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Doc/whatsnew/whatsnew24.tex
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......@@ -10,7 +10,7 @@
%
\title{What's New in Python 2.4}
\release{0.5}
\release{0.9}
\author{A.M.\ Kuchling}
\authoraddress{
\strong{Python Software Foundation}\\
......@@ -21,29 +21,27 @@
\maketitle
\tableofcontents
This article explains the new features in Python 2.4 beta1, scheduled
for release in mid-October. The final version of Python 2.4 is
expected to be released around December 2004.
This article explains the new features in Python 2.4, scheduled for
release in December 2004.
Python 2.4 is a medium-sized release. It doesn't introduce as many
changes as the radical Python 2.2, but introduces more features than
the conservative 2.3 release did. The most significant new language
features (as of this writing) are function decorators and generator
expressions; most other changes are to the standard library.
the conservative 2.3 release. The most significant new language
features are function decorators and generator expressions; most other
changes are to the standard library.
% XXX update these figures as we go
According to the CVS change logs, there were 421 patches applied and
413 bugs fixed between Python 2.3 and 2.4. Both figures are likely to
be underestimates.
This article doesn't attempt to provide a complete specification of
every single new feature, but instead provides a convenient overview.
For full details, you should refer to the documentation for Python
2.4, such as the \citetitle[../lib/lib.html]{Python Library Reference}
and the \citetitle[../ref/ref.html]{Python Reference Manual}. If you
want to understand the complete implementation and design rationale,
refer to the PEP for a particular new feature or to the module
documentation.
every single new feature, but instead provides a brief introduction to
each feature. For full details, you should refer to the documentation
for Python 2.4, such as the \citetitle[../lib/lib.html]{Python Library
Reference} and the \citetitle[../ref/ref.html]{Python Reference
Manual}. Often you will be referred to the PEP for a particular new
feature for explanations of the implementation and design rationale.
%======================================================================
......@@ -98,6 +96,7 @@ classes. There are currently no plans to deprecate the module.
Greg Wilson and ultimately implemented by Raymond Hettinger.}
\end{seealso}
%======================================================================
\section{PEP 237: Unifying Long Integers and Integers}
......@@ -121,6 +120,7 @@ written by Moshe Zadka and GvR. The changes for 2.4 were implemented by
Kalle Svensson.}
\end{seealso}
%======================================================================
\section{PEP 289: Generator Expressions}
......@@ -129,7 +129,8 @@ The iterator feature introduced in Python 2.2 and the
through large data sets without having the entire data set in memory
at one time. List comprehensions don't fit into this picture very
well because they produce a Python list object containing all of the
items, unavoidably pulling them all into memory. When trying to write
items. This unavoidably pulls all of the objects into memory, which
can be a problem if your data set is very large. When trying to write
a functionally-styled program, it would be natural to write something
like:
......@@ -149,9 +150,9 @@ for link in get_all_links():
\end{verbatim}
The first form is more concise and perhaps more readable, but if
you're dealing with a large number of link objects the second form
would have to be used to avoid having all link objects in memory at
the same time.
you're dealing with a large number of link objects you'd have to write
the second form to avoid having all link objects in memory at the same
time.
Generator expressions work similarly to list comprehensions but don't
materialize the entire list; instead they create a generator that will
......@@ -188,9 +189,10 @@ implemented by Jiwon Seo with early efforts steered by Hye-Shik Chang.}
%======================================================================
\section{PEP 292: Simpler String Substitutions}
Some new classes in the standard library provide a
alternative mechanism for substituting variables into strings that's
better-suited for applications where untrained users need to edit templates.
Some new classes in the standard library provide an alternative
mechanism for substituting variables into strings; this style of
substitution may be better for applications where untrained
users need to edit templates.
The usual way of substituting variables by name is the \code{\%}
operator:
......@@ -206,9 +208,9 @@ problem if the template is in a Python module, because you run the
code, get an ``Unsupported format character'' \exception{ValueError},
and fix the problem. However, consider an application such as Mailman
where template strings or translations are being edited by users who
aren't aware of the Python language; the syntax is complicated to
explain to such users, and if they make a mistake, it's difficult to
provide helpful feedback to them.
aren't aware of the Python language. The format string's syntax is
complicated to explain to such users, and if they make a mistake, it's
difficult to provide helpful feedback to them.
PEP 292 adds a \class{Template} class to the \module{string} module
that uses \samp{\$} to indicate a substitution. \class{Template} is a
......@@ -244,7 +246,7 @@ by Barry Warsaw.}
%======================================================================
\section{PEP 318: Decorators for Functions, Methods and Classes}
\section{PEP 318: Decorators for Functions and Methods}
Python 2.2 extended Python's object model by adding static methods and
class methods, but it didn't extend Python's syntax to provide any new
......@@ -267,14 +269,14 @@ If the method was very long, it would be easy to miss or forget the
The intention was always to add some syntax to make such definitions
more readable, but at the time of 2.2's release a good syntax was not
obvious. Years later, when Python 2.4 is coming out, a good syntax
\emph{still} isn't obvious but users are asking for easier access to
the feature, so a new syntactic feature has been added.
obvious. Today a good syntax \emph{still} isn't obvious but users are
asking for easier access to the feature; a new syntactic feature has
been added to meet this need.
The feature is called ``function decorators''. The name comes from
the idea that \function{classmethod}, \function{staticmethod}, and
friends are storing additional information on a function object; they're
\emph{decorating} functions with more details.
The new feature is called ``function decorators''. The name comes
from the idea that \function{classmethod}, \function{staticmethod},
and friends are storing additional information on a function object;
they're \emph{decorating} functions with more details.
The notation borrows from Java and uses the \character{@} character as an
indicator. Using the new syntax, the example above would be written:
......@@ -298,7 +300,7 @@ def f ():
...
\end{verbatim}
It's equivalent to:
It's equivalent to the following pre-decorator code:
\begin{verbatim}
def f(): ...
......@@ -308,7 +310,7 @@ f = A(B(C(f)))
Decorators must come on the line before a function definition, and
can't be on the same line, meaning that \code{@A def f(): ...} is
illegal. You can only decorate function definitions, either at the
module-level or inside a class; you can't decorate class definitions.
module level or inside a class; you can't decorate class definitions.
A decorator is just a function that takes the function to be decorated
as an argument and returns either the same function or some new
......@@ -352,12 +354,11 @@ def p2(arg):
\end{verbatim}
An example in \pep{318} contains a fancier version of this idea that
lets you specify the required type and check the returned type as
well.
lets you both specify the required type and check the returned type.
Decorator functions can take arguments. If arguments are supplied,
the decorator function is called with only those arguments and must
return a new decorator function; this new function must take a single
your decorator function is called with only those arguments and must
return a new decorator function; this function must take a single
function and return a function, as previously described. In other
words, \code{@A @B @C(args)} becomes:
......@@ -375,11 +376,6 @@ functions writable. This attribute is used to display function names
in tracebacks, so decorators should change the name of any new
function that's constructed and returned.
The new syntax was provisionally added in 2.4alpha2, and is subject to
change during the 2.4beta release cycle depending on the Python
community's reaction. Post-2.4 versions of Python will preserve
compatibility with whatever syntax is used in 2.4final.
\begin{seealso}
\seepep{318}{Decorators for Functions, Methods and Classes}{Written
by Kevin D. Smith, Jim Jewett, and Skip Montanaro. Several people
......@@ -387,6 +383,9 @@ wrote patches implementing function decorators, but the one that was
actually checked in was patch \#979728, written by Mark Russell.}
\end{seealso}
% XXX add link to decorators module in Wiki
%======================================================================
\section{PEP 322: Reverse Iteration}
......@@ -412,7 +411,7 @@ iterators. If you want to reverse an iterator, first convert it to
a list with \function{list()}.
\begin{verbatim}
>>> input= open('/etc/passwd', 'r')
>>> input = open('/etc/passwd', 'r')
>>> for line in reversed(list(input)):
... print line
...
......@@ -429,17 +428,17 @@ root:*:0:0:System Administrator:/var/root:/bin/tcsh
%======================================================================
\section{PEP 324: New subprocess Module}
The standard library provides a number of ways to
execute a subprocess, each of which offers different features and
levels of difficulty. \function{os.system(\var{command})} is easy, but
slow -- it runs a shell process which executes the command --
and dangerous -- you have to be careful about escaping metacharacters.
The \module{popen2} module offers classes that can capture
standard output and standard error from the subprocess, but the naming
is confusing.
The \module{subprocess} module cleans all this up, providing a unified
interface that offers all the features you might need.
The standard library provides a number of ways to execute a
subprocess, offering different features and different levels of
complexity. \function{os.system(\var{command})} is easy to use, but
slow (it runs a shell process which executes the command) and
dangerous (you have to be careful about escaping the shell's
metacharacters). The \module{popen2} module offers classes that can
capture standard output and standard error from the subprocess, but
the naming is confusing. The \module{subprocess} module cleans
this up, providing a unified interface that offers all the features
you might need.
Instead of \module{popen2}'s collection of classes,
\module{subprocess} contains a single class called \class{Popen}
whose constructor supports a number of different keyword arguments.
......@@ -452,39 +451,51 @@ class Popen(args, bufsize=0, executable=None,
startupinfo=None, creationflags=0):
\end{verbatim}
\var{args} is commonly a sequence of strings that will be the arguments to
the program executed as the subprocess. (If the \var{shell} argument is true,
\var{args} can be a string which will then be passed on to the shell for interpretation.)
\var{args} is commonly a sequence of strings that will be the
arguments to the program executed as the subprocess. (If the
\var{shell} argument is true, \var{args} can be a string which will
then be passed on to the shell for interpretation, just as
\function{os.system()} does.)
\var{stdin}, \var{stdout}, and \var{stderr} specify what the
subprocess's input, output, and error streams will be. You can
provide a file object or a file descriptor, or you can
use \code{subprocess.PIPE} to create a pipe between the subprocess
and the parent.
provide a file object or a file descriptor, or you can use the
constant \code{subprocess.PIPE} to create a pipe between the
subprocess and the parent.
The constructor has a number of handy options:
\begin{itemize}
\item \var{close_fds} requests that all file descriptors be closed before running the subprocess.
\item \var{cwd} specifies the working directory in which the subprocess will be executed (defaulting to whatever the parent's working directory is).
\item \var{close_fds} requests that all file descriptors be closed
before running the subprocess.
\item \var{cwd} specifies the working directory in which the
subprocess will be executed (defaulting to whatever the parent's
working directory is).
\item \var{env} is a dictionary specifying environment variables.
\item \var{preexec_fn} is a function that gets called before the child is started.
\item \var{universal_newlines} opens the child's input and output using
Python's universal newline feature.
\item \var{preexec_fn} is a function that gets called before the
child is started.
\item \var{universal_newlines} opens the child's input and output
using Python's universal newline feature.
\end{itemize}
Once you've created the \class{Popen} instance,
you can call \method{wait()} to pause until the subprocess has exited,
\method{poll()} to check if it's exited without pausing,
or \method{communicate(\var{data})} to send the string \var{data} to
you can call its \method{wait()} method to pause until the subprocess
has exited, \method{poll()} to check if it's exited without pausing,
or \method{communicate(\var{data})} to send the string \var{data} to
the subprocess's standard input. \method{communicate(\var{data})}
then reads any data that the subprocess has sent to its standard output or error, returning a tuple \code{(\var{stdout_data}, \var{stderr_data})}.
then reads any data that the subprocess has sent to its standard output
or standard error, returning a tuple \code{(\var{stdout_data},
\var{stderr_data})}.
\function{call()} is a shortcut that passes its arguments along to
the \class{Popen} constructor, waits for the command to complete, and
returns the status code of the subprocess. It can serve as an analog
to
\function{os.system()}:
\function{call()} is a shortcut that passes its arguments along to the
\class{Popen} constructor, waits for the command to complete, and
returns the status code of the subprocess. It can serve as a safer
analog to \function{os.system()}:
\begin{verbatim}
sts = subprocess.call(['dpkg', '-i', '/tmp/new-package.deb'])
......@@ -516,12 +527,12 @@ Reading this section of the PEP is highly recommended.
%======================================================================
\section{PEP 327: Decimal Data Type}
Python has always supported floating-point (FP) numbers as a data
type, based on the underlying C \ctype{double} type. However, while
most programming languages provide a floating-point type, most people
(even programmers) are unaware that computing with floating-point
numbers entails certain unavoidable inaccuracies. The new decimal
type provides a way to avoid these inaccuracies.
Python has always supported floating-point (FP) numbers, based on the
underlying C \ctype{double} type, as a data type. However, while most
programming languages provide a floating-point type, most people (even
programmers) are unaware that computing with floating-point numbers
entails certain unavoidable inaccuracies. The new decimal type
provides a way to avoid these inaccuracies.
\subsection{Why is Decimal needed?}
......@@ -540,20 +551,20 @@ For example, the number 1.25 has positive sign, a mantissa value of
1.01 (in binary), and an exponent of 0 (the decimal point doesn't need
to be shifted). The number 5 has the same sign and mantissa, but the
exponent is 2 because the mantissa is multiplied by 4 (2 to the power
of the exponent 2).
of the exponent 2); 1.25 * 4 equals 5.
Modern systems usually provide floating-point support that conforms to
a relevant standard called IEEE 754. C's \ctype{double} type is
usually implemented as a 64-bit IEEE 754 number, which uses 52 bits of
space for the mantissa. This means that numbers can only be specified
to 52 bits of precision. If you're trying to represent numbers whose
a standard called IEEE 754. C's \ctype{double} type is usually
implemented as a 64-bit IEEE 754 number, which uses 52 bits of space
for the mantissa. This means that numbers can only be specified to 52
bits of precision. If you're trying to represent numbers whose
expansion repeats endlessly, the expansion is cut off after 52 bits.
Unfortunately, most software needs to produce output in base 10, and
base 10 often gives rise to such repeating decimals in the binary
expansion. For example, 1.1 decimal is binary \code{1.0001100110011
...}; .1 = 1/16 + 1/32 + 1/256 plus an infinite number of additional
terms. IEEE 754 has to chop off that infinitely repeated decimal
after 52 digits, so the representation is slightly inaccurate.
common fractions in base 10 are often repeating decimals in binary.
For example, 1.1 decimal is binary \code{1.0001100110011 ...}; .1 =
1/16 + 1/32 + 1/256 plus an infinite number of additional terms. IEEE
754 has to chop off that infinitely repeated decimal after 52 digits,
so the representation is slightly inaccurate.
Sometimes you can see this inaccuracy when the number is printed:
\begin{verbatim}
......@@ -579,15 +590,16 @@ Hence, the \class{Decimal} type was created.
\subsection{The \class{Decimal} type}
A new module, \module{decimal}, was added to Python's standard library.
It contains two classes, \class{Decimal} and \class{Context}.
\class{Decimal} instances represent numbers, and
\class{Context} instances are used to wrap up various settings such as the precision and default rounding mode.
A new module, \module{decimal}, was added to Python's standard
library. It contains two classes, \class{Decimal} and
\class{Context}. \class{Decimal} instances represent numbers, and
\class{Context} instances are used to wrap up various settings such as
the precision and default rounding mode.
\class{Decimal} instances, like regular Python integers and FP
numbers, are immutable; once they've been created, you can't change
the value it represents. \class{Decimal} instances can be created
from integers or strings:
\class{Decimal} instances are immutable, like regular Python integers
and FP numbers; once it's been created, you can't change the value an
instance represents. \class{Decimal} instances can be created from
integers or strings:
\begin{verbatim}
>>> import decimal
......@@ -611,10 +623,10 @@ Cautionary note: the sign bit is a Boolean value, so 0 is positive and
Converting from floating-point numbers poses a bit of a problem:
should the FP number representing 1.1 turn into the decimal number for
exactly 1.1, or for 1.1 plus whatever inaccuracies are introduced?
The decision was to leave such a conversion out of the API. Instead,
you should convert the floating-point number into a string using the
desired precision and pass the string to the \class{Decimal}
constructor:
The decision was to dodge the issue and leave such a conversion out of
the API. Instead, you should convert the floating-point number into a
string using the desired precision and pass the string to the
\class{Decimal} constructor:
\begin{verbatim}
>>> f = 1.1
......@@ -675,9 +687,9 @@ regular floating-point number and not a \class{Decimal}.
351364.18288201344j
\end{verbatim}
Instances also have a \method{sqrt()} method that returns a
\class{Decimal}, but if you need other things such as trigonometric
functions you'll have to implement them.
\class{Decimal} instances have a \method{sqrt()} method that
returns a \class{Decimal}, but if you need other things such as
trigonometric functions you'll have to implement them.
\begin{verbatim}
>>> d.sqrt()
......@@ -694,7 +706,8 @@ decimal operations:
\item \member{prec} is the precision, the number of decimal places.
\item \member{rounding} specifies the rounding mode. The \module{decimal}
module has constants for the various possibilities:
\constant{ROUND_DOWN}, \constant{ROUND_CEILING}, \constant{ROUND_HALF_EVEN}, and various others.
\constant{ROUND_DOWN}, \constant{ROUND_CEILING},
\constant{ROUND_HALF_EVEN}, and various others.
\item \member{traps} is a dictionary specifying what happens on
encountering certain error conditions: either an exception is raised or
a value is returned. Some examples of error conditions are
......@@ -703,7 +716,9 @@ division by zero, loss of precision, and overflow.
There's a thread-local default context available by calling
\function{getcontext()}; you can change the properties of this context
to alter the default precision, rounding, or trap handling.
to alter the default precision, rounding, or trap handling. The
following example shows the effect of changing the precision of the default
context:
\begin{verbatim}
>>> decimal.getcontext().prec
......@@ -764,7 +779,7 @@ easier to import many names from a module. In a
\code{from \var{module} import \var{names}} statement,
\var{names} is a sequence of names separated by commas. If the sequence is
very long, you can either write multiple imports from the same module,
or you can use backslashes to escape the line endings:
or you can use backslashes to escape the line endings like this:
\begin{verbatim}
from SimpleXMLRPCServer import SimpleXMLRPCServer,\
......@@ -773,20 +788,21 @@ from SimpleXMLRPCServer import SimpleXMLRPCServer,\
resolve_dotted_attribute
\end{verbatim}
The syntactic change simply allows putting the names within
parentheses. Python ignores newlines within a parenthesized
The syntactic change in Python 2.4 simply allows putting the names
within parentheses. Python ignores newlines within a parenthesized
expression, so the backslashes are no longer needed:
\begin{verbatim}
from SimpleXMLRPCServer import (SimpleXMLRPCServer,
SimpleXMLRPCRequestHandler,
CGIXMLRPCRequestHandler,
resolve_dotted_attribute)
SimpleXMLRPCRequestHandler,
CGIXMLRPCRequestHandler,
resolve_dotted_attribute)
\end{verbatim}
The PEP also proposes that all \keyword{import} statements be
absolute imports, with a leading \samp{.} character to indicate a
relative import. This part of the PEP is not yet implemented.
The PEP also proposes that all \keyword{import} statements be absolute
imports, with a leading \samp{.} character to indicate a relative
import. This part of the PEP is not yet implemented, and will have to
wait for Python 2.5 or some other future version.
\begin{seealso}
\seepep{328}{Imports: Multi-Line and Absolute/Relative}
......@@ -808,6 +824,7 @@ implementation required that the numeric locale remain set to the
Not setting the numeric locale caused trouble for extensions that used
third-party C libraries, however, because they wouldn't have the
% XXX is it GTK or GTk?
correct locale set. The motivating example was GTK+, whose user
interface widgets weren't displaying numbers in the current locale.
......@@ -830,7 +847,8 @@ can now change the numeric locale, letting extensions such as GTK+
produce the correct results.
\begin{seealso}
\seepep{331}{Locale-Independent Float/String Conversions}{Written by Christian R. Reis, and implemented by Gustavo Carneiro.}
\seepep{331}{Locale-Independent Float/String Conversions}
{Written by Christian R. Reis, and implemented by Gustavo Carneiro.}
\end{seealso}
%======================================================================
......@@ -841,6 +859,18 @@ language.
\begin{itemize}
\item Decorators for functions and methods were added (\pep{318}).
\item Built-in \function{set} and \function{frozenset} types were
added (\pep{218}). Other new built-ins include the \function{reversed(\var{seq})} function (\pep{322}).
\item Generator expressions were added (\pep{289}).
\item Certain numeric expressions no longer return values restricted to 32 or 64 bits (\pep{237}).
\item You can now put parentheses around the list of names in a
\code{from \var{module} import \var{names}} statement (\pep{328}).
\item The \method{dict.update()} method now accepts the same
argument forms as the \class{dict} constructor. This includes any
mapping, any iterable of key/value pairs, and keyword arguments.
......@@ -862,17 +892,18 @@ the string.
['www.python', 'org']
\end{verbatim}
\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.
(Contributed by Raymond Hettinger.)
\item Three keyword parameters, \var{cmp}, \var{key}, and
\var{reverse}, were added to the \method{sort()} method of lists.
These parameters make some common usages of \method{sort()} simpler.
All of these parameters 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.
For the \var{cmp} parameter, the value should be a comparison function
that takes two parameters and returns -1, 0, or +1 depending on how
the parameters compare. This function will then be used to sort the
list. Previously this was the only parameter that could be provided
to \method{sort()}.
\var{key} should be a single-argument function that takes a list
\var{key} should be a single-parameter 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:
......@@ -882,24 +913,27 @@ list case-insensitively:
>>> L.sort() # Case-sensitive sort
>>> L
['A', 'D', 'b', 'c']
>>> # Using 'key' parameter to sort list
>>> L.sort(key=lambda x: x.lower())
>>> L
['A', 'b', 'c', 'D']
>>> # Old-fashioned way
>>> 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 it twice for each comparison.
to perform a case-insensitive sort. It works but is slower than using
a \var{key} parameter. Using \var{key} calls \method{lower()} method
once for each element in the list while using \var{cmp} will call it
twice for each comparison, so using \var{key} saves on invocations of
the \method{lower()} method.
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:
written as:
\begin{verbatim}
>>> L.sort(key=str.lower)
......@@ -907,11 +941,10 @@ coded as:
['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(x.score, y.score)) ;
L.reverse()}, you can now write: \code{L.sort(key = lambda x: x.score,
reverse=True)}.
Finally, the \var{reverse} parameter takes a Boolean value. If the
value is true, the list will be sorted into reverse order.
Instead of \code{L.sort() ; L.reverse()}, you can now write
\code{L.sort(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
......@@ -919,6 +952,8 @@ 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.
(All changes to \method{sort()} contributed by Raymond Hettinger.)
\item There is a new built-in function
\function{sorted(\var{iterable})} that works like the in-place
\method{list.sort()} method but can be used in
......@@ -964,7 +999,7 @@ you can now run the Python profiler with \code{python -m profile}.
\item The \function{eval(\var{expr}, \var{globals}, \var{locals})}
and \function{execfile(\var{filename}, \var{globals}, \var{locals})}
functions and the \keyword{exec} statement now accept any mapping type
for the \var{locals} argument. Previously this had to be a regular
for the \var{locals} parameter. Previously this had to be a regular
Python dictionary. (Contributed by Raymond Hettinger.)
\item The \function{zip()} built-in function and \function{itertools.izip()}
......@@ -988,6 +1023,7 @@ Python dictionary. (Contributed by Raymond Hettinger.)
a partially-initialized module object in \code{sys.modules}. The
incomplete module object left behind would fool further imports of the
same module into succeeding, leading to confusing errors.
% (XXX contributed by Tim?)
\item \constant{None} is now a constant; code that binds a new value to
the name \samp{None} is now a syntax error.
......@@ -1003,7 +1039,7 @@ the name \samp{None} is now a syntax error.
\item The inner loops for list and tuple slicing
were optimized and now run about one-third faster. The inner loops
were also optimized for dictionaries, resulting in performance boosts for
for dictionaries were also optimized , resulting in performance boosts for
\method{keys()}, \method{values()}, \method{items()},
\method{iterkeys()}, \method{itervalues()}, and \method{iteritems()}.
(Contributed by Raymond Hettinger.)
......@@ -1024,7 +1060,7 @@ the name \samp{None} is now a syntax error.
\item The methods \method{list.__getitem__()},
\method{dict.__getitem__()}, and \method{dict.__contains__()} are
are now implemented as \class{method_descriptor} objects rather
than \class{wrapper_descriptor} objects. This form of optimized
than \class{wrapper_descriptor} objects. This form of
access doubles their performance and makes them more suitable for
use as arguments to functionals:
\samp{map(mydict.__getitem__, keylist)}.
......@@ -1035,7 +1071,7 @@ the name \samp{None} is now a syntax error.
by about a third. (Contributed by Raymond Hettinger.)
\item The peephole bytecode optimizer has been improved to
produce shorter, faster bytecode; remarkably the resulting bytecode is
produce shorter, faster bytecode; remarkably, the resulting bytecode is
more readable. (Enhanced by Raymond Hettinger.)
\item String concatenations in statements of the form \code{s = s +
......@@ -1048,6 +1084,7 @@ you want to efficiently glue a large number of strings together.
\end{itemize}
% XXX fill in these figures
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.
......@@ -1065,8 +1102,8 @@ details.
\begin{itemize}
\item The \module{asyncore} module's \function{loop()} now has a
\var{count} parameter that lets you perform a limited number
\item The \module{asyncore} module's \function{loop()} function now
has a \var{count} parameter that lets you perform a limited number
of passes through the polling loop. The default is still to loop
forever.
......@@ -1093,21 +1130,21 @@ euc-jisx0213, iso-2022-jp, iso-2022-jp-1, iso-2022-jp-2,
\item Korean: cp949, euc-kr, johab, iso-2022-kr
\end{itemize}
\item Some other new encodings were added: HP Roman8,
ISO_8859-11, ISO_8859-16, PCTP-154, and TIS-620.
\item The UTF-8 and UTF-16 codecs now cope better with receiving partial input.
Previously the \class{StreamReader} class would try to read more data,
which made it impossible to resume decoding from the stream. The
making it impossible to resume decoding from the stream. The
\method{read()} method will now return as much data as it can and future
calls will resume decoding where previous ones left off.
(Implemented by Walter D\"orwald.)
\item Some other new encodings were added: HP Roman8,
ISO_8859-11, ISO_8859-16, PCTP-154, and TIS-620.
\item There is a new \module{collections} module for
various specialized collection datatypes.
Currently it contains just one type, \class{deque},
a double-ended queue that supports efficiently adding and removing
elements from either end.
elements from either end:
\begin{verbatim}
>>> from collections import deque
......@@ -1126,9 +1163,9 @@ deque(['f', 'g', 'h', 'i', 'j'])
True
\end{verbatim}
Several modules now take advantage of \class{collections.deque} for
improved performance, such as the \module{Queue} and
\module{threading} modules. (Contributed by Raymond Hettinger.)
Several modules, such as the \module{Queue} and \module{threading}
modules, now take advantage of \class{collections.deque} for improved
performance. (Contributed by Raymond Hettinger.)
\item The \module{ConfigParser} classes have been enhanced slightly.
The \method{read()} method now returns a list of the files that
......@@ -1148,10 +1185,10 @@ of two versions of a text. (Contributed by Dan Gass.)
\item The \module{email} package was updated to version 3.0,
which dropped various deprecated APIs and removes support for Python
versions earlier than 2.3. The 3.0 version of the package uses a new
incremental parser for MIME message, available in the
incremental parser for MIME messages, available in the
\module{email.FeedParser} module. The new parser doesn't require
reading the entire message into memory, and doesn't throw exceptions
if a message is malformed; instead it records any problems as a
if a message is malformed; instead it records any problems in the
\member{defect} attribute of the message. (Developed by Anthony
Baxter, Barry Warsaw, Thomas Wouters, and others.)
......@@ -1174,20 +1211,22 @@ get a full list. (Contributed by Andrew Eland.)
\item The \module{itertools} module gained a
\function{groupby(\var{iterable}\optional{, \var{func}})} function.
\var{iterable} returns a succession of elements, and the optional
\var{func} is a function that takes an element and returns a key
value; if omitted, the key is simply the element itself.
\function{groupby()} then groups the elements into subsequences
which have matching values of the key, and returns a series of 2-tuples
containing the key value and an iterator over the subsequence.
\var{iterable} is something that can be iterated over to return a
stream of elements, and the optional \var{func} parameter is a
function that takes an element and returns a key value; if omitted,
the key is simply the element itself. \function{groupby()} then
groups the elements into subsequences which have matching values of
the key, and returns a series of 2-tuples containing the key value
and an iterator over the subsequence.
Here's an example. The \var{key} function simply returns whether a
number is even or odd, so the result of \function{groupby()} is to
return consecutive runs of odd or even numbers.
Here's an example to make this clearer. The \var{key} function simply
returns whether a number is even or odd, so the result of
\function{groupby()} is to return consecutive runs of odd or even
numbers.
\begin{verbatim}
>>> import itertools
>>> L = [2,4,6, 7,8,9,11, 12, 14]
>>> L = [2, 4, 6, 7, 8, 9, 11, 12, 14]
>>> for key_val, it in itertools.groupby(L, lambda x: x % 2):
... print key_val, list(it)
...
......@@ -1255,27 +1294,28 @@ bookmarking, windowing, or lookahead iterators.
\item A number of functions were added to the \module{locale}
module, such as \function{bind_textdomain_codeset()} to specify a
particular encoding, and a family of \function{l*gettext()} functions
particular encoding and a family of \function{l*gettext()} functions
that return messages in the chosen encoding.
(Contributed by Gustavo Niemeyer.)
\item The \module{logging} package's \function{basicConfig} function
gained some keyword arguments to simplify log configuration. The
default behavior is to log messages to standard error, but
various keyword arguments can be specified to log to a particular file,
change the logging format, or set the logging level. For example:
\item Some keyword arguments were added to the \module{logging}
package's \function{basicConfig} function to simplify log
configuration. The default behavior is to log messages to standard
error, but various keyword arguments can be specified to log to a
particular file, change the logging format, or set the logging level.
For example:
\begin{verbatim}
import logging
logging.basicConfig(filename = '/var/log/application.log',
level=0, # Log all messages, including debugging,
logging.basicConfig(filename='/var/log/application.log',
level=0, # Log all messages
format='%(levelname):%(process):%(thread):%(message)')
\end{verbatim}
Other additions to \module{logging} include a \method{log(\var{level},
\var{msg})} convenience method, and a
\class{TimedRotatingFileHandler} class that rotates its log files at
a timed interval. The module already had \class{RotatingFileHandler},
Other additions to the \module{logging} package include a
\method{log(\var{level}, \var{msg})} convenience method, as well as a
\class{TimedRotatingFileHandler} class that rotates its log files at a
timed interval. The module already had \class{RotatingFileHandler},
which rotated logs once the file exceeded a certain size. Both
classes derive from a new \class{BaseRotatingHandler} class that can
be used to implement other rotating handlers.
......@@ -1292,7 +1332,7 @@ but the primary effect is to make \file{.pyc} files significantly smaller.
newsgroup descriptions for a single group or for a range of groups.
(Contributed by J\"urgen A. Erhard.)
\item The \module{operator} module gained two new functions,
\item Two new functions were added to the \module{operator} module,
\function{attrgetter(\var{attr})} and \function{itemgetter(\var{index})}.
Both functions return callables that take a single argument and return
the corresponding attribute or item; these callables make excellent
......@@ -1311,11 +1351,12 @@ data extractors when used with \function{map()} or
(Contributed by Raymond Hettinger.)
\item The \module{optparse} module was updated. The module now passes
its messages through \function{gettext.gettext()}, making it possible
to internationalize Optik's help and error messages. Help messages
for options can now include the string \code{'\%default'}, which will
be replaced by the option's default value.
\item The \module{optparse} module was updated in various ways. The
module now passes its messages through \function{gettext.gettext()},
making it possible to internationalize Optik's help and error
messages. Help messages for options can now include the string
\code{'\%default'}, which will be replaced by the option's default
value. (Contributed by Greg Ward.)
\item The long-term plan is to deprecate the \module{rfc822} module
in some future Python release in favor of the \module{email} package.
......@@ -1325,12 +1366,11 @@ changed to make it usable as a replacement for
processing code with this in mind. (Change implemented by Anthony
Baxter.)
\item A new \function{urandom(\var{n})} function
was added to the \module{os} module, providing access to
platform-specific sources of randomness such as
\file{/dev/urandom} on Linux or the Windows CryptoAPI. The
function returns a string containing \var{n} bytes of random data.
(Contributed by Trevor Perrin.)
\item A new \function{urandom(\var{n})} function was added to the
\module{os} module, returning a string containing \var{n} bytes of
random data. This function provides access to platform-specific
sources of randomness such as \file{/dev/urandom} on Linux or the
Windows CryptoAPI. (Contributed by Trevor Perrin.)
\item Another new function: \function{os.path.lexists(\var{path})}
returns true if the file specified by \var{path} exists, whether or
......@@ -1349,11 +1389,12 @@ not it's a symbolic link. This differs from the existing
% XXX more to say about this?
(Contributed by Nick Bastin.)
\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.
(Contributed by Raymond Hettinger.)
\item The \module{random} module has a new method called
\method{getrandbits(\var{N})} that returns a long integer \var{N}
bits in length. The existing \method{randrange()} method now uses
\method{getrandbits()} where appropriate, making generation of
arbitrarily large random numbers more efficient. (Contributed by
Raymond Hettinger.)
\item The regular expression language accepted by the \module{re} module
was extended with simple conditional expressions, written as
......@@ -1363,19 +1404,20 @@ not it's a symbolic link. This differs from the existing
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.
\item The \module{re} module is also no longer recursive, thanks
to a massive amount of work by Gustavo Niemeyer. In a recursive
regular expression engine, certain patterns result in a large amount
of C stack space being consumed, and it was possible to overflow the
stack. For example, if you matched a 30000-byte string of \samp{a}
characters against the expression \regexp{(a|b)+}, one stack frame was
consumed per character. Python 2.3 tried to check for stack overflow
and raise a \exception{RuntimeError} exception, but if you were
unlucky Python could dump core. Python 2.4's regular expression
engine can match this pattern without problems.
\item A new \function{socketpair()} function was added to the
\module{socket} module, returning a pair of connected sockets.
\item The \module{re} module is also no longer recursive, thanks to a
massive amount of work by Gustavo Niemeyer. In a recursive regular
expression engine, certain patterns result in a large amount of C
stack space being consumed, and it was possible to overflow the stack.
For example, if you matched a 30000-byte string of \samp{a} characters
against the expression \regexp{(a|b)+}, one stack frame was consumed
per character. Python 2.3 tried to check for stack overflow and raise
a \exception{RuntimeError} exception, but certain patterns could
sidestep the checking and if you were unlucky Python could segfault.
Python 2.4's regular expression engine can match this pattern without
problems.
\item A new \function{socketpair()} function, returning a pair of
connected sockets, was added to the \module{socket} module.
(Contributed by Dave Cole.)
\item The \function{sys.exitfunc()} function has been deprecated. Code
......@@ -1385,7 +1427,7 @@ handles calling multiple exit functions. Eventually
accessed only by \module{atexit}.
\item The \module{tarfile} module now generates GNU-format tar files
by default.
by default. (Contributed by Lars Gustaebel.)
\item The \module{threading} module now has an elegantly simple way to support
thread-local data. The module contains a \class{local} class whose
......@@ -1425,36 +1467,142 @@ been removed.
%======================================================================
% whole new modules get described in subsections here
%=====================
\subsection{cookielib}
The \module{cookielib} library supports client-side handling for HTTP
cookies, just as the \module{Cookie} provides server-side cookie
support in CGI scripts. Cookies are stored in cookie jars; the library
transparently stores cookies offered by the web server in the cookie
jar, and fetches the cookie from the jar when connecting to the
server. Similar to web browsers, policy objects control whether
cookies are accepted or not.
cookies, mirroring the \module{Cookie} module's server-side cookie
support. Cookies are stored in cookie jars; the library transparently
stores cookies offered by the web server in the cookie jar, and
fetches the cookie from the jar when connecting to the server. As in
web browsers, policy objects control whether cookies are accepted or
not.
In order to store cookies across sessions, two implementations of
cookie jars are provided: one that stores cookies in the Netscape
format, so applications can use the Mozilla or Lynx cookie jars, and
format so applications can use the Mozilla or Lynx cookie files, and
one that stores cookies in the same format as the Perl libwww libary.
\module{urllib2} has been changed to interact with \module{cookielib}:
\class{HTTPCookieProcessor} manages a cookie jar that is used when
accessing URLs.
% ==================
\subsection{doctest}
The \module{doctest} module underwent considerable refactoring thanks
to Edward Loper and Tim Peters.
to Edward Loper and Tim Peters. Testing can still be as simple as
running \function{doctest.testmod()}, but the refactorings allow
customizing the module's operation in various ways
The new \class{DocTestFinder} class extracts the tests from a given
object's docstrings:
\begin{verbatim}
def f (x, y):
""">>> f(2,2)
4
>>> f(3,2)
6
"""
return x*y
finder = doctest.DocTestFinder()
# Get list of DocTest instances
tests = finder.find(f)
\end{verbatim}
The new \class{DocTestRunner} class then runs individual tests and can
produce a summary of the results:
\begin{verbatim}
runner = doctest.DocTestRunner()
for t in tests:
tried, failed = runner.run(t)
runner.summarize(verbose=1)
\end{verbatim}
The above example produces the following output:
\begin{verbatim}
1 items passed all tests:
2 tests in f
2 tests in 1 items.
2 passed and 0 failed.
Test passed.
\end{verbatim}
\class{DocTestRunner} uses an instance of the \class{OutputChecker}
class to compare the expected output with the actual output. This
class takes a number of different flags that customize its behaviour;
ambitious users can also write a completely new subclass of
\class{OutputChecker}.
The default output checker provides a number of handy features.
For example, with the \constant{doctest.ELLIPSIS} option flag,
an ellipsis (\samp{...}) in the expected output matches any substring,
making it easier to accommodate outputs that vary in minor ways:
\begin{verbatim}
def o (n):
""">>> o(1)
<__main__.C instance at 0x...>
>>>
"""
\end{verbatim}
Another special string, \samp{<BLANKLINE>}, matches a blank line:
\begin{verbatim}
def p (n):
""">>> p(1)
<BLANKLINE>
>>>
"""
\end{verbatim}
Another new capability is producing a diff-style display of the output
by specifying the \constant{doctest.REPORT_UDIFF} (unified diffs),
\constant{doctest.REPORT_CDIFF} (context diffs), or
\constant{doctest.REPORT_NDIFF} (delta-style) option flags. For example:
\begin{verbatim}
def g (n):
""">>> g(4)
here
is
a
lengthy
>>>"""
L = 'here is a rather lengthy list of words'.split()
for word in L[:n]:
print word
\end{verbatim}
Running the above function's tests with
\constant{doctest.REPORT_UDIFF} specified, you get the following output:
\begin{verbatim}
**********************************************************************
File ``t.py'', line 15, in g
Failed example:
g(4)
Differences (unified diff with -expected +actual):
@@ -2,3 +2,3 @@
is
a
-lengthy
+rather
**********************************************************************
\end{verbatim}
% XXX describe this
% ======================================================================
\section{Build and C API Changes}
Changes to Python's build process and to the C API include:
Some of the changes to Python's build process and to the C API are:
\begin{itemize}
......@@ -1496,14 +1644,15 @@ Changes to Python's build process and to the C API include:
\method{set.__contains__()}. (Contributed by Raymond Hettinger.)
\item Python can now be built with additional profiling for the
interpreter itself. This is intended for people developing on the
interpreter itself, intended as an aid to people developing the
Python core. Providing \longprogramopt{--enable-profiling} to the
\program{configure} script will let you profile the interpreter with
\program{gprof}, and providing the \longprogramopt{--with-tsc}
switch enables profiling using the Pentium's Time-Stamp-Counter
register. The switch is slightly misnamed, because the profiling
feature also works on the PowerPC platform, though that processor
architecture doesn't call that register a TSC.
register. (The \longprogramopt{--with-tsc} switch is slightly
misnamed, because the profiling feature also works on the PowerPC
platform, though that processor architecture doesn't call that
register ``the TSC register''.)
\item The \ctype{tracebackobject} type has been renamed to \ctype{PyTracebackObject}.
......@@ -1530,6 +1679,13 @@ changes to your code:
\begin{itemize}
\item Left shifts and hexadecimal/octal constants that are too
large no longer trigger a \exception{FutureWarning} and return
a value limited to 32 or 64 bits; instead they return a long integer.
\item Integer operations will no longer trigger an \exception{OverflowWarning}.
The \exception{OverflowWarning} warning will disappear in Python 2.5.
\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.
......@@ -1548,6 +1704,12 @@ changes to your code:
\item The \module{tarfile} module now generates GNU-format tar files
by default.
\item Encountering a failure while importing a module no longer leaves
a partially-initialized module object in \code{sys.modules}.
\item \constant{None} is now a constant; code that binds a new value to
the name \samp{None} is now a syntax error.
\end{itemize}
......
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