\documentclass{howto} \title{What's New in Python 2.0} \release{0.05} \author{A.M. Kuchling and Moshe Zadka} \authoraddress{\email{amk1@bigfoot.com}, \email{moshez@math.huji.ac.il} } \begin{document} \maketitle\tableofcontents \section{Introduction} {\large This is a draft document; please report inaccuracies and omissions to the authors. This document should not be treated as definitive; features described here might be removed or changed during the beta cycle before the final release of Python 2.0. } A new release of Python, version 2.0, will be released some time this summer. Beta versions are already available from \url{http://www.pythonlabs.com/products/python2.0/}. This article covers the exciting new features in 2.0, highlights some other useful changes, and points out a few incompatible changes that may require rewriting code. Python's development never completely stops between releases, and a steady flow of bug fixes and improvements are always being submitted. A host of minor fixes, a few optimizations, additional docstrings, and better error messages went into 2.0; to list them all would be impossible, but they're certainly significant. Consult the publicly-available CVS logs if you want to see the full list. % ====================================================================== \section{What About Python 1.6?} Python 1.6 can be thought of as the Contractual Obligations Python release. After the core development team left CNRI in May 2000, CNRI requested that a 1.6 release be created, containing all the work on Python that had been performed at CNRI. Python 1.6 therefore represents the state of the CVS tree as of May 2000, with the most significant new feature being Unicode support. Development continued after May, of course, so the 1.6 tree received a few fixes to ensure that it's forward-compatible with Python 2.0. 1.6 is therefore part of Python's evolution, and not a side branch. So, should you take much interest in Python 1.6? Probably not. The 1.6final and 2.0beta1 releases were made on the same day (September 5, 2000), the plan being to finalize Python 2.0 within a month or so. If you have applications to maintain, there seems little point in breaking things by moving to 1.6, fixing them, and then having another round of breakage within a month by moving to 2.0; you're better off just going straight to 2.0. Most of the really interesting features described in this document are only in 2.0, because a lot of work was done between May and September. % ====================================================================== \section{Unicode} The largest new feature in Python 2.0 is a new fundamental data type: Unicode strings. Unicode uses 16-bit numbers to represent characters instead of the 8-bit number used by ASCII, meaning that 65,536 distinct characters can be supported. The final interface for Unicode support was arrived at through countless often-stormy discussions on the python-dev mailing list, and mostly implemented by Marc-Andr\'e Lemburg, based on a Unicode string type implementation by Fredrik Lundh. A detailed explanation of the interface is in the file \file{Misc/unicode.txt} in the Python source distribution; it's also available on the Web at \url{http://starship.python.net/crew/lemburg/unicode-proposal.txt}. This article will simply cover the most significant points from the full interface. In Python source code, Unicode strings are written as \code{u"string"}. Arbitrary Unicode characters can be written using a new escape sequence, \code{\e u\var{HHHH}}, where \var{HHHH} is a 4-digit hexadecimal number from 0000 to FFFF. The existing \code{\e x\var{HHHH}} escape sequence can also be used, and octal escapes can be used for characters up to U+01FF, which is represented by \code{\e 777}. Unicode strings, just like regular strings, are an immutable sequence type. They can be indexed and sliced, but not modified in place. Unicode strings have an \method{encode( \optional{encoding} )} method that returns an 8-bit string in the desired encoding. Encodings are named by strings, such as \code{'ascii'}, \code{'utf-8'}, \code{'iso-8859-1'}, or whatever. A codec API is defined for implementing and registering new encodings that are then available throughout a Python program. If an encoding isn't specified, the default encoding is usually 7-bit ASCII, though it can be changed for your Python installation by calling the \function{sys.setdefaultencoding(\var{encoding})} function in a customised version of \file{site.py}. Combining 8-bit and Unicode strings always coerces to Unicode, using the default ASCII encoding; the result of \code{'a' + u'bc'} is \code{u'abc'}. New built-in functions have been added, and existing built-ins modified to support Unicode: \begin{itemize} \item \code{unichr(\var{ch})} returns a Unicode string 1 character long, containing the character \var{ch}. \item \code{ord(\var{u})}, where \var{u} is a 1-character regular or Unicode string, returns the number of the character as an integer. \item \code{unicode(\var{string} \optional{, \var{encoding}} \optional{, \var{errors}} ) } creates a Unicode string from an 8-bit string. \code{encoding} is a string naming the encoding to use. The \code{errors} parameter specifies the treatment of characters that are invalid for the current encoding; passing \code{'strict'} as the value causes an exception to be raised on any encoding error, while \code{'ignore'} causes errors to be silently ignored and \code{'replace'} uses U+FFFD, the official replacement character, in case of any problems. \end{itemize} A new module, \module{unicodedata}, provides an interface to Unicode character properties. For example, \code{unicodedata.category(u'A')} returns the 2-character string 'Lu', the 'L' denoting it's a letter, and 'u' meaning that it's uppercase. \code{u.bidirectional(u'\e x0660')} returns 'AN', meaning that U+0660 is an Arabic number. The \module{codecs} module contains functions to look up existing encodings and register new ones. Unless you want to implement a new encoding, you'll most often use the \function{codecs.lookup(\var{encoding})} function, which returns a 4-element tuple: \code{(\var{encode_func}, \var{decode_func}, \var{stream_reader}, \var{stream_writer})}. \begin{itemize} \item \var{encode_func} is a function that takes a Unicode string, and returns a 2-tuple \code{(\var{string}, \var{length})}. \var{string} is an 8-bit string containing a portion (perhaps all) of the Unicode string converted into the given encoding, and \var{length} tells you how much of the Unicode string was converted. \item \var{decode_func} is the mirror of \var{encode_func}, taking a Unicode string and returns a 2-tuple \code{(\var{ustring}, \var{length})} containing a Unicode string and \var{length} telling you how much of the string was consumed. \item \var{stream_reader} is a class that supports decoding input from a stream. \var{stream_reader(\var{file_obj})} returns an object that supports the \method{read()}, \method{readline()}, and \method{readlines()} methods. These methods will all translate from the given encoding and return Unicode strings. \item \var{stream_writer}, similarly, is a class that supports encoding output to a stream. \var{stream_writer(\var{file_obj})} returns an object that supports the \method{write()} and \method{writelines()} methods. These methods expect Unicode strings, translating them to the given encoding on output. \end{itemize} For example, the following code writes a Unicode string into a file, encoding it as UTF-8: \begin{verbatim} import codecs unistr = u'\u0660\u2000ab ...' (UTF8_encode, UTF8_decode, UTF8_streamreader, UTF8_streamwriter) = codecs.lookup('UTF-8') output = UTF8_streamwriter( open( '/tmp/output', 'wb') ) output.write( unistr ) output.close() \end{verbatim} The following code would then read UTF-8 input from the file: \begin{verbatim} input = UTF8_streamreader( open( '/tmp/output', 'rb') ) print repr(input.read()) input.close() \end{verbatim} Unicode-aware regular expressions are available through the \module{re} module, which has a new underlying implementation called SRE written by Fredrik Lundh of Secret Labs AB. A \code{-U} command line option was added which causes the Python compiler to interpret all string literals as Unicode string literals. This is intended to be used in testing and future-proofing your Python code, since some future version of Python may drop support for 8-bit strings and provide only Unicode strings. % ====================================================================== \section{List Comprehensions} Lists are a workhorse data type in Python, and many programs manipulate a list at some point. Two common operations on lists are to loop over them, and either pick out the elements that meet a certain criterion, or apply some function to each element. For example, given a list of strings, you might want to pull out all the strings containing a given substring, or strip off trailing whitespace from each line. The existing \function{map()} and \function{filter()} functions can be used for this purpose, but they require a function as one of their arguments. This is fine if there's an existing built-in function that can be passed directly, but if there isn't, you have to create a little function to do the required work, and Python's scoping rules make the result ugly if the little function needs additional information. Take the first example in the previous paragraph, finding all the strings in the list containing a given substring. You could write the following to do it: \begin{verbatim} # Given the list L, make a list of all strings # containing the substring S. sublist = filter( lambda s, substring=S: string.find(s, substring) != -1, L) \end{verbatim} Because of Python's scoping rules, a default argument is used so that the anonymous function created by the \keyword{lambda} statement knows what substring is being searched for. List comprehensions make this cleaner: \begin{verbatim} sublist = [ s for s in L if string.find(s, S) != -1 ] \end{verbatim} List comprehensions have the form: \begin{verbatim} [ expression for expr in sequence1 for expr2 in sequence2 ... for exprN in sequenceN if condition \end{verbatim} The \keyword{for}...\keyword{in} clauses contain the sequences to be iterated over. The sequences do not have to be the same length, because they are \emph{not} iterated over in parallel, but from left to right; this is explained more clearly in the following paragraphs. The elements of the generated list will be the successive values of \var{expression}. The final \keyword{if} clause is optional; if present, \var{expression} is only evaluated and added to the result if \var{condition} is true. To make the semantics very clear, a list comprehension is equivalent to the following Python code: \begin{verbatim} for expr1 in sequence1: for expr2 in sequence2: ... for exprN in sequenceN: if (condition): # Append the value of # the expression to the # resulting list. \end{verbatim} This means that when there are \keyword{for}...\keyword{in} clauses, the resulting list will be equal to the product of the lengths of all the sequences. If you have two lists of length 3, the output list is 9 elements long: \begin{verbatim} seq1 = 'abc' seq2 = (1,2,3) >>> [ (x,y) for x in seq1 for y in seq2] [('a', 1), ('a', 2), ('a', 3), ('b', 1), ('b', 2), ('b', 3), ('c', 1), ('c', 2), ('c', 3)] \end{verbatim} To avoid introducing an ambiguity into Python's grammar, if \var{expression} is creating a tuple, it must be surrounded with parentheses. The first list comprehension below is a syntax error, while the second one is correct: \begin{verbatim} # Syntax error [ x,y for x in seq1 for y in seq2] # Correct [ (x,y) for x in seq1 for y in seq2] \end{verbatim} The idea of list comprehensions originally comes from the functional programming language Haskell (\url{http://www.haskell.org}). Greg Ewing argued most effectively for adding them to Python and wrote the initial list comprehension patch, which was then discussed for a seemingly endless time on the python-dev mailing list and kept up-to-date by Skip Montanaro. % ====================================================================== \section{Augmented Assignment} Augmented assignment operators, another long-requested feature, have been added to Python 2.0. Augmented assignment operators include \code{+=}, \code{-=}, \code{*=}, and so forth. For example, the statement \code{a += 2} increments the value of the variable \code{a} by 2, equivalent to the slightly lengthier \code{a = a + 2}. The full list of supported assignment operators is \code{+=}, \code{-=}, \code{*=}, \code{/=}, \code{\%=}, \code{**=}, \code{\&=}, \code{|=}, \verb|^=|, \code{>>=}, and \code{<<=}. Python classes can override the augmented assignment operators by defining methods named \method{__iadd__}, \method{__isub__}, etc. For example, the following \class{Number} class stores a number and supports using += to create a new instance with an incremented value. \begin{verbatim} class Number: def __init__(self, value): self.value = value def __iadd__(self, increment): return Number( self.value + increment) n = Number(5) n += 3 print n.value \end{verbatim} The \method{__iadd__} special method is called with the value of the increment, and should return a new instance with an appropriately modified value; this return value is bound as the new value of the variable on the left-hand side. Augmented assignment operators were first introduced in the C programming language, and most C-derived languages, such as \program{awk}, C++, Java, Perl, and PHP also support them. The augmented assignment patch was implemented by Thomas Wouters. % ====================================================================== \section{String Methods} Until now string-manipulation functionality was in the \module{string} module, which was usually a front-end for the \module{strop} module written in C. The addition of Unicode posed a difficulty for the \module{strop} module, because the functions would all need to be rewritten in order to accept either 8-bit or Unicode strings. For functions such as \function{string.replace()}, which takes 3 string arguments, that means eight possible permutations, and correspondingly complicated code. Instead, Python 2.0 pushes the problem onto the string type, making string manipulation functionality available through methods on both 8-bit strings and Unicode strings. \begin{verbatim} >>> 'andrew'.capitalize() 'Andrew' >>> 'hostname'.replace('os', 'linux') 'hlinuxtname' >>> 'moshe'.find('sh') 2 \end{verbatim} One thing that hasn't changed, a noteworthy April Fools' joke notwithstanding, is that Python strings are immutable. Thus, the string methods return new strings, and do not modify the string on which they operate. The old \module{string} module is still around for backwards compatibility, but it mostly acts as a front-end to the new string methods. Two methods which have no parallel in pre-2.0 versions, although they did exist in JPython for quite some time, are \method{startswith()} and \method{endswith}. \code{s.startswith(t)} is equivalent to \code{s[:len(t)] == t}, while \code{s.endswith(t)} is equivalent to \code{s[-len(t):] == t}. One other method which deserves special mention is \method{join}. The \method{join} method of a string receives one parameter, a sequence of strings, and is equivalent to the \function{string.join} function from the old \module{string} module, with the arguments reversed. In other words, \code{s.join(seq)} is equivalent to the old \code{string.join(seq, s)}. % ====================================================================== \section{Optional Collection of Cycles} The C implementation of Python uses reference counting to implement garbage collection. Every Python object maintains a count of the number of references pointing to itself, and adjusts the count as references are created or destroyed. Once the reference count reaches zero, the object is no longer accessible, since you need to have a reference to an object to access it, and if the count is zero, no references exist any longer. Reference counting has some pleasant properties: it's easy to understand and implement, and the resulting implementation is portable, fairly fast, and reacts well with other libraries that implement their own memory handling schemes. The major problem with reference counting is that it sometimes doesn't realise that objects are no longer accessible, resulting in a memory leak. This happens when there are cycles of references. Consider the simplest possible cycle, a class instance which has a reference to itself: \begin{verbatim} instance = SomeClass() instance.myself = instance \end{verbatim} After the above two lines of code have been executed, the reference count of \code{instance} is 2; one reference is from the variable named \samp{'instance'}, and the other is from the \samp{myself} attribute of the instance. If the next line of code is \code{del instance}, what happens? The reference count of \code{instance} is decreased by 1, so it has a reference count of 1; the reference in the \samp{myself} attribute still exists. Yet the instance is no longer accessible through Python code, and it could be deleted. Several objects can participate in a cycle if they have references to each other, causing all of the objects to be leaked. An experimental step has been made toward fixing this problem. When compiling Python, the \verb|--with-cycle-gc| option can be specified. This causes a cycle detection algorithm to be periodically executed, which looks for inaccessible cycles and deletes the objects involved. A new \module{gc} module provides functions to perform a garbage collection, obtain debugging statistics, and tuning the collector's parameters. Why isn't cycle detection enabled by default? Running the cycle detection algorithm takes some time, and some tuning will be required to minimize the overhead cost. It's not yet obvious how much performance is lost, because benchmarking this is tricky and depends crucially on how often the program creates and destroys objects. Several people tackled this problem and contributed to a solution. An early implementation of the cycle detection approach was written by Toby Kelsey. The current algorithm was suggested by Eric Tiedemann during a visit to CNRI, and Guido van Rossum and Neil Schemenauer wrote two different implementations, which were later integrated by Neil. Lots of other people offered suggestions along the way; the March 2000 archives of the python-dev mailing list contain most of the relevant discussion, especially in the threads titled ``Reference cycle collection for Python'' and ``Finalization again''. % ====================================================================== \section{Other Core Changes} Various minor changes have been made to Python's syntax and built-in functions. None of the changes are very far-reaching, but they're handy conveniences. \subsection{Minor Language Changes} A new syntax makes it more convenient to call a given function with a tuple of arguments and/or a dictionary of keyword arguments. In Python 1.5 and earlier, you'd use the \function{apply()} built-in function: \code{apply(f, \var{args}, \var{kw})} calls the function \function{f()} with the argument tuple \var{args} and the keyword arguments in the dictionary \var{kw}. \function{apply()} is the same in 2.0, but thanks to a patch from Greg Ewing, \code{f(*\var{args}, **\var{kw})} as a shorter and clearer way to achieve the same effect. This syntax is symmetrical with the syntax for defining functions: \begin{verbatim} def f(*args, **kw): # args is a tuple of positional args, # kw is a dictionary of keyword args ... \end{verbatim} The \keyword{print} statement can now have its output directed to a file-like object by following the \keyword{print} with \verb|>> file|, similar to the redirection operator in Unix shells. Previously you'd either have to use the \method{write()} method of the file-like object, which lacks the convenience and simplicity of \keyword{print}, or you could assign a new value to \code{sys.stdout} and then restore the old value. For sending output to standard error, it's much easier to write this: \begin{verbatim} print >> sys.stderr, "Warning: action field not supplied" \end{verbatim} Modules can now be renamed on importing them, using the syntax \code{import \var{module} as \var{name}} or \code{from \var{module} import \var{name} as \var{othername}}. The patch was submitted by Thomas Wouters. A new format style is available when using the \code{\%} operator; '\%r' will insert the \function{repr()} of its argument. This was also added from symmetry considerations, this time for symmetry with the existing '\%s' format style, which inserts the \function{str()} of its argument. For example, \code{'\%r \%s' \% ('abc', 'abc')} returns a string containing \verb|'abc' abc|. Previously there was no way to implement a class that overrode Python's built-in \keyword{in} operator and implemented a custom version. \code{\var{obj} in \var{seq}} returns true if \var{obj} is present in the sequence \var{seq}; Python computes this by simply trying every index of the sequence until either \var{obj} is found or an \exception{IndexError} is encountered. Moshe Zadka contributed a patch which adds a \method{__contains__} magic method for providing a custom implementation for \keyword{in}. Additionally, new built-in objects written in C can define what \keyword{in} means for them via a new slot in the sequence protocol. Earlier versions of Python used a recursive algorithm for deleting objects. Deeply nested data structures could cause the interpreter to fill up the C stack and crash; Christian Tismer rewrote the deletion logic to fix this problem. On a related note, comparing recursive objects recursed infinitely and crashed; Jeremy Hylton rewrote the code to no longer crash, producing a useful result instead. For example, after this code: \begin{verbatim} a = [] b = [] a.append(a) b.append(b) \end{verbatim} The comparison \code{a==b} returns true, because the two recursive data structures are isomorphic. \footnote{See the thread ``trashcan and PR\#7'' in the April 2000 archives of the python-dev mailing list for the discussion leading up to this implementation, and some useful relevant links. %http://www.python.org/pipermail/python-dev/2000-April/004834.html } Work has been done on porting Python to 64-bit Windows on the Itanium processor, mostly by Trent Mick of ActiveState. (Confusingly, \code{sys.platform} is still \code{'win32'} on Win64 because it seems that for ease of porting, MS Visual C++ treats code as 32 bit on Itanium.) PythonWin also supports Windows CE; see the Python CE page at \url{http://starship.python.net/crew/mhammond/ce/} for more information. An attempt has been made to alleviate one of Python's warts, the often-confusing \exception{NameError} exception when code refers to a local variable before the variable has been assigned a value. For example, the following code raises an exception on the \keyword{print} statement in both 1.5.2 and 2.0; in 1.5.2 a \exception{NameError} exception is raised, while 2.0 raises a new \exception{UnboundLocalError} exception. \exception{UnboundLocalError} is a subclass of \exception{NameError}, so any existing code that expects \exception{NameError} to be raised should still work. \begin{verbatim} def f(): print "i=",i i = i + 1 f() \end{verbatim} Two new exceptions, \exception{TabError} and \exception{IndentationError}, have been introduced. They're both subclasses of \exception{SyntaxError}, and are raised when Python code is found to be improperly indented. \subsection{Changes to Built-in Functions} A new built-in, \function{zip(\var{seq1}, \var{seq2}, ...)}, has been added. \function{zip()} returns a list of tuples where each tuple contains the i-th element from each of the argument sequences. The difference between \function{zip()} and \code{map(None, \var{seq1}, \var{seq2})} is that \function{map()} pads the sequences with \code{None} if the sequences aren't all of the same length, while \function{zip()} truncates the returned list to the length of the shortest argument sequence. The \function{int()} and \function{long()} functions now accept an optional ``base'' parameter when the first argument is a string. \code{int('123', 10)} returns 123, while \code{int('123', 16)} returns 291. \code{int(123, 16)} raises a \exception{TypeError} exception with the message ``can't convert non-string with explicit base''. A new variable holding more detailed version information has been added to the \module{sys} module. \code{sys.version_info} is a tuple \code{(\var{major}, \var{minor}, \var{micro}, \var{level}, \var{serial})} For example, in a hypothetical 2.0.1beta1, \code{sys.version_info} would be \code{(2, 0, 1, 'beta', 1)}. \var{level} is a string such as \code{"alpha"}, \code{"beta"}, or \code{"final"} for a final release. Dictionaries have an odd new method, \method{setdefault(\var{key}, \var{default})}, which behaves similarly to the existing \method{get()} method. However, if the key is missing, \method{setdefault()} both returns the value of \var{default} as \method{get()} would do, and also inserts it into the dictionary as the value for \var{key}. Thus, the following lines of code: \begin{verbatim} if dict.has_key( key ): return dict[key] else: dict[key] = [] return dict[key] \end{verbatim} can be reduced to a single \code{return dict.setdefault(key, [])} statement. The interpreter sets a maximum recursion depth in order to catch runaway recursion before filling the C stack and causing a core dump or GPF.. Previously this limit was fixed when you compiled Python, but in 2.0 the maximum recursion depth can be read and modified using \function{sys.getrecursionlimit} and \function{sys.setrecursionlimit}. The default value is 1000, and a rough maximum value for a given platform can be found by running a new script, \file{Misc/find_recursionlimit.py}. % ====================================================================== \section{Porting to 2.0} New Python releases try hard to be compatible with previous releases, and the record has been pretty good. However, some changes are considered useful enough, usually because they fix initial design decisions that turned out to be actively mistaken, that breaking backward compatibility can't always be avoided. This section lists the changes in Python 2.0 that may cause old Python code to break. The change which will probably break the most code is tightening up the arguments accepted by some methods. Some methods would take multiple arguments and treat them as a tuple, particularly various list methods such as \method{.append()} and \method{.insert()}. In earlier versions of Python, if \code{L} is a list, \code{L.append( 1,2 )} appends the tuple \code{(1,2)} to the list. In Python 2.0 this causes a \exception{TypeError} exception to be raised, with the message: 'append requires exactly 1 argument; 2 given'. The fix is to simply add an extra set of parentheses to pass both values as a tuple: \code{L.append( (1,2) )}. The earlier versions of these methods were more forgiving because they used an old function in Python's C interface to parse their arguments; 2.0 modernizes them to use \function{PyArg_ParseTuple}, the current argument parsing function, which provides more helpful error messages and treats multi-argument calls as errors. If you absolutely must use 2.0 but can't fix your code, you can edit \file{Objects/listobject.c} and define the preprocessor symbol \code{NO_STRICT_LIST_APPEND} to preserve the old behaviour; this isn't recommended. Some of the functions in the \module{socket} module are still forgiving in this way. For example, \function{socket.connect( ('hostname', 25) )} is the correct form, passing a tuple representing an IP address, but \function{socket.connect( 'hostname', 25 )} also works. \function{socket.connect_ex()} and \function{socket.bind()} are similarly easy-going. 2.0alpha1 tightened these functions up, but because the documentation actually used the erroneous multiple argument form, many people wrote code which would break with the stricter checking. GvR backed out the changes in the face of public reaction, so for the \module{socket} module, the documentation was fixed and the multiple argument form is simply marked as deprecated; it \emph{will} be tightened up again in a future Python version. The \code{\e x} escape in string literals now takes exactly 2 hex digits. Previously it would consume all the hex digits following the 'x' and take the lowest 8 bits of the result, so \code{\e x123456} was equivalent to \code{\e x56}. The \exception{AttributeError} exception has a more friendly error message, whose text will be something like \code{'Spam' instance has no attribute 'eggs'}. Previously the error message was just the missing attribute name \code{eggs}, and code written to take advantage of this fact will break in 2.0. Some work has been done to make integers and long integers a bit more interchangeable. In 1.5.2, large-file support was added for Solaris, to allow reading files larger than 2Gb; this made the \method{tell()} method of file objects return a long integer instead of a regular integer. Some code would subtract two file offsets and attempt to use the result to multiply a sequence or slice a string, but this raised a \exception{TypeError}. In 2.0, long integers can be used to multiply or slice a sequence, and it'll behave as you'd intuitively expect it to; \code{3L * 'abc'} produces 'abcabcabc', and \code{ (0,1,2,3)[2L:4L]} produces (2,3). Long integers can also be used in various new places where previously only integers were accepted, such as in the \method{seek()} method of file objects. The subtlest long integer change of all is that the \function{str()} of a long integer no longer has a trailing 'L' character, though \function{repr()} still includes it. The 'L' annoyed many people who wanted to print long integers that looked just like regular integers, since they had to go out of their way to chop off the character. This is no longer a problem in 2.0, but code which does \code{str(longval)[:-1]} and assumes the 'L' is there, will now lose the final digit. Taking the \function{repr()} of a float now uses a different formatting precision than \function{str()}. \function{repr()} uses \code{\%.17g} format string for C's \function{sprintf()}, while \function{str()} uses \code{\%.12g} as before. The effect is that \function{repr()} may occasionally show more decimal places than \function{str()}, for certain numbers. For example, the number 8.1 can't be represented exactly in binary, so \code{repr(8.1)} is \code{'8.0999999999999996'}, while str(8.1) is \code{'8.1'}. The \code{-X} command-line option, which turned all standard exceptions into strings instead of classes, has been removed; the standard exceptions will now always be classes. The \module{exceptions} module containing the standard exceptions was translated from Python to a built-in C module, written by Barry Warsaw and Fredrik Lundh. % Commented out for now -- I don't think anyone will care. %The pattern and match objects provided by SRE are C types, not Python %class instances as in 1.5. This means you can no longer inherit from %\class{RegexObject} or \class{MatchObject}, but that shouldn't be much %of a problem since no one should have been doing that in the first %place. % ====================================================================== \section{Extending/Embedding Changes} Some of the changes are under the covers, and will only be apparent to people writing C extension modules or embedding a Python interpreter in a larger application. If you aren't dealing with Python's C API, you can safely skip this section. The version number of the Python C API was incremented, so C extensions compiled for 1.5.2 must be recompiled in order to work with 2.0. On Windows, attempting to import a third party extension built for Python 1.5.x usually results in an immediate crash; there's not much we can do about this. (Here's Mark Hammond's explanation of the reasons for the crash. The 1.5 module is linked against \file{Python15.dll}. When \file{Python.exe} , linked against \file{Python16.dll}, starts up, it initializes the Python data structures in \file{Python16.dll}. When Python then imports the module \file{foo.pyd} linked against \file{Python15.dll}, it immediately tries to call the functions in that DLL. As Python has not been initialized in that DLL, the program immediately crashes.) Users of Jim Fulton's ExtensionClass module will be pleased to find out that hooks have been added so that ExtensionClasses are now supported by \function{isinstance()} and \function{issubclass()}. This means you no longer have to remember to write code such as \code{if type(obj) == myExtensionClass}, but can use the more natural \code{if isinstance(obj, myExtensionClass)}. The \file{Python/importdl.c} file, which was a mass of \#ifdefs to support dynamic loading on many different platforms, was cleaned up and reorganised by Greg Stein. \file{importdl.c} is now quite small, and platform-specific code has been moved into a bunch of \file{Python/dynload_*.c} files. Another cleanup: there were also a number of \file{my*.h} files in the Include/ directory that held various portability hacks; they've been merged into a single file, \file{Include/pyport.h}. Vladimir Marangozov's long-awaited malloc restructuring was completed, to make it easy to have the Python interpreter use a custom allocator instead of C's standard \function{malloc()}. For documentation, read the comments in \file{Include/pymem.h} and \file{Include/objimpl.h}. For the lengthy discussions during which the interface was hammered out, see the Web archives of the 'patches' and 'python-dev' lists at python.org. Recent versions of the GUSI development environment for MacOS support POSIX threads. Therefore, Python's POSIX threading support now works on the Macintosh. Threading support using the user-space GNU \texttt{pth} library was also contributed. Threading support on Windows was enhanced, too. Windows supports thread locks that use kernel objects only in case of contention; in the common case when there's no contention, they use simpler functions which are an order of magnitude faster. A threaded version of Python 1.5.2 on NT is twice as slow as an unthreaded version; with the 2.0 changes, the difference is only 10\%. These improvements were contributed by Yakov Markovitch. Python 2.0's source now uses only ANSI C prototypes, so compiling Python now requires an ANSI C compiler, and can no longer be done using a compiler that only supports K\&R C. Previously the Python virtual machine used 16-bit numbers in its bytecode, limiting the size of source files. In particular, this affected the maximum size of literal lists and dictionaries in Python source; occasionally people who are generating Python code would run into this limit. A patch by Charles G. Waldman raises the limit from \verb|2^16| to \verb|2^{32}|. % ====================================================================== \section{Distutils: Making Modules Easy to Install} Before Python 2.0, installing modules was a tedious affair -- there was no way to figure out automatically where Python is installed, or what compiler options to use for extension modules. Software authors had to go through an arduous ritual of editing Makefiles and configuration files, which only really work on Unix and leave Windows and MacOS unsupported. Software users faced wildly differing installation instructions The SIG for distribution utilities, shepherded by Greg Ward, has created the Distutils, a system to make package installation much easier. They form the \module{distutils} package, a new part of Python's standard library. In the best case, installing a Python module from source will require the same steps: first you simply mean unpack the tarball or zip archive, and the run ``\code{python setup.py install}''. The platform will be automatically detected, the compiler will be recognized, C extension modules will be compiled, and the distribution installed into the proper directory. Optional command-line arguments provide more control over the installation process, the distutils package offers many places to override defaults -- separating the build from the install, building or installing in non-default directories, and more. In order to use the Distutils, you need to write a \file{setup.py} script. For the simple case, when the software contains only .py files, a minimal \file{setup.py} can be just a few lines long: \begin{verbatim} from distutils.core import setup setup (name = "foo", version = "1.0", py_modules = ["module1", "module2"]) \end{verbatim} The \file{setup.py} file isn't much more complicated if the software consists of a few packages: \begin{verbatim} from distutils.core import setup setup (name = "foo", version = "1.0", packages = ["package", "package.subpackage"]) \end{verbatim} A C extension can be the most complicated case; here's an example taken from the PyXML package: \begin{verbatim} from distutils.core import setup, Extension expat_extension = Extension('xml.parsers.pyexpat', define_macros = [('XML_NS', None)], include_dirs = [ 'extensions/expat/xmltok', 'extensions/expat/xmlparse' ], sources = [ 'extensions/pyexpat.c', 'extensions/expat/xmltok/xmltok.c', 'extensions/expat/xmltok/xmlrole.c', ] ) setup (name = "PyXML", version = "0.5.4", ext_modules =[ expat_extension ] ) \end{verbatim} The Distutils can also take care of creating source and binary distributions. The ``sdist'' command, run by ``\code{python setup.py sdist}', builds a source distribution such as \file{foo-1.0.tar.gz}. Adding new commands isn't difficult, ``bdist_rpm'' and ``bdist_wininst'' commands have already been contributed to create an RPM distribution and a Windows installer for the software, respectively. Commands to create other distribution formats such as Debian packages and Solaris \file{.pkg} files are in various stages of development. All this is documented in a new manual, \textit{Distributing Python Modules}, that joins the basic set of Python documentation. % ====================================================================== %\section{New XML Code} %XXX write this section... % ====================================================================== \section{Module changes} Lots of improvements and bugfixes were made to Python's extensive standard library; some of the affected modules include \module{readline}, \module{ConfigParser}, \module{cgi}, \module{calendar}, \module{posix}, \module{readline}, \module{xmllib}, \module{aifc}, \module{chunk, wave}, \module{random}, \module{shelve}, and \module{nntplib}. Consult the CVS logs for the exact patch-by-patch details. Brian Gallew contributed OpenSSL support for the \module{socket} module. OpenSSL is an implementation of the Secure Socket Layer, which encrypts the data being sent over a socket. When compiling Python, you can edit \file{Modules/Setup} to include SSL support, which adds an additional function to the \module{socket} module: \function{socket.ssl(\var{socket}, \var{keyfile}, \var{certfile})}, which takes a socket object and returns an SSL socket. The \module{httplib} and \module{urllib} modules were also changed to support ``https://'' URLs, though no one has implemented FTP or SMTP over SSL. The \module{httplib} module has been rewritten by Greg Stein to support HTTP/1.1. Backward compatibility with the 1.5 version of \module{httplib} is provided, though using HTTP/1.1 features such as pipelining will require rewriting code to use a different set of interfaces. The \module{Tkinter} module now supports Tcl/Tk version 8.1, 8.2, or 8.3, and support for the older 7.x versions has been dropped. The Tkinter module now supports displaying Unicode strings in Tk widgets. Also, Fredrik Lundh contributed an optimization which makes operations like \code{create_line} and \code{create_polygon} much faster, especially when using lots of coordinates. The \module{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. As mentioned in the earlier discussion of 2.0's Unicode support, the underlying implementation of the regular expressions provided by the \module{re} module has been changed. SRE, a new regular expression engine written by Fredrik Lundh and partially funded by Hewlett Packard, supports matching against both 8-bit strings and Unicode strings. % ====================================================================== \section{New modules} A number of new modules were added. We'll simply list them with brief descriptions; consult the 2.0 documentation for the details of a particular module. \begin{itemize} \item{\module{atexit}}: For registering functions to be called before the Python interpreter exits. Code that currently sets \code{sys.exitfunc} directly should be changed to use the \module{atexit} module instead, importing \module{atexit} and calling \function{atexit.register()} with the function to be called on exit. (Contributed by Skip Montanaro.) \item{\module{codecs}, \module{encodings}, \module{unicodedata}:} Added as part of the new Unicode support. \item{\module{filecmp}:} Supersedes the old \module{cmp}, \module{cmpcache} and \module{dircmp} modules, which have now become deprecated. (Contributed by Gordon MacMillan and Moshe Zadka.) \item{\module{linuxaudiodev}:} Support for the \file{/dev/audio} device on Linux, a twin to the existing \module{sunaudiodev} module. (Contributed by Peter Bosch.) \item{\module{mmap}:} An interface to memory-mapped files on both Windows and Unix. A file's contents can be mapped directly into memory, at which point it behaves like a mutable string, so its contents can be read and modified. They can even be passed to functions that expect ordinary strings, such as the \module{re} module. (Contributed by Sam Rushing, with some extensions by A.M. Kuchling.) \item{\module{pyexpat}:} An interface to the Expat XML parser. (Contributed by Paul Prescod.) \item{\module{robotparser}:} Parse a \file{robots.txt} file, which is used for writing Web spiders that politely avoid certain areas of a Web site. The parser accepts the contents of a \file{robots.txt} file, builds a set of rules from it, and can then answer questions about the fetchability of a given URL. (Contributed by Skip Montanaro.) \item{\module{tabnanny}:} A module/script to check Python source code for ambiguous indentation. (Contributed by Tim Peters.) \item{\module{UserString}:} A base class useful for deriving objects that behave like strings. \item{\module{webbrowser}:} A module that provides a platform independent way to launch a web browser on a specific URL. For each platform, various browsers are tried in a specific order. The user can alter which browser is launched by setting the \var{BROWSER} environment variable. (Originally inspired by Eric S. Raymond's patch to \module{urllib} which added similar functionality, but the final module comes from code originally implemented by Fred Drake as \file{Tools/idle/BrowserControl.py}, and adapted for the standard library by Fred.) \item{\module{_winreg}:} An interface to the Windows registry. \module{_winreg} is an adaptation of functions that have been part of PythonWin since 1995, but has now been added to the core distribution, and enhanced to support Unicode. \module{_winreg} was written by Bill Tutt and Mark Hammond. \item{\module{zipfile}:} A module for reading and writing ZIP-format archives. These are archives produced by \program{PKZIP} on DOS/Windows or \program{zip} on Unix, not to be confused with \program{gzip}-format files (which are supported by the \module{gzip} module) (Contributed by James C. Ahlstrom.) \item{\module{imputil}:} A module that provides a simpler way for writing customised import hooks, in comparison to the existing \module{ihooks} module. (Implemented by Greg Stein, with much discussion on python-dev along the way.) \end{itemize} % ====================================================================== \section{IDLE Improvements} IDLE is the official Python cross-platform IDE, written using Tkinter. Python 2.0 includes IDLE 0.6, which adds a number of new features and improvements. A partial list: \begin{itemize} \item UI improvements and optimizations, especially in the area of syntax highlighting and auto-indentation. \item The class browser now shows more information, such as the top level functions in a module. \item Tab width is now a user settable option. When opening an existing Python file, IDLE automatically detects the indentation conventions, and adapts. \item There is now support for calling browsers on various platforms, used to open the Python documentation in a browser. \item IDLE now has a command line, which is largely similar to the vanilla Python interpreter. \item Call tips were added in many places. \item IDLE can now be installed as a package. \item In the editor window, there is now a line/column bar at the bottom. \item Three new keystroke commands: Check module (Alt-F5), Import module (F5) and Run script (Ctrl-F5). \end{itemize} % ====================================================================== \section{Deleted and Deprecated Modules} A few modules have been dropped because they're obsolete, or because there are now better ways to do the same thing. The \module{stdwin} module is gone; it was for a platform-independent windowing toolkit that's no longer developed. A number of modules have been moved to the \file{lib-old} subdirectory: \module{cmp}, \module{cmpcache}, \module{dircmp}, \module{dump}, \module{find}, \module{grep}, \module{packmail}, \module{poly}, \module{util}, \module{whatsound}, \module{zmod}. If you have code which relies on a module that's been moved to \file{lib-old}, you can simply add that directory to \code{sys.path} to get them back, but you're encouraged to update any code that uses these modules. \section{Acknowledgements} The authors would like to thank the following people for offering suggestions on drafts of this article: Mark Hammond, Fredrik Lundh, Detlef Lannert, Skip Montanaro, Vladimir Marangozov, Guido van Rossum, and Neil Schemenauer. \end{document}