[Python-checkins] python/dist/src/Doc/tut glossary.tex, NONE,
1.5.2.1 tut.tex, 1.196.8.9, 1.196.8.10
rhettinger at users.sourceforge.net
rhettinger at users.sourceforge.net
Thu Dec 4 16:30:07 EST 2003
Update of /cvsroot/python/python/dist/src/Doc/tut
In directory sc8-pr-cvs1:/tmp/cvs-serv14962
Modified Files:
Tag: release23-maint
tut.tex
Added Files:
Tag: release23-maint
glossary.tex
Log Message:
Backport library tour, glossary, and small fixups to the tutorial.
--- NEW FILE: glossary.tex ---
\chapter{Glossary\label{glossary}}
%%% keep the entries sorted and include at least one \index{} item for each
%%% cross-references are marked with \emph{entry}
\begin{description}
\index{>>>}
\item[\code{>\code{>}>}]
The typical Python prompt of the interactive shell. Often seen for
code examples that can be tried right away in the interpreter.
\index{...}
\item[\code{.\code{.}.}]
The typical Python prompt of the interactive shell when entering code
for an indented code block.
\index{BDFL}
\item[BDFL]
Benevolent Dictator For Life, a.k.a. \ulink{Guido van
Rossum}{http://www.python.org/\textasciitilde{}guido/}, Python's creator.
\index{byte code}
\item[byte code]
The internal representation of a Python program in the interpreter.
The byte code is also cached in the \code{.pyc} and \code{.pyo}
files so that executing the same file is faster the second time
(compilation from source to byte code can be saved). This
``intermediate language'' is said to run on a ``virtual
machine'' that calls the subroutines corresponding to each bytecode.
\index{classic class}
\item[classic class]
Any class which does not inherit from \class{object}. See
\emph{new-style class}.
\index{coercion}
\item[coercion]
Converting data from one type to another. For example,
{}\code{int(3.15)} coerces the floating point number to the integer,
{}\code{3}. Most mathematical operations have rules for coercing
their arguments to a common type. For instance, adding \code{3+4.5},
causes the integer \code{3} to be coerced to be a float
{}\code{3.0} before adding to \code{4.5} resulting in the float
{}\code{7.5}.
\index{descriptor}
\item[descriptor]
Any \emph{new-style} object that defines the methods
{}\method{__get__()}, \method{__set__()}, or \method{__delete__()}.
When a class attribute is a descriptor, its special binding behavior
is triggered upon attribute lookup. Normally, writing \var{a.b} looks
up the object \var{b} in the class dictionary for \var{a}, but if
{}\var{b} is a descriptor, the defined method gets called.
Understanding descriptors is a key to a deep understanding of Python
because they are the basis for many features including functions,
methods, properties, class methods, static methods, and reference to
super classes.
\index{dictionary}
\item[dictionary]
An associative array, where arbitrary keys are mapped to values. The
use of \class{dict} much resembles that for \class{list}, but the keys
can be any object with a \method{__hash__()} function, not just
integers starting from zero. Called a hash in Perl.
\index{EAFP}
\item[EAFP]
Easier to ask for forgiveness than permission. This common Python
coding style assumes the existence of valid keys or attributes and
catches exceptions if the assumption proves false. This clean and
fast style is characterized by the presence of many \keyword{try} and
{}\keyword{except} statements. The technique contrasts with the
{}\emph{LBYL} style that is common in many other languages such as C.
\index{__future__}
\item[__future__]
A pseudo module which programmers can use to enable new language
features which are not compatible with the current interpreter. For
example, the expression \code{11/4} currently evaluates to \code{2}.
If the module in which it is executed had enabled \emph{true division}
by executing:
\begin{verbatim}
from __future__ import division
\end{verbatim}
the expression \code{11/4} would evaluate to \code{2.75}. By actually
importing the \ulink{\module{__future__}}{../lib/module-future.html}
module and evaluating its variables, you can see when a new feature
was first added to the language and when it will become the default:
\begin{verbatim}
>>> import __future__
>>> __future__.division
_Feature((2, 2, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 8192)
\end{verbatim}
\index{generator}
\item[generator]
A function that returns an iterator. It looks like a normal function
except that the \keyword{yield} keyword is used instead of
{}\keyword{return}. Generator functions often contain one or more
{}\keyword{for} or \keyword{while} loops that \keyword{yield} elements
back to the caller. The function execution is stopped at the
{}\keyword{yield} keyword (returning the result) and is resumed there
when the next element is requested by calling the \method{next()}
method of the returned iterator.
\index{GIL}
\item[GIL]
See \emph{global interpreter lock}.
\index{global interpreter lock}
\item[global interpreter lock]
The lock used by Python threads to assure that only one thread can be
run at a time. This simplifies Python by assuring that no two
processes can access the same memory at the same time. Locking the
entire interpreter makes it easier for the interpreter to be
multi-threaded, at the expense of some parallelism on multi-processor
machines. Efforts have been made in the past to create a
``free-threaded'' interpreter (one which locks shared data at a much
finer granularity), but performance suffered in the common
single-processor case.
\index{IDLE}
\item[IDLE]
An Integrated Development Environment for Python. IDLE is a
basic editor and interpreter environment that ships with the standard
distribution of Python. Good for beginners, it also serves as clear
example code for those wanting to implement a moderately
sophisticated, multi-platform GUI application.
\index{immutable}
\item[immutable]
A object with fixed value. Immutable objects are numbers, strings or
tuples (and more). Such an object cannot be altered. A new object
has to be created if a different value has to be stored. They play an
important role in places where a constant hash value is needed. For
example as a key in a dictionary.
\index{integer division}
\item[integer division]
Mathematical division discarding any remainder. For example, the
expression \code{11/4} currently evaluates to \code{2} in contrast
to the \code{2.75} returned by float division. Also called
{}\emph{floor division}. When dividing two integers the outcome will
always be another integer (having the floor function applied to it).
However, if one of the operands is another numeric type (such as a
{}\class{float}), the result will be coerced (see \emph{coercion}) to
a common type. For example, a integer divided by a float will result
in a float value, possibly with a decimal fraction. Integer division
can be forced by using the \code{//} operator instead of the \code{/}
operator. See also \emph{__future__}.
\index{interactive}
\item[interactive]
Python has an interactive interpreter which means that you can try out
things and directly see its result. Just launch \code{python} with no
arguments (possibly by selecting it from your computer's main menu).
It is a very powerful way to test out new ideas or inspect modules and
packages (remember \code{help(x)}).
\index{interpreted}
\item[interpreted]
Python is an interpreted language, opposed to a compiled one. This
means that the source files can be run right away without first making
an executable which is then run. Interpreted languages typically have
a shorter development/debug cycle than compiled ones. See also
{}\emph{interactive}.
\index{iterable}
\item[iterable]
A container object capable of returning its members one at a time.
Examples of iterables include all sequence types (such as \class{list},
{}\class{str}, and \class{tuple}) and some non-sequence types like
{}\class{dict} and \class{file} and objects of any classes you define
with an \method{__iter__()} or \method{__getitem__()} method. Iterables
can be used in a \keyword{for} loop and in many other places where a
sequence is needed (\function{zip()}, \function{map()}, ...). When an
iterable object is passed as an argument to the builtin function
{}\function{iter()}, it returns an iterator for the object. This
iterator is good for one pass over the set of values. When using
iterables, it is usually not necessary to call \function{iter()} or
deal with iterator objects yourself. The \code{for} statement does
that automatically for you, creating a temporary unnamed variable to
hold the iterator for the duration of the loop. See also
{}\emph{iterator}, \emph{sequence}, and \emph{generator}.
\index{iterator}
\item[iterator]
An object representing a stream of data. Repeated calls to the
iterator's \method{next()} method return successive items in the
stream. When no more data is available a \exception{StopIteration}
exception is raised instead. At this point, the iterator object is
exhausted and any further calls to its \method{next()} method just
raise \exception{StopIteration} again. Iterators are required to have
an \method{__iter__()} method that returns the iterator object
itself so every iterator is also iterable and may be used in most
places where other iterables are accepted. One notable exception is
code that attempts multiple iteration passes. A container object
(such as a \class{list}) produces a fresh new iterator each time you
pass it to the \function{iter()} function or use it in a
{}\keyword{for} loop. Attempting this with an iterator will just
return the same exhausted iterator object from the second iteration
pass, making it appear like an empty container.
\index{list comprehension}
\item[list comprehension]
A compact way to process all or a subset of elements in a sequence and
return a list with the results. \code{result = ["0x\%02x"
\% x for x in range(256) if x \% 2 == 0]} generates a list of strings
containing hex numbers (0x..) that are even and in the range from 0 to 255.
The \keyword{if} clause is optional. If omitted, all elements in
{}\code{range(256)} are processed in that case.
\index{mapping}
\item[mapping]
A container object (such as \class{dict}) that supports arbitrary key
lookups using the special method \method{__getitem__()}.
\index{metaclass}
\item[metaclass]
The class of a class. Class definitions create a class name, a class
dictionary, and a list of base classes. The metaclass is responsible
for taking those three arguments and creating the class. Most object
oriented programming languages provide a default implementation. What
makes Python special is that it is possible to create custom
metaclasses. Most users never need this tool, but when the need
arises, metaclasses can provide powerful, elegant solutions. They
have been used for logging attribute access, adding thread-safety,
tracking object creation, implementing singletons, and many other
tasks.
\index{LBYL}
\item[LBYL]
Look before you leap. This coding style explicitly tests for
pre-conditions before making calls or lookups. This style contrasts
with the \emph{EAFP} approach and is characterized the presence of
many \keyword{if} statements.
\index{mutable}
\item[mutable]
Mutable objects can change their value but keep their \function{id()}.
See also \emph{immutable}.
\index{namespace}
\item[namespace]
The place where a variable is stored. Namespaces are implemented as
dictionary. There is the local, global and builtins namespace and the
nested namespaces in objects (in methods). Namespaces support
modularity by preventing naming conflicts. For instance, the
functions \function{__builtin__.open()} and \function{os.open()} are
distinguished by their namespaces. Namespaces also aid readability
and maintainability by making it clear which modules implement a
function. For instance, writing \function{random.seed()} or
{}\function{itertools.izip()} makes it clear that those functions are
implemented by the \ulink{\module{random}}{../lib/module-random.html}
and \ulink{\module{itertools}}{../lib/module-itertools.html} modules
respectively.
\index{nested scope}
\item[nested scope]
The ability to refer to a variable in an enclosing definition. For
instance, a function defined inside another function can refer to
variables in the outer function. Note that nested scopes work only
for reference and not for assignment which will always write to the
innermost scope. In contrast, local variables both read and write in
the innermost scope. Likewise, global variables read and write to the
global namespace.
\index{new-style class}
\item[new-style class]
Any class that inherits from \class{object}. This includes all
built-in types like \class{list} and \class{dict}. Only new-style
classes can use Python's newer, versatile features like
{}\method{__slots__}, descriptors, properties,
\method{__getattribute__()}, class methods, and static methods.
\index{Python3000}
\item[Python3000]
A mythical python release, allowed not to be backward compatible, with
telepathic interface.
\index{__slots__}
\item[__slots__]
A declaration inside a \emph{new-style class} that saves memory by
pre-declaring space for instance attributes and eliminating instance
dictionaries. Though popular, the technique is somewhat tricky to get
right and is best reserved for rare cases where there are large
numbers of instances in a memory critical application.
\index{sequence}
\item[sequence]
An \emph{iterable} which supports efficient element access using
integer indices via the \method{__getitem__()} and
{}\method{__len__()} special methods. Some built-in sequence types
are \class{list}, \class{str}, \class{tuple}, and \class{unicode}.
Note that \class{dict} also supports \method{__getitem__()} and
{}\method{__len__()}, but is considered a mapping rather than a
sequence because the lookups use arbitrary \emph{immutable} keys
rather than integers.
\index{Zen of Python}
\item[Zen of Python]
Listing of Python design principles and philosophies that are helpful
in understanding and using the language. The listing can be found by
typing ``\code{import this}'' at the interactive prompt.
\end{description}
Index: tut.tex
===================================================================
RCS file: /cvsroot/python/python/dist/src/Doc/tut/tut.tex,v
retrieving revision 1.196.8.9
retrieving revision 1.196.8.10
diff -C2 -d -r1.196.8.9 -r1.196.8.10
*** tut.tex 3 Dec 2003 10:36:15 -0000 1.196.8.9
--- tut.tex 4 Dec 2003 21:30:04 -0000 1.196.8.10
***************
*** 12,15 ****
--- 12,17 ----
\input{boilerplate}
+ \makeindex
+
\begin{document}
***************
*** 1405,1410 ****
while True:
ok = raw_input(prompt)
! if ok in ('y', 'ye', 'yes'): return 1
! if ok in ('n', 'no', 'nop', 'nope'): return 0
retries = retries - 1
if retries < 0: raise IOError, 'refusenik user'
--- 1407,1412 ----
while True:
ok = raw_input(prompt)
! if ok in ('y', 'ye', 'yes'): return True
! if ok in ('n', 'no', 'nop', 'nope'): return False
retries = retries - 1
if retries < 0: raise IOError, 'refusenik user'
***************
*** 2112,2120 ****
When looping through dictionaries, the key and corresponding value can
! be retrieved at the same time using the \method{items()} method.
\begin{verbatim}
>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
! >>> for k, v in knights.items():
... print k, v
...
--- 2114,2122 ----
When looping through dictionaries, the key and corresponding value can
! be retrieved at the same time using the \method{iteritems()} method.
\begin{verbatim}
>>> knights = {'gallahad': 'the pure', 'robin': 'the brave'}
! >>> for k, v in knights.iteritems():
... print k, v
...
***************
*** 3897,3901 ****
\section{Random Remarks \label{remarks}}
! [These should perhaps be placed more carefully...]
--- 3899,3903 ----
\section{Random Remarks \label{remarks}}
! % [These should perhaps be placed more carefully...]
***************
*** 4297,4305 ****
\begin{verbatim}
>>> def reverse(data):
! for index in range(len(data)-1, -1, -1):
! yield data[index]
>>> for char in reverse('golf'):
! print char
f
--- 4299,4307 ----
\begin{verbatim}
>>> def reverse(data):
! for index in range(len(data)-1, -1, -1):
! yield data[index]
>>> for char in reverse('golf'):
! print char
f
***************
*** 4325,4328 ****
--- 4327,4647 ----
+
+ \chapter{Brief Tour of the Standard Library \label{briefTour}}
+
+
+ \section{Operating System Interface\label{os-interface}}
+
+ The \ulink{\module{os}}{../lib/module-os.html}
+ module provides dozens of functions for interacting with the
+ operating system:
+
+ \begin{verbatim}
+ >>> import os
+ >>> os.system('copy /data/mydata.fil /backup/mydata.fil')
+ 0
+ >>> os.getcwd() # Return the current working directory
+ 'C:\\Python24'
+ >>> os.chdir('/server/accesslogs')
+ \end{verbatim}
+
+ Be sure to use the \samp{import os} style instead of
+ \samp{from os import *}. This will keep \function{os.open()} from
+ shadowing the builtin \function{open()} function which operates much
+ differently.
+
+ The builtin \function{dir()} and \function{help()} functions are useful
+ as interactive aids for working with large modules like \module{os}:
+
+ \begin{verbatim}
+ >>> import os
+ >>> dir(os)
+ <returns a listi of all module functions>
+ >>> help(os)
+ <returns an extensive manual page created from the module's docstrings>
+ \end{verbatim}
+
+ For daily file and directory management tasks, the
+ \ulink{\module{shutil}}{../lib/module-shutil.html}
+ module provides a higher level interface that is easier to use:
+
+ \begin{verbatim}
+ >>> import shutil
+ >>> shutil.copyfile('data.db', 'archive.db')
+ >>> shutil.move('/build/excecutables', 'installdir')
+ \end{verbatim}
+
+
+ \section{File Wildcards\label{file-wildcards}}
+
+ The \ulink{\module{glob}}{../lib/module-glob.html}
+ module provides a function for making file lists from directory
+ wildcard searches:
+
+ \begin{verbatim}
+ >>> import glob
+ >>> glob.glob('*.py')
+ ['primes.py', 'random.py', 'quote.py']
+ \end{verbatim}
+
+
+ \section{Command Line Arguments\label{command-line-arguments}}
+
+ Common utility scripts often invoke processing command line arguments.
+ These arguments are stored in the
+ \ulink{\module{sys}}{../lib/module-sys.html}\ module's \var{argv}
+ attribute as a list. For instance the following output results from
+ running \samp{python demo.py one two three} at the command line:
+
+ \begin{verbatim}
+ >>> import sys
+ >>> print sys.argv[]
+ ['demo.py', 'one', 'two', 'three']
+ \end{verbatim}
+
+ The \ulink{\module{getopt}}{../lib/module-getopt.html}
+ module processes \var{sys.argv} using the conventions of the \UNIX{}
+ \function{getopt()} function. More powerful and flexible command line
+ processing is provided by the
+ \ulink{\module{optparse}}{../lib/module-optparse.html} module.
+
+
+ \section{Error Output Redirection and Program Termination\label{stderr}}
+
+ The \ulink{\module{sys}}{../lib/module-sys.html}
+ module also has attributes for \var{stdin}, \var{stdout}, and
+ \var{stderr}. The latter is useful for emitting warnings and error
+ messages to make them visible even when \var{stdout} has been redirected:
+
+ \begin{verbatim}
+ >>> sys.stderr.write('Warning, log file not found starting a new one')
+ Warning, log file not found starting a new one
+ \end{verbatim}
+
+ The most direct way to terminate a script is to use \samp{sys.exit()}.
+
+
+ \section{String Pattern Matching\label{string-pattern-matching}}
+
+ The \ulink{\module{re}}{../lib/module-re.html}
+ module provides regular expression tools for advanced string processing.
+ When only simple capabilities are needed, string methods are preferred
+ because they are easier to read and debug. However, for more
+ sophisticated applications, regular expressions can provide succinct,
+ optimized solutions:
+
+ \begin{verbatim}
+ >>> import re
+ >>> re.findall(r'\bf[a-z]*', 'which foot or hand fell fastest')
+ ['foot', 'fell', 'fastest']
+ >>> re.sub(r'(\b[a-z]+) \1', r'\1', 'cat in the the hat')
+ 'cat in the hat'
+ \end{verbatim}
+
+
+ \section{Mathematics\label{mathematics}}
+
+ The \ulink{\module{math}}{../lib/module-math.html} math module gives
+ access to the underlying C library functions for floating point math:
+
+ \begin{verbatim}
+ >>> import math
+ >>> math.cos(math.pi / 4.0)
+ 0.70710678118654757
+ >>> math.log(1024, 2)
+ 10.0
+ \end{verbatim}
+
+ The \ulink{\module{random}}{../lib/module-random.html}
+ module provides tools for making random selections:
+
+ \begin{verbatim}
+ >>> import random
+ >>> random.choice(['apple', 'pear', 'banana'])
+ 'apple'
+ >>> random.sample(xrange(100), 10) # sampling without replacement
+ [30, 83, 16, 4, 8, 81, 41, 50, 18, 33]
+ >>> random.random() # random float
+ 0.17970987693706186
+ >>> random.randrange(6) # random integer chosen from range(6)
+ 4
+ \end{verbatim}
+
+
+ \section{Internet Access\label{internet-access}}
+
+ There are a number of modules for accessing the internet and processing
+ internet protocols. Two of the simplest are
+ \ulink{\module{urllib2}}{../lib/module-urllib2.html}
+ for retrieving data from urls and
+ \ulink{\module{smtplib}}{../lib/module-smtplib.html}
+ for sending mail:
+
+ \begin{verbatim}
+ >>> import urllib2
+ >>> for line in urllib2.urlopen('http://tycho.usno.navy.mil/cgi-bin/timer.pl'):
+ ... if 'EST' in line: # look for Eastern Standard Time
+ ... print line
+
+ <BR>Nov. 25, 09:43:32 PM EST
+
+ >>> import smtplib
+ >>> server = smtplib.SMTP('localhost')
+ >>> server.sendmail('soothsayer at tmp.org', 'jceasar at tmp.org',
+ """To: jceasar at tmp.org
+ From: soothsayer at tmp.org
+
+ Beware the Ides of March.
+ """)
+ >>> server.quit()
+ \end{verbatim}
+
+
+ \section{Dates and Times\label{dates-and-times}}
+
+ The \ulink{\module{datetime}}{../lib/module-datetime.html} module
+ supplies classes for manipulating dates and times in both simple
+ and complex ways. While date and time arithmetic is supported, the
+ focus of the implementation is on efficient member extraction for
+ output formatting and manipulation. The module also supports objects
+ that are time zone aware.
+
+ \begin{verbatim}
+ # dates are easily constructed and formatted
+ >>> from datetime import date
+ >>> now = date.today()
+ >>> now
+ datetime.date(2003, 12, 2)
+ >>> now.strftime("%m-%d-%y or %d%b %Y is a %A on the %d day of %B")
+ '12-02-03 or 02Dec 2003 is a Tuesday on the 02 day of December'
+
+ # dates support calendar arithmetic
+ >>> birthday = date(1964, 7, 31)
+ >>> age = now - birthday
+ >>> age.days
+ 14368
+ \end{verbatim}
+
+
+ \section{Data Compression\label{data-compression}}
+
+ Common data archiving and compression formats are directly supported
+ by modules including: \module{zlib}, \module{gzip}, \module{bz2},
+ \module{zipfile}, and \module{tar}.
+
+ \begin{verbatim}
+ >>> import zlib
+ >>> s = 'witch which has which witches wrist watch'
+ >>> len(s)
+ 41
+ >>> t = zlib.compress(s)
+ >>> len(t)
+ 37
+ >>> zlib.decompress(t)
+ 'witch which has which witches wrist watch'
+ >>> zlib.crc32(t)
+ -1438085031
+ \end{verbatim}
+
+
+ \section{Performance Measurement\label{performance-measurement}}
+
+ Some Python users develop a deep interest in knowing the relative
+ performance between different approaches to the same problem.
+ Python provides a measurement tool that answers those questions
+ immediately.
+
+ For example, it may be tempting to use the tuple packing and unpacking
+ feature instead of the traditional approach to swapping arguments.
+ The \ulink{\module{timeit}}{../lib/module-timeit.html} module
+ quickly demonstrates that the traditional approach is faster:
+
+ \begin{verbatim}
+ >>> from timeit import Timer
+ >>> dir(Timer)
+ >>> Timer('t=a; a=b; b=t', 'a=1; b=1').timeit()
+ 0.60864915603680925
+ >>> Timer('a,b = b,a', 'a=1; b=1').timeit()
+ 0.8625194857439773
+ \end{verbatim}
+
+ In contrast to \module{timeit}'s fine level of granularity, the
+ \ulink{\module{profile}}{../lib/module-profile.html} and \module{pstats}
+ modules provide tools for identifying time critical sections in larger
+ blocks of code.
+
+
+ \section{Quality Control\label{quality-control}}
+
+ One approach for developing high quality software is to write tests for
+ each function as it is developed and to run those tests frequently during
+ the development process.
+
+ The \ulink{\module{doctest}}{../lib/module-doctest.html} module provides
+ a tool for scanning a module and validating tests embedded in a program's
+ docstrings. Test construction is as simple as cutting-and-pasting a
+ typical call along with its results into the docstring. This improves
+ the documentation by providing the user with an example and it allows the
+ doctest module to make sure the code remains true to the documentation:
+
+ \begin{verbatim}
+ def average(values):
+ """Computes the arithmetic mean of a list of numbers.
+
+ >>> print average([20, 30, 70])
+ 40.0
+ """
+ return sum(values, 0.0) / len(values)
+
+ import doctest
+ doctest.testmod() # automatically validate the embedded tests
+ \end{verbatim}
+
+ The \ulink{\module{unittest}}{../lib/module-unittest.html} module is not
+ as effortless as the \module{doctest} module, but it allows a more
+ comprehensive set of tests to be maintained in a separate file:
+
+ \begin{verbatim}
+ import unittest
+
+ class TestStatisticalFunctions(unittest.TestCase):
+
+ def test_average(self):
+ self.assertEqual(average([20, 30, 70]), 40.0)
+ self.assertEqual(round(average([1, 5, 7]), 1), 4.3)
+ self.assertRaises(ZeroDivisionError, average, [])
+ self.assertRaises(TypeError, average, 20, 30, 70)
+
+ unittest.main() # Calling from the command line invokes all tests
+ \end{verbatim}
+
+ \section{Batteries Included\label{batteries-included}}
+
+ Python has a ``batteries included'' philosophy. The is best seen
+ through the sophisticated and robust capabilites of its larger
+ packages. For example:
+
+ * The \module{xmlrpclib} and \module{SimpleXMLRPCServer} modules make
+ implementing remote procedure calls into an almost trivial task.
+ Despite the names, no direct knowledge or handling of XML is needed.
+
+ * The \module{email} package is a library for managing email messages,
+ including MIME and other RFC 2822-based message documents. Unlike
+ \module{smtplib} and \module{poplib} which actually send and receive
+ messages, the email package has a complete toolset for building or
+ decoding complex message structures (including attachments)
+ and for implementing internet encoding and header protocols.
+
+ * The \module{xml.dom} and \module{xml.sax} packages provide robust
+ support for parsing this popular data interchange format. Likewise,
+ the \module{csv} module supports direct reads and writes in a common
+ database format. Together, these modules and packages greatly simplify
+ data interchange between python applications and other tools.
+
+ * Internationalization is supported by a number of modules including
+ \module{gettext}, \module{locale}, and the \module{codecs} package.
+
+
+
\chapter{What Now? \label{whatNow}}
***************
*** 4804,4807 ****
--- 5123,5130 ----
\chapter{History and License}
\input{license}
+
+ \input{glossary}
+
+ \input{tut.ind}
\end{document}
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