module and Python has the ability (permissions, free space, etc...) to write the compiled module back to the directory. But note that running Python on a top level script is not considered an import and so no .pyc will be created automatically. 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 isn't imported.
If you need to create abc.pyc -- that is, to create a .pyc file for a module that is not imported -- you can. (Look up the py_compile and compileall modules in the Library Reference.)
You can manually compile any module using the "py_compile" 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, which can also be run straight from the command line.
You can do it from the shell (or DOS) prompt by entering:
python compile.py abc.pyor
python compile.py *Or you can write a script to do it on a list of filenames that you enter.
import sys from py_compile import compile
if len(sys.argv) <= 1: sys.exit(1)
for file in sys.argv[1:]: compile(file)ACKNOWLEDGMENTS:
Steve Holden, David Bolen, Rich Somerfield, Oleg Broytmann, Steve Ferg
Edit this entry / Log info / Last changed on Wed Feb 12 15:58:25 2003 by Stephen Ferg
There's more information on this in each of the Python books: Programming Python, Internet Programming with Python, and Das Python-Buch (in German).
Edit this entry / Log info / Last changed on Mon Dec 10 05:18:57 2001 by Fred L. Drake, Jr.
Edit this entry / Log info / Last changed on Fri May 23 20:08:14 1997 by Bill Tutt
Edit this entry / Log info / Last changed on Wed May 21 22:23:18 1997 by David Ascher
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 for example interfacing with any kind of Python sequence (e.g. lists and tuples) using calls like PySequence_Length(), PySequence_GetItem(), etc.) as well as many other useful protocols.
Edit this entry / Log info / Last changed on Wed May 21 22:34:20 1997 by David Ascher
Edit this entry / Log info / Last changed on Thu Jul 31 18:15:29 1997 by Guido van Rossum
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 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)".
Edit this entry / Log info / Last changed on Thu Jun 6 16:15:46 2002 by Neal Norwitz
In Python code, define an object that supports the "write()" method. Redirect sys.stdout and sys.stderr to this object. 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!
Edit this entry / Log info / Last changed on Wed Dec 16 18:34:25 1998 by Richard Jones
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.
Edit this entry / Log info / Last changed on Wed May 21 22:56:40 1997 by david ascher
A useful automated approach (which also works for C) is SWIG: http://www.swig.org/.
Edit this entry / Log info / Last changed on Fri Oct 15 05:14:01 1999 by Sjoerd Mullender
Remove lines:
#include "allobjects.h" #include "modsupport.h"And insert instead:
#include "Python.h"You may also need to add
#include "rename2.h"if the module uses "old names".
This may happen with other ancient python modules as well, and the same fix applies.
Edit this entry / Log info / Last changed on Sun Dec 21 02:03:35 1997 by GvR
Edit this entry / Log info / Last changed on Tue Jun 24 15:54:01 1997 by aaron watters
Edit this entry / Log info / Last changed on Tue Jan 26 13:44:04 1999 by A.M. Kuchling
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 will be raised.
Edit this entry / Log info / Last changed on Thu Mar 25 07:16:08 1999 by Mark Hammond
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() (in a separate thread maybe) 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 (then the input is incomplete). 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 fine - 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 "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); }
Edit this entry / Log info / Last changed on Wed Mar 15 09:47:24 2000 by Alex Farber
In your .gdbinit file (or interactively), add the command
br _PyImport_LoadDynamicModule
$ 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
Edit this entry / Log info / Last changed on Fri Oct 20 11:10:32 2000 by Joe VanAndel
Edit this entry / Log info / Last changed on Sun Jan 14 18:03:51 2001 by douglas orr
You need to be careful when instantiating immutable types like integers or strings. See http://www.amk.ca/python/2.2/, section 2, for details.
Prior to version 2.2, Python (like Java) insisted that there are first-class and second-class objects (the former are types, the latter classes), and never the twain shall meet.
The library has, however, done a good job of providing class wrappers for the more commonly desired objects (see UserDict, UserList and UserString for examples), and more are always welcome if you happen to be in the mood to write code. These wrappers still exist in Python 2.2.
Edit this entry / Log info / Last changed on Mon Jun 10 15:14:07 2002 by Matthias Urlichs
Since there are no begin/end brackets there cannot be a disagreement between grouping perceived by the parser and the human reader. I remember long ago seeing a C fragment like this:
if (x <= y) x++; y--; z++;and staring a long time at it wondering why y was being decremented even for x > y... (And I wasn't a C newbie then either.)
Since there are no begin/end brackets, Python is much less prone to coding-style conflicts. In C there are loads of different ways to place the braces (including the choice whether to place braces around single statements in certain cases, for consistency). If you're used to reading (and writing) code that uses one style, you will feel at least slightly uneasy when reading (or being required to write) another style. Many coding styles place begin/end brackets on a line by themself. This makes programs considerably longer and wastes valuable screen space, making it harder to get a good overview over a program. Ideally, a function should fit on one basic tty screen (say, 20 lines). 20 lines of Python are worth a LOT more than 20 lines of C. This is not solely due to the lack of begin/end brackets (the lack of declarations also helps, and the powerful operations of course), but it certainly helps!
Edit this entry / Log info / Last changed on Wed May 21 16:00:15 1997 by GvR
Edit this entry / Log info / Last changed on Tue Jan 2 03:05:25 2001 by Moshe Zadka
It is also convenient to have a function that can readily be applied to an amorphous collection of objects when you use the functional features of Python (map(), apply() et al).
In fact, implementing len(), max(), min() as a built-in function is actually less code than implementing them as methods for each type. One can quibble about individual cases but it's a part of Python, and it's too late to change such things fundamentally now. The functions have to remain to avoid massive code breakage.
Note that for string operations Python has moved from external functions (the string module) to methods. However, len() is still a function.
Edit this entry / Log info / Last changed on Thu May 30 14:08:58 2002 by Steve Holden
This is caused by the relatively late addition of (user-defined) classes to the language -- the implementation framework doesn't easily allow it. See the answer to question 4.2 for a work-around. This may be fixed in the (distant) future.
Edit this entry / Log info / Last changed on Thu May 23 02:53:22 2002 by Neal Norwitz
First, it makes it more obvious that you are using a method or instance attribute instead of a local variable. Reading "self.x" or "self.meth()" makes it absolutely clear that an instance variable or method is used even if you don't know the class definition by heart. In C++, you can sort of tell by the lack of a local variable declaration (assuming globals are rare or easily recognizable) -- but in Python, there are no local variable declarations, so you'd have to look up the class definition to be sure.
Second, it means that no special syntax is necessary if you want to explicitly reference or call the method from a particular class. In C++, if you want to use a method from base class that is overridden in a derived class, you have to use the :: operator -- in Python you can write baseclass.methodname(self, <argument list>). This is particularly useful for __init__() methods, and in general in cases where a derived class method wants to extend the base class method of the same name and thus has to call the base class method somehow.
Lastly, for instance variables, it solves a syntactic problem with assignment: since local variables in Python are (by definition!) those variables to which a value assigned in a function body (and that aren't explicitly declared global), there has to be some way to tell the interpreter that an assignment was meant to assign to an instance variable instead of to a local variable, and it should preferably be syntactic (for efficiency reasons). C++ does this through declarations, but Python doesn't have declarations and it would be a pity having to introduce them just for this purpose. Using the explicit "self.var" solves this nicely. Similarly, for using instance variables, having to write "self.var" means that references to unqualified names inside a method don't have to search the instance's directories.
Edit this entry / Log info / Last changed on Fri Jan 12 08:01:50 2001 by Steve Holden
Answer 2: Fortunately, there is Stackless Python, which has a completely redesigned interpreter loop that avoids the C stack. It's still experimental but looks very promising. Although it is binary compatible with standard Python, it's still unclear whether Stackless will make it into the core -- maybe it's just too revolutionary. Stackless Python currently lives here: http://www.stackless.com. A microthread implementation that uses it can be found here: http://world.std.com/~wware/uthread.html.
Edit this entry / Log info / Last changed on Sat Apr 15 08:18:16 2000 by Just van Rossum
However, in Python, this is not a serious problem. Unlike lambda forms in other languages, where they add functionality, Python lambdas are only a shorthand notation if you're too lazy to define a function.
Functions are already first class objects in Python, and can be declared in a local scope. Therefore the only advantage of using a lambda form instead of a locally-defined function is that you don't need to invent a name for the function -- but that's just a local variable to which the function object (which is exactly the same type of object that a lambda form yields) is assigned!
Edit this entry / Log info / Last changed on Sun Jun 14 14:15:17 1998 by Tim Peters
Edit this entry / Log info / Last changed on Thu Mar 21 05:20:56 2002 by Erno Kuusela
Edit this entry / Log info / Last changed on Thu Mar 21 05:22:04 2002 by Erno Kuusela
for k in d: ...There are also methods returning iterators over the values and items:
for k in d.iterkeys(): # same as above for v in d.itervalues(): # iterate over values for k, v in d.iteritems(): # iterate over itemsAll these require that you do not modify the dictionary during the loop.
For previous Python versions, the following defense should do:
Have you tried it? I bet it's fast enough for your purposes! In most cases such a list takes only a few percent of the space occupied by the dictionary. Apart from the fixed header, the list needs only 4 bytes (the size of a pointer) per key. A dictionary uses 12 bytes per key plus between 30 and 70 percent hash table overhead, plus the space for the keys and values. By necessity, all keys are distinct objects, and a string object (the most common key type) costs at least 20 bytes plus the length of the string. Add to that the values contained in the dictionary, and you see that 4 bytes more per item really isn't that much more memory...
A call to dict.keys() makes one fast scan over the dictionary (internally, the iteration function does exist) copying the pointers to the key objects into a pre-allocated list object of the right size. The iteration time isn't lost (since you'll have to iterate anyway -- unless in the majority of cases your loop terminates very prematurely (which I doubt since you're getting the keys in random order).
I don't expose the dictionary iteration operation to Python programmers because the dictionary shouldn't be modified during the entire iteration -- if it is, there's a small chance that the dictionary is reorganized because the hash table becomes too full, and then the iteration may miss some items and see others twice. Exactly because this only occurs rarely, it would lead to hidden bugs in programs: it's easy never to have it happen during test runs if you only insert or delete a few items per iteration -- but your users will surely hit upon it sooner or later.
Edit this entry / Log info / Last changed on Fri May 24 21:24:08 2002 by GvR
Several projects described in the Python newsgroup or at past Python conferences have shown that this approach is feasible, although the speedups reached so far are only modest (e.g. 2x). JPython uses the same strategy for compiling to Java bytecode. (Jim Hugunin has demonstrated that in combination with whole-program analysis, speedups of 1000x are feasible for small demo programs. See the website for the 1997 Python conference.)
Internally, Python source code is always translated into a "virtual machine code" or "byte code" representation before it is interpreted (by the "Python virtual machine" or "bytecode interpreter"). In order to avoid the overhead of parsing and translating modules that rarely change over and over again, this byte code is written on a file whose name ends in ".pyc" whenever a module is parsed (from a file whose name ends in ".py"). When the corresponding .py file is changed, it is parsed and translated again and the .pyc file is rewritten.
There is no performance difference once the .pyc file has been loaded (the bytecode read from the .pyc file is exactly the same as the bytecode created by direct translation). The only difference is that loading code from a .pyc file is faster than parsing and translating a .py file, so the presence of precompiled .pyc files will generally improve start-up time of Python scripts. If desired, the Lib/compileall.py module/script can be used to force creation of valid .pyc files for a given set of modules.
Note that the main script executed by Python, even if its filename ends in .py, is not compiled to a .pyc file. It is compiled to bytecode, but the bytecode is not saved to a file.
If you are looking for a way to translate Python programs in order to distribute them in binary form, without the need to distribute the interpreter and library as well, have a look at the freeze.py script in the Tools/freeze directory. This creates a single binary file incorporating your program, the Python interpreter, and those parts of the Python library that are needed by your program. Of course, the resulting binary will only run on the same type of platform as that used to create it.
Newsflash: there are now several programs that do this, to some extent. Look for Psyco, Pyrex, PyInline, Py2Cmod, and Weave.
Edit this entry / Log info / Last changed on Fri May 24 21:26:19 2002 by GvR
Jython relies on the Java runtime; so it uses the JVM's garbage collector. This difference can cause some subtle porting problems if your Python code depends on the behavior of the reference counting implementation.
The reference cycle collector was added in CPython 2.0. It periodically executes a cycle detection algorithm which looks for inaccessible cycles and deletes the objects involved. A new gc module provides functions to perform a garbage collection, obtain debugging statistics, and tuning the collector's parameters.
The detection of cycles can be disabled when Python is compiled, if you can't afford even a tiny speed penalty or suspect that the cycle collection is buggy, by specifying the "--without-cycle-gc" switch when running the configure script.
Sometimes objects get stuck in "tracebacks" temporarily and hence are not deallocated when you might expect. Clear the tracebacks via
import sys sys.exc_traceback = sys.last_traceback = NoneTracebacks are used for reporting errors and implementing debuggers and related things. They contain a portion of the program state extracted during the handling of an exception (usually the most recent exception).
In the absence of circularities and modulo tracebacks, Python programs need not explicitly manage memory.
Why python doesn't use a more traditional garbage collection scheme? For one thing, unless this were added to C as a standard feature, it's a portability pain in the ass. And yes, I know about the Xerox library. It has bits of assembler code for most common platforms. Not for all. And although it is mostly transparent, it isn't completely transparent (when I once linked Python with it, it dumped core).
Traditional GC also becomes a problem when Python gets embedded into other applications. While in a stand-alone Python it may be fine to replace the standard malloc() and free() with versions provided by the GC library, an application embedding Python may want to have its own substitute for malloc() and free(), and may not want Python's. Right now, Python works with anything that implements malloc() and free() properly.
In Jython, the following code (which is fine in C Python) will probably run out of file descriptors long before it runs out of memory:
for file in <very long list of files>: f = open(file) c = f.read(1)Using the current reference counting and destructor scheme, each new assignment to f closes the previous file. Using GC, this is not guaranteed. Sure, you can think of ways to fix this. But it's not off-the-shelf technology. If you want to write code that will work with any Python implementation, you should explicitly close the file; this will work regardless of GC:
for file in <very long list of files>: f = open(file) c = f.read(1) f.close()
Edit this entry / Log info / Last changed on Thu Mar 21 05:35:38 2002 by Erno Kuusela
Immutable tuples are useful in situations where you need to pass a few items to a function and don't want the function to modify the tuple; for example,
point1 = (120, 140) point2 = (200, 300) record(point1, point2) draw(point1, point2)You don't want to have to think about what would happen if record() changed the coordinates -- it can't, because the tuples are immutable.
On the other hand, when creating large lists dynamically, it is absolutely crucial that they are mutable -- adding elements to a tuple one by one requires using the concatenation operator, which makes it quadratic in time.
As a general guideline, use tuples like you would use structs in C or records in Pascal, use lists like (variable length) arrays.
Edit this entry / Log info / Last changed on Fri May 23 15:26:03 1997 by GvR
This makes indexing a list (a[i]) an operation whose cost is independent of the size of the list or the value of the index.
When items are appended or inserted, the array of references is resized. Some cleverness is applied to improve the performance of appending items repeatedly; when the array must be grown, some extra space is allocated so the next few times don't require an actual resize.
Edit this entry / Log info / Last changed on Fri May 23 15:32:24 1997 by GvR
Compared to B-trees, this gives better performance for lookup (the most common operation by far) under most circumstances, and the implementation is simpler.
Edit this entry / Log info / Last changed on Fri May 23 23:51:14 1997 by Vladimir Marangozov
If you think you need to have a dictionary indexed with a list, try to use a tuple instead. The function tuple(l) creates a tuple with the same entries as the list l.
Some unacceptable solutions that have been proposed:
- Hash lists by their address (object ID). This doesn't work because if you construct a new list with the same value it won't be found; e.g.,
d = {[1,2]: '12'} print d[[1,2]]will raise a KeyError exception because the id of the [1,2] used in the second line differs from that in the first line. In other words, dictionary keys should be compared using '==', not using 'is'.
- Make a copy when using a list as a key. This doesn't work because the list (being a mutable object) could contain a reference to itself, and then the copying code would run into an infinite loop.
- Allow lists as keys but tell the user not to modify them. This would allow a class of hard-to-track bugs in programs that I'd rather not see; it invalidates an important invariant of dictionaries (every value in d.keys() is usable as a key of the dictionary).
- Mark lists as read-only once they are used as a dictionary key. The problem is that it's not just the top-level object that could change its value; you could use a tuple containing a list as a key. Entering anything as a key into a dictionary would require marking all objects reachable from there as read-only -- and again, self-referential objects could cause an infinite loop again (and again and again).
There is a trick to get around this if you need to, but use it at your own risk: You can wrap a mutable structure inside a class instance which has both a __cmp__ and a __hash__ method.
class listwrapper: def __init__(self, the_list): self.the_list = the_list def __cmp__(self, other): return self.the_list == other.the_list def __hash__(self): l = self.the_list result = 98767 - len(l)*555 for i in range(len(l)): try: result = result + (hash(l[i]) % 9999999) * 1001 + i except: result = (result % 7777777) + i * 333 return resultNote that the hash computation is complicated by the possibility that some members of the list may be unhashable and also by the possibility of arithmetic overflow.
You must make sure that the hash value for all such wrapper objects that reside in a dictionary (or other hash based structure), remain fixed while the object is in the dictionary (or other structure).
Furthermore it must always be the case that if o1 == o2 (ie o1.__cmp__(o2)==0) then hash(o1)==hash(o2) (ie, o1.__hash__() == o2.__hash__()), regardless of whether the object is in a dictionary or not. If you fail to meet these restrictions dictionaries and other hash based structures may misbehave!
In the case of listwrapper above whenever the wrapper object is in a dictionary the wrapped list must not change to avoid anomalies. Don't do this unless you are prepared to think hard about the requirements and the consequences of not meeting them correctly. You've been warned!
Edit this entry / Log info / Last changed on Thu Jul 10 10:08:40 1997 by aaron watters
Lists are arrays in the C or Pascal sense of the word (see question 6.16). 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 Numerics extensions and others define array-like structures with various characteristics as well.
To get Lisp-like lists, emulate cons cells
lisp_list = ("like", ("this", ("example", None) ) )using tuples (or lists, if you want mutability). 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 (it's usually a lot slower than using Python lists).
Think of Python lists as mutable heterogeneous arrays of Python objects (say that 10 times fast :) ).
Edit this entry / Log info / Last changed on Wed Aug 13 07:08:27 1997 by aaron watters
As a result, here's the idiom to iterate over the keys of a dictionary in sorted order:
keys = dict.keys() keys.sort() for key in keys: ...do whatever with dict[key]...
Edit this entry / Log info / Last changed on Thu Dec 2 17:01:52 1999 by Fred L. Drake, Jr.
A good test suite for a module can at once provide a regression test and serve as a module interface specification (even better since it also gives example usage). Look to many of the standard libraries which often have a "script interpretation" which provides a simple "self test." Even modules which use complex external interfaces can often be tested in isolation using trivial "stub" emulations of the external interface.
An appropriate testing discipline (if enforced) can help build large complex applications in Python as well as having interface specifications would do (or better). Of course Python allows you to get sloppy and not do it. Also you might want to design your code with an eye to make it easily tested.
Edit this entry / Log info / Last changed on Thu May 23 03:05:29 2002 by Neal Norwitz
Remember that in Python usage "type" refers to a C implementation of an object. To distinguish among instances of different classes use Instance.__class__, and also look to 4.47. Sorry for the terminological confusion, but at this point in Python's development nothing can be done!
Edit this entry / Log info / Last changed on Tue Jul 1 12:35:47 1997 by aaron watters
This may happen if there are circular references (see question 4.17). There are also certain bits of memory that are allocated by the C library that are impossible to free (e.g. a tool like Purify will complain about these).
But in general, Python 1.5 and beyond (in contrast with earlier versions) is quite agressive about cleaning up memory on exit.
If you want to force Python to delete certain things on deallocation use the sys.exitfunc hook to force those deletions. For example if you are debugging an extension module using a memory analysis tool and you wish to make Python deallocate almost everything you might use an exitfunc like this one:
import sys
def my_exitfunc(): print "cleaning up" import sys # do order dependant deletions here ... # now delete everything else in arbitrary order for x in sys.modules.values(): d = x.__dict__ for name in d.keys(): del d[name]
sys.exitfunc = my_exitfuncOther exitfuncs can be less drastic, of course.
(In fact, this one just does what Python now already does itself; but the example of using sys.exitfunc to force cleanups is still useful.)
Edit this entry / Log info / Last changed on Tue Sep 29 09:46:26 1998 by GvR
instance.attribute(arg1, arg2)usually translates to the equivalent of
Class.attribute(instance, arg1, arg2)where Class is a (super)class of instance. Similarly
instance.attribute = valuesets an attribute of an instance (overriding any attribute of a class that instance inherits).
Sometimes programmers want to have different behaviours -- they want a method which does not bind to the instance and a class attribute which changes in place. Python does not preclude these behaviours, but you have to adopt a convention to implement them. One way to accomplish this is to use "list wrappers" and global functions.
def C_hello(): print "hello"
class C: hello = [C_hello] counter = [0]
I = C()Here I.hello[0]() acts very much like a "class method" and I.counter[0] = 2 alters C.counter (and doesn't override it). If you don't understand why you'd ever want to do this, that's because you are pure of mind, and you probably never will want to do it! This is dangerous trickery, not recommended when avoidable. (Inspired by Tim Peter's discussion.)
In Python 2.2, you can do this using the new built-in operations classmethod and staticmethod. See http://www.python.org/2.2/descrintro.html#staticmethods
Edit this entry / Log info / Last changed on Tue Sep 11 15:59:37 2001 by GvR
Because of this feature it is good programming practice not to use mutable objects as default values, but to introduce them in the function. Don't write:
def foo(dict={}): # XXX shared reference to one dict for all calls ...but:
def foo(dict=None): if dict is None: dict = {} # create a new dict for local namespaceSee page 182 of "Internet Programming with Python" for one discussion of this feature. Or see the top of page 144 or bottom of page 277 in "Programming Python" for another discussion.
Edit this entry / Log info / Last changed on Sat Aug 16 07:03:35 1997 by Case Roole
class label: pass # declare a label try: ... if (condition): raise label() # goto label ... except label: # where to goto pass ...This doesn't allow you to jump into the middle of a loop, but that's usually considered an abuse of goto anyway. Use sparingly.
Edit this entry / Log info / Last changed on Wed Sep 10 07:16:44 1997 by aaron watters
def linear(a,b): def result(x, a=a, b=b): return a*x + b return resultOr using callable objects:
class linear: def __init__(self, a, b): self.a, self.b = a,b def __call__(self, x): return self.a * x + self.bIn both cases:
taxes = linear(0.3,2)gives a callable object where taxes(10e6) == 0.3 * 10e6 + 2.
The defaults strategy has the disadvantage that the default arguments could be accidentally or maliciously overridden. The callable objects approach has the disadvantage that it is a bit slower and a bit longer. Note however that a collection of callables can share their signature via inheritance. EG
class exponential(linear): # __init__ inherited def __call__(self, x): return self.a * (x ** self.b)On comp.lang.python, zenin@bawdycaste.org points out that an object can encapsulate state for several methods in order to emulate the "closure" concept from functional programming languages, for example:
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.setHere inc, dec and reset act like "functions which share the same closure containing the variable count.value" (if you like that way of thinking).
Edit this entry / Log info / Last changed on Fri Sep 25 08:38:35 1998 by Aaron Watters
Note that JPython doesn't have this restriction!
Edit this entry / Log info / Last changed on Fri May 22 15:01:07 1998 by GvR
Raw strings were designed to ease creating input for processors (chiefly regular expression engines) that want to do their own backslash escape processing. Such processors consider an unmatched trailing backslash to be an error anyway, so raw strings disallow that. In return, they allow you to pass on the string quote character by escaping it with a backslash. These rules work well when r-strings are used for their intended purpose.
If you're trying to build Windows pathnames, note that all Windows system calls accept forward slashes too:
f = open("/mydir/file.txt") # works fine!If you're trying to build a pathname for a DOS command, try e.g. one of
dir = r"\this\is\my\dos\dir" "\\" dir = r"\this\is\my\dos\dir\ "[:-1] dir = "\\this\\is\\my\\dos\\dir\\"
Edit this entry / Log info / Last changed on Mon Jul 13 20:50:20 1998 by Tim Peters
while (line = readline(f)) { ...do something with line... }where in Python you're forced to write this:
while 1: line = f.readline() if not line: break ...do something with line...This issue comes up in the Python newsgroup with alarming frequency -- search Deja News for past messages about assignment expression. The reason for not allowing assignment in Python expressions is a common, hard-to-find bug in those other languages, caused by this construct:
if (x = 0) { ...error handling... } else { ...code that only works for nonzero x... }Many alternatives have been proposed. Most are hacks that save some typing but use arbitrary or cryptic syntax or keywords, and fail the simple criterion that I use for language change proposals: it should intuitively suggest the proper meaning to a human reader who has not yet been introduced with the construct.
The earliest time something can be done about this will be with Python 2.0 -- if it is decided that it is worth fixing. An interesting phenomenon is that most experienced Python programmers recognize the "while 1" idiom and don't seem to be missing the assignment in expression construct much; it's only the newcomers who express a strong desire to add this to the language.
One fairly elegant solution would be to introduce a new operator for assignment in expressions spelled ":=" -- this avoids the "=" instead of "==" problem. It would have the same precedence as comparison operators but the parser would flag combination with other comparisons (without disambiguating parentheses) as an error.
Finally -- there's an alternative way of spelling this that seems attractive but is generally less robust than the "while 1" solution:
line = f.readline() while line: ...do something with line... line = f.readline()The problem with this is that if you change your mind about exactly how you get the next line (e.g. you want to change it into sys.stdin.readline()) you have to remember to change two places in your program -- the second one hidden at the bottom of the loop.
Edit this entry / Log info / Last changed on Tue May 18 00:57:41 1999 by Andrew Dalke
Some languages, such as Object Pascal, Delphi, and C++, use static types. So it is possible to know, in an unambiguous way, what member is being assigned in a "with" clause. This is the main point - the compiler always knows the scope of every variable at compile time.
Python uses dynamic types. It is impossible to know in advance which attribute will be referenced at runtime. Member attributes may be added or removed from objects on the fly. This would make it impossible to know, from a simple reading, what attribute is being referenced - a local one, a global one, or a member attribute.
For instance, take the following snippet (it is incomplete btw, just to give you the idea):
def with_is_broken(a): with a: print xThe snippet assumes that "a" must have a member attribute called "x". However, there is nothing in Python that guarantees that. What should happen if "a" is, let us say, an integer? And if I have a global variable named "x", will it end up being used inside the with block? As you see, the dynamic nature of Python makes such choices much harder.
The primary benefit of "with" and similar language features (reduction of code volume) can, however, easily be achieved in Python by assignment. Instead of:
function(args).dict[index][index].a = 21 function(args).dict[index][index].b = 42 function(args).dict[index][index].c = 63would become:
ref = function(args).dict[index][index] ref.a = 21 ref.b = 42 ref.c = 63This also has the happy side-effect of increasing execution speed, since name bindings are resolved at run-time in Python, and the second method only needs to perform the resolution once. If the referenced object does not have a, b and c attributes, of course, the end result is still a run-time exception.
Edit this entry / Log info / Last changed on Fri Jan 11 14:32:58 2002 by Steve Holden
if a==b print aversus
if a==b: print aNotice how the second one is slightly easier to read. Notice further how a colon sets off the example in the second line of this FAQ answer; it's a standard usage in English. Finally, the colon makes it easier for editors with syntax highlighting.
Edit this entry / Log info / Last changed on Mon Jun 3 07:22:57 2002 by Matthias Urlichs
Back in the days of Python 1.5, Greg Stein actually implemented a comprehensive patch set ("free threading") that removed the GIL, replacing it with fine-grained locking. Unfortunately, even on Windows (where locks are very efficient) this ran ordinary Python code about twice as slow as the interpreter using the GIL. On Linux the performance loss was even worse (pthread locks aren't as efficient).
Since then, the idea of getting rid of the GIL has occasionally come up but nobody has found a way to deal with the expected slowdown; Greg's free threading patch set has not been kept up-to-date for later Python versions.
This doesn't mean that you can't make good use of Python on multi-CPU machines! You just have to be creative with dividing the work up between multiple processes rather than multiple threads.
It has been suggested that the GIL should be a per-interpreter-state lock rather than truly global; interpreters then wouldn't be able to share objects. Unfortunately, this isn't likely to happen either.
It would be a tremendous amount of work, because many object implementations currently have global state. E.g. small ints and small strings are cached; these caches would have to be moved to the interpreter state. Other object types have their own free list; these free lists would have to be moved to the interpreter state. And so on.
And I doubt that it can even be done in finite time, because the same problem exists for 3rd party extensions. It is likely that 3rd party extensions are being written at a faster rate than you can convert them to store all their global state in the interpreter state.
And finally, once you have multiple interpreters not sharing any state, what have you gained over running each interpreter in a separate process?
Edit this entry / Log info / Last changed on Fri Feb 7 16:34:01 2003 by GvR
http://www.cwi.nl/~jack/macpython.html
Edit this entry / Log info / Last changed on Fri May 4 09:33:42 2001 by GvR
Most windows extensions can be found (or referenced) at http://www.python.org/windows/
Windows 3.1/DOS support seems to have dropped off recently. You may need to settle for an old version of Python one these platforms. One such port is WPY
WPY: Ports to DOS, Windows 3.1(1), Windows 95, Windows NT and OS/2. Also contains a GUI package that offers portability between Windows (not DOS) and Unix, and native look and feel on both. ftp://ftp.python.org/pub/python/wpy/.
Edit this entry / Log info / Last changed on Tue Jun 2 20:21:57 1998 by Mark Hammond
Edit this entry / Log info / Last changed on Tue Sep 7 11:33:16 1999 by GvR
Edit this entry / Log info / Last changed on Thu Sep 19 15:40:38 2002 by Skip Montanaro
On the IBM mainframe side, for Z/OS there's a port of python 1.4 that goes with their open-unix package, formely OpenEdition MVS, (http://www-1.ibm.com/servers/eserver/zseries/zos/unix/python.html). On a side note, there's also a java vm ported - so, in theory, jython could run too.
Edit this entry / Log info / Last changed on Mon Nov 18 03:18:39 2002 by Bruno Jessen
Some specific platforms:
Windows: all versions (95, 98, ME, NT, 2000, XP) are supported, all python.org releases come with a Windows installer.
MacOS: Jack Jansen does an admirable job of keeping the Mac version up to date (both MacOS X and older versions); see http://www.cwi.nl/~jack/macpython.html
For all supported platforms, see http://www.python.org/download/ (follow the link to "Other platforms" for less common platforms)
Edit this entry / Log info / Last changed on Fri May 24 21:34:24 2002 by GvR
But if you are sure you have the only distribution with a hope of working on your system, then...
You still need to copy the files from the distribution directory "python/Lib" to your system. If you don't have the full distribution, you can get the file lib<version>.tar.gz from most ftp sites carrying Python; this is a subset of the distribution containing just those files, e.g. ftp://ftp.python.org/pub/python/src/lib1.4.tar.gz.
Once you have installed the library, you need to point sys.path to it. Assuming the library is in C:\misc\python\lib, the following commands will point your Python interpreter to it (note the doubled backslashes -- you can also use single forward slashes instead):
>>> import sys >>> sys.path.insert(0, 'C:\\misc\\python\\lib') >>>For a more permanent effect, set the environment variable PYTHONPATH, as follows (talking to a DOS prompt):
C> SET PYTHONPATH=C:\misc\python\lib
Edit this entry / Log info / Last changed on Fri May 23 16:28:27 1997 by Ken Manheimer
Regarding the same question for the PC, Kurt Wm. Hemr writes: "While anyone with a pulse could certainly figure out how to do the same on MS-Windows, I would recommend the NotGNU Emacs clone for MS-Windows. Not only can you easily resave and "reload()" from Python after making changes, but since WinNot auto-copies to the clipboard any text you select, you can simply select the entire procedure (function) which you changed in WinNot, switch to QWPython, and shift-ins to reenter the changed program unit."
If you're using Windows95 or Windows NT, you should also know about PythonWin, which provides a GUI framework, with an mouse-driven editor, an object browser, and a GUI-based debugger. See
http://www.python.org/ftp/python/pythonwin/for details.
Edit this entry / Log info / Last changed on Sun May 25 10:04:25 1997 by GvR
http://www.python.org/download/download_windows.htmlOne warning: don't attempt to use Tkinter from PythonWin (Mark Hammond's IDE). Use it from the command line interface (python.exe) or the windowless interpreter (pythonw.exe).
Edit this entry / Log info / Last changed on Fri Jun 12 09:32:48 1998 by GvR
"...\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 (eg, GIF) responses may get garbled (resulting in, eg, a "broken image").
Edit this entry / Log info / Last changed on Wed Jul 30 10:48:02 1997 by aaron watters
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()
Edit this entry / Log info / Last changed on Thu Jul 31 15:34:09 1997 by Bill Tutt
import sys if sys.platform == "win32": import win32pipe popen = win32pipe.popen else: import os popen = os.popen(See FAQ 7.13 for an explanation of why you might want to do something like this.) Also you can try to import a module and use a fallback if the import fails:
try: import really_fast_implementation choice = really_fast_implementation except ImportError: import slower_implementation choice = slower_implementation
Edit this entry / Log info / Last changed on Wed Aug 13 07:39:06 1997 by aaron watters
Edit this entry / Log info / Last changed on Mon Dec 14 06:53:32 1998 by Irmen de Jong
Edit this entry / Log info / Last changed on Fri Jun 25 10:45:38 1999 by Bill Tutt
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 by people who would know 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). However, that issue is beyond this Windows FAQ entry.
** Apache configuration
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.
** Netscape Servers: Information on this topic exists at: http://home.netscape.com/comprod/server_central/support/fasttrack_man/programs.htm#1010870
Edit this entry / Log info / Last changed on Wed Mar 27 12:25:54 2002 by Gerhard Häring
(Search for "keypress" to find an answer for Unix as well.)
Edit this entry / Log info / Last changed on Mon Mar 30 16:21:46 1998 by GvR
Edit this entry / Log info / Last changed on Thu Jun 11 00:41:26 1998 by Gvr
http://www.python.org/doc/essays/styleguide.htmlUnder 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.
Edit this entry / Log info / Last changed on Mon Feb 12 15:04:14 2001 by Steve Holden
def kill(pid): """kill function for Win32""" import win32api handle = win32api.OpenProcess(1, 0, pid) return (0 != win32api.TerminateProcess(handle, 0))
Edit this entry / Log info / Last changed on Sat Aug 8 18:55:06 1998 by Jeff Bauer
>>> import os >>> os.path.isdir( '\\\\rorschach\\public') 0 >>> os.path.isdir( '\\\\rorschach\\public\\') 1[Blake Winton responds:] I've had the same problem doing "Start >> Run" and then a directory on a shared drive. If I use "\\rorschach\public", it will fail, but if I use "\\rorschach\public\", it will work. For that matter, os.stat() does the same thing (well, it gives an error for "\\\\rorschach\\public", but you get the idea)...
I've got a theory about why this happens, but it's only a theory. NT knows the difference between shared directories, and regular directories. "\\rorschach\public" isn't a directory, it's _really_ an IPC abstraction. This is sort of lended credence to by the fact that when you're mapping a network drive, you can't map "\\rorschach\public\utils", but only "\\rorschach\public".
[Clarification by funkster@midwinter.com] It's not actually a Python question, as Python is working just fine; it's clearing up something a bit muddled about Windows networked drives.
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 directoryThe 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
Edit this entry / Log info / Last changed on Sun Jan 31 08:44:48 1999 by GvR
I think this happens because the application was compiled with a different set of compiler flags than Python15.DLL. It seems that some compiler flags affect the standard I/O library in such a way that using different flags makes calls fail. You need to set it for the non-debug multi-threaded DLL (/MD on the command line, or can be set via MSVC under Project Settings->C++/Code Generation then the "Use rum-time library" dropdown.)
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.
Edit this entry / Log info / Last changed on Wed Nov 17 17:37:07 1999 by Mark Hammond
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.)
Edit this entry / Log info / Last changed on Wed Dec 2 22:32:41 1998 by GvR
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.)
Edit this entry / Log info / Last changed on Sat Nov 21 13:41:35 1998 by GvR
The Python 1.5.* DLLs (python15.dll) are all compiled with MS VC++ 5.0 and with multithreading-DLL options (/MD, I think).
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.
Edit this entry / Log info / Last changed on Wed Jan 13 10:58:14 1999 by GvR
You can use freeze on Windows, but you must download the source tree (see http://www.python.org/download/download_source.html). This is recommended for Python 1.5.2 (and betas thereof) only; older versions don't quite work.
You need the Microsoft VC++ 5.0 compiler (maybe it works with 6.0 too). You probably need to build Python -- the project files are all in the PCbuild directory.
The freeze program is in the Tools\freeze subdirectory of the source tree.
Edit this entry / Log info / Last changed on Wed Feb 17 18:47:24 1999 by GvR
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.
Edit this entry / Log info / Last changed on Tue Nov 23 02:40:08 1999 by Jameson Quinn
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).
Edit this entry / Log info / Last changed on Fri Jun 11 00:54:13 1999 by GvR
Win2K:
The standard 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.
WinNT:
The steps taken by the installed as described above allow you do run a script with 'foo.py', but a long time 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.
An appropriate 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 :EOFWin9x:
[Due to Bruce Eckel]
@echo off rem = """ rem run python on this bat file. Needs the full path where rem you keep your python files. The -x causes python to skip rem the first line of the file: python -x c:\aaa\Python\\"%0".bat %1 %2 %3 %4 %5 %6 %7 %8 %9 goto endofpython rem """
# The python program goes here:
print "hello, Python"
# For the end of the batch file: rem = """ :endofpython rem """
Edit this entry / Log info / Last changed on Tue Nov 30 10:25:17 1999 by GvR
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 msg 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"
Edit this entry / Log info / Last changed on Thu Oct 26 15:42:00 2000 by GvR
When '##' appears in a file name below, it is an abbreviated version number. For example, for Python 2.1.1, ## will be replaced by 21.
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 python##.dll; it is typically installed in c:\Windows\System.
You can link to Python statically or dynamically. Linking statically means linking against python##.lib The drawback is that your app won't run if python##.dll does not exist on your system.
General note: python##.lib is the so-called "import lib" corresponding to python.dll. It merely defines symbols for the linker.
Borland note: convert python##.lib to OMF format using Coff2Omf.exe first.
Linking dynamically greatly simplifies link options; everything happens at run time. Your code must load python##.dll using the Windows LoadLibraryEx() routine. The code must also use access routines and data in python##.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.
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 python##.dll.
Problem 1: The so-called "Very High Level" functions that take FILE * arguments will not work in a multi-compiler environment; 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 python##.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.
Edit this entry / Log info / Last changed on Thu Jan 31 16:29:34 2002 by Victor Kryukov
http://www.e-coli.net/pyiis_server.html (for Win2k Server) http://www.e-coli.net/pyiis.html (for Win2k pro)
Edit this entry / Log info / Last changed on Fri Mar 22 22:05:51 2002 by douglas savitsky
Unless you use some sort of integrated development environment (such as PythonWin or IDLE, to name only two in a growing family) then 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 I use "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, usually called the "Python interpreter". The interpreter reads your script, "compiles" it into "Python bytecodes" (which are instructions for an imaginary computer known as the "Python Virtual Machine") 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:
pythonand hitting return. If you 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. >>>then this part of the job has been correctly managed during Python's installation process, and 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, but it takes a little getting used to. Check it by entering a few expressions of your choice and seeing the results...
>>> print "Hello" Hello >>> "Hello" * 3 HelloHelloHelloWhen you want to end your interactive Python session, enter a terminator (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 terminator -- Windows runs a single "python" command in the window, which terminates 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 filenamethen 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 the PATH, which is a just list of directories where Windows will look for programs. Rather than just enter the right command every time you create a command window, 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. Alternatively, perhaps you made a note. Otherwise you will be reduced to a search of your whole disk ... break out the Windows explorer and use "Tools | Find" or hit the "Search" button and look for "python.exe". Suppose you discover that Python is installed in the C:\Python22 directory (the default at the time of writing) then you should make sure that entering the command
c:\Python22\pythonstarts 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:\Python22;%PATH%For Windows NT, 2000 and (I assume) XP, you will need to add a string such as
;C:\Python22to 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 or may not want to reboot your system to make absolutely sure the new setting has "taken" (don't you love the way Windows gives you these freqeuent coffee breaks). You probably won't need to 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
pythonat 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.pyBecause 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.pyif 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.pywill 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. Easier to remember, for now, that
python C:\Steve\Projects\Python\pytest.pyworks pretty close to the same, and redirection will work (more) reliably.
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.
pythonshould 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, but that's another lessFAQ. Take a look at
python --helpif your needs are complex.
4. Interactive mode (where you see the ">>>" prompt) is best used not for running programs, which are better executed as in steps 2 and 3, but for checking that individual statements and expressions do what you think they will, and for developing code by experiment.
Edit this entry / Log info / Last changed on Tue Aug 20 16:19:53 2002 by GvR