\documentclass{howto} \usepackage{distutils} % $Id$ \title{What's New in Python 2.4} \release{0.0} \author{A.M.\ Kuchling} \authoraddress{\email{amk@amk.ca}} \begin{document} \maketitle \tableofcontents This article explains the new features in Python 2.4. No release date for Python 2.4 has been set; expect that this will happen mid-2004. While Python 2.3 was primarily a library development release, Python 2.4 may extend the core language and interpreter in as-yet-undetermined ways. This article doesn't attempt to provide a complete specification of the new features, but instead provides a convenient overview. For full details, you should refer to the documentation for Python 2.4. % add hyperlink when the documentation becomes available online. If you want to understand the complete implementation and design rationale, refer to the PEP for a particular new feature. %====================================================================== \section{PEP 218: Built-In Set Objects} Two new built-in types, \function{set(iterable)} and \function{frozenset(iterable)} provide high speed data types for membership testing, for eliminating duplicates from sequences, and for mathematical operations like unions, intersections, differences, and symmetric differences. \begin{verbatim} >>> a = set('abracadabra') # form a set from a string >>> 'z' in a # fast membership testing False >>> a # unique letters in a set(['a', 'r', 'b', 'c', 'd']) >>> ''.join(a) # convert back into a string 'arbcd' >>> b = set('alacazam') # form a second set >>> a - b # letters in a but not in b set(['r', 'd', 'b']) >>> a | b # letters in either a or b set(['a', 'c', 'r', 'd', 'b', 'm', 'z', 'l']) >>> a & b # letters in both a and b set(['a', 'c']) >>> a ^ b # letters in a or b but not both set(['r', 'd', 'b', 'm', 'z', 'l']) >>> a.add('z') # add a new element >>> a.update('wxy') # add multiple new elements >>> a set(['a', 'c', 'b', 'd', 'r', 'w', 'y', 'x', 'z']) >>> a.remove('x') # take one element out >>> a set(['a', 'c', 'b', 'd', 'r', 'w', 'y', 'z']) \end{verbatim} The type \function{frozenset()} is an immutable version of \function{set()}. Since it is immutable and hashable, it may be used as a dictionary key or as a member of another set. Accordingly, it does not have methods like \method{add()} and \method{remove()} which could alter its contents. \begin{seealso} \seepep{218}{Adding a Built-In Set Object Type}{Originally proposed by Greg Wilson and ultimately implemented by Raymond Hettinger.} \end{seealso} %====================================================================== \section{PEP 322: Reverse Iteration} A new built-in function, \function{reversed(seq)}, takes a sequence and returns an iterator that returns the elements of the sequence in reverse order. \begin{verbatim} >>> for i in reversed(xrange(1,4)): ... print i ... 3 2 1 \end{verbatim} Compared to extended slicing, \code{range(1,4)[::-1]}, \function{reversed()} is easier to read, runs faster, and uses substantially less memory. Note that \function{reversed()} only accepts sequences, not arbitrary iterators. If you want to reverse an iterator, first convert it to a list with \function{list()}. \begin{verbatim} >>> input = open('/etc/passwd', 'r') >>> for line in reversed(list(input)): ... print line ... root:*:0:0:System Administrator:/var/root:/bin/tcsh ... \end{verbatim} \begin{seealso} \seepep{322}{Reverse Iteration}{Written and implemented by Raymond Hettinger.} \end{seealso} %====================================================================== \section{Other Language Changes} Here are all of the changes that Python 2.4 makes to the core Python language. \begin{itemize} \item The string methods, \method{ljust()}, \method{rjust()}, and \method{center()} now take an optional argument for specifying a fill character other than a space. \item The \method{sort()} method of lists gained three keyword arguments, \var{cmp}, \var{key}, and \var{reverse}. These arguments make some common usages of \method{sort()} simpler. All are optional. \var{cmp} is the same as the previous single argument to \method{sort()}; if provided, the value should be a comparison function that takes two arguments and returns -1, 0, or +1 depending on how the arguments compare. \var{key} should be a single-argument function that takes a list element and returns a comparison key for the element. The list is then sorted using the comparison keys. The following example sorts a list case-insensitively: \begin{verbatim} >>> L = ['A', 'b', 'c', 'D'] >>> L.sort() # Case-sensitive sort >>> L ['A', 'D', 'b', 'c'] >>> L.sort(key=lambda x: x.lower()) >>> L ['A', 'b', 'c', 'D'] >>> L.sort(cmp=lambda x,y: cmp(x.lower(), y.lower())) >>> L ['A', 'b', 'c', 'D'] \end{verbatim} The last example, which uses the \var{cmp} parameter, is the old way to perform a case-insensitive sort. It works, but is slower than using a \var{key} parameter. Using \var{key} results in calling the \method{lower()} method once for each element in the list while using \var{cmp} will call the method twice for each comparison. For simple key functions and comparison functions, it is often possible to avoid a \keyword{lambda} expression by using an unbound method instead. For example, the above case-insensitive sort is best coded as: \begin{verbatim} >>> L.sort(key=str.lower) >>> L ['A', 'b', 'c', 'D'] \end{verbatim} The \var{reverse} parameter should have a Boolean value. If the value is \constant{True}, the list will be sorted into reverse order. Instead of \code{L.sort(lambda x,y: cmp(y.score, x.score))}, you can now write: \code{L.sort(key = lambda x: x.score, reverse=True)}. The results of sorting are now guaranteed to be stable. This means that two entries with equal keys will be returned in the same order as they were input. For example, you can sort a list of people by name, and then sort the list by age, resulting in a list sorted by age where people with the same age are in name-sorted order. \item The list type gained a \method{sorted(iterable)} method that works like the in-place \method{sort()} method but has been made suitable for use in expressions. The differences are: \begin{itemize} \item the input may be any iterable; \item a newly formed copy is sorted, leaving the original intact; and \item the expression returns the new sorted copy \end{itemize} \begin{verbatim} >>> L = [9,7,8,3,2,4,1,6,5] >>> [10+i for i in list.sorted(L)] # usable in a list comprehension [11, 12, 13, 14, 15, 16, 17, 18, 19] >>> L = [9,7,8,3,2,4,1,6,5] # original is left unchanged [9,7,8,3,2,4,1,6,5] >>> list.sorted('Monte Python') # any iterable may be an input [' ', 'M', 'P', 'e', 'h', 'n', 'n', 'o', 'o', 't', 't', 'y'] >>> # List the contents of a dict sorted by key values >>> colormap = dict(red=1, blue=2, green=3, black=4, yellow=5) >>> for k, v in list.sorted(colormap.iteritems()): ... print k, v ... black 4 blue 2 green 3 red 1 yellow 5 \end{verbatim} \item The \function{zip()} built-in function and \function{itertools.izip()} now return an empty list instead of raising a \exception{TypeError} exception if called with no arguments. This makes the functions more suitable for use with variable length argument lists: \begin{verbatim} >>> def transpose(array): ... return zip(*array) ... >>> transpose([(1,2,3), (4,5,6)]) [(1, 4), (2, 5), (3, 6)] >>> transpose([]) [] \end{verbatim} \end{itemize} %====================================================================== \subsection{Optimizations} \begin{itemize} \item Optimizations should be described here. \end{itemize} The net result of the 2.4 optimizations is that Python 2.4 runs the pystone benchmark around XX\% faster than Python 2.3 and YY\% faster than Python 2.2. %====================================================================== \section{New, Improved, and Deprecated Modules} As usual, Python's standard library received a number of enhancements and bug fixes. Here's a partial list of the most notable changes, sorted alphabetically by module name. Consult the \file{Misc/NEWS} file in the source tree for a more complete list of changes, or look through the CVS logs for all the details. \begin{itemize} \item The \module{curses} modules now supports the ncurses extension \function{use_default_colors()}. On platforms where the terminal supports transparency, this makes it possible to use a transparent background. (Contributed by J\"org Lehmann.) \item The \module{heapq} module has been converted to C. The resulting ten-fold improvement in speed makes the module suitable for handling high volumes of data. \item The \module{imaplib} module now supports IMAP's THREAD command. (Contributed by Yves Dionne.) \item A new \function{getsid()} function was added to the \module{posix} module that underlies the \module{os} module. (Contributed by J. Raynor.) \item The \module{random} module has a new method called \method{getrandbits(N)} which returns an N-bit long integer. This method supports the existing \method{randrange()} method, making it possible to efficiently generate arbitrarily large random numbers (suitable for prime number generation in RSA applications). \item The regular expression language accepted by the \module{re} module was extended with simple conditional expressions, written as \code{(?(\var{group})\var{A}|\var{B})}. \var{group} is either a numeric group ID or a group name defined with \code{(?P...)} earlier in the expression. If the specified group matched, the regular expression pattern \var{A} will be tested against the string; if the group didn't match, the pattern \var{B} will be used instead. \end{itemize} %====================================================================== % whole new modules get described in \subsections here % ====================================================================== \section{Build and C API Changes} Changes to Python's build process and to the C API include: \begin{itemize} \item Three new convenience macros were added for common return values from extension functions: \csimplemacro{Py_RETURN_NONE}, \csimplemacro{Py_RETURN_TRUE}, and \csimplemacro{Py_RETURN_FALSE}. \item A new function, \cfunction{PyTuple_Pack(N, obj1, obj2, ..., objN)}, constructs tuples from a variable length argument list of Python objects. \item A new function, \function{PyDict_Contains(d, k)}, implements fast dictionary lookups without masking exceptions raised during the loop-up process (compare with \function{PySequence_Contains()} which is slower or \function{PyMapping_HasKey()} which clears all exceptions). \end{itemize} %====================================================================== \subsection{Port-Specific Changes} Platform-specific changes go here. %====================================================================== \section{Other Changes and Fixes \label{section-other}} As usual, there were a bunch of other improvements and bugfixes scattered throughout the source tree. A search through the CVS change logs finds there were XXX patches applied and YYY bugs fixed between Python 2.3 and 2.4. Both figures are likely to be underestimates. Some of the more notable changes are: \begin{itemize} \item Details go here. \end{itemize} %====================================================================== \section{Porting to Python 2.4} This section lists previously described changes that may require changes to your code: \begin{itemize} \item The \function{zip()} built-in function and \function{itertools.izip()} now return an empty list instead of raising a \exception{TypeError} exception if called with no arguments. \item \function{dircache.listdir()} now passes exceptions to the caller instead of returning empty lists. \end{itemize} %====================================================================== \section{Acknowledgements \label{acks}} The author would like to thank the following people for offering suggestions, corrections and assistance with various drafts of this article: Raymond Hettinger. \end{document}