Fix spelling and add markup.

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Raymond Hettinger 2003-09-27 05:42:14 +00:00
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commit 5a25aa6c4a

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@ -1,6 +1,7 @@
\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}
@ -13,7 +14,7 @@ code for an indented code block.}
for code examples that can be tried right away in the interpreter.}
\index{__slots__}
\item[__slots__]{A declaration inside a new-style class that saves
\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
@ -24,7 +25,7 @@ of instances in a memory critical application.}
Rossum}{http://www.python.org/~guido/}, Python's creator.}
\index{byte code}
\item[byte code]{The internal represenatation of a Python program in the
\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
@ -37,51 +38,52 @@ See new-style class.}
\index{coercion}
\item[coercion]{Converting data from one type to another. For example,
int(3.15) coerces the floating point number to the integer, 3. Most
mathematical operations have rules for coercing their arguments to a common
type. For instance, adding 3 + 4.5, causes the integer 3 to be coerced to
be a float (3.0) before adding to 4.5 resulting in the float 7.5.}
{}\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 object that defines the methods __get__(), __set__(),
or __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
\item[descriptor]{Any 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 `dict` much resembles that for `list`, but the keys can
be any object with a `__hash__` function, not just integers starting from
zero. Called a hash in Perl.}
values. The use of \class{dict} much resembles that for \class{list}, but
the keys can be any object with a \function{__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 existance of valid keys or attributes and
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 `try` and `except` statments.
The technique contrasts with the '''LBYL''' style that is common in many
other languages such as C.}
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 ``true division`` by
executing}
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 __future__ module and evaluating its variables, you can see
when a new feature was first added to the language and when it will becode
the default:
importing the \module{__future__} 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__
@ -99,7 +101,7 @@ the caller. The function execution is stopped at the \keyword{yield} keyword
requested by calling the \function{next()} method of the returned iterator.}
\index{GIL}
\item[GIL]{See \em{global interpreter lock}.}
\item[GIL]{See \emph{global interpreter lock}.}
\index{global interpreter lock}
\item[global interpreter lock]{the lock used by Python threads to assure
@ -113,9 +115,9 @@ performance suffered in the common single-processor case.}
\index{IDLE}
\item[IDLE]{an Integrated Development Environment for Python. IDLE is a
basic editor and intepreter environment that ships with the standard
distribution of Python. Good for beginners and those on a budget, it also
serves as clear example code for those wanting to implement a moderately
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}
@ -127,15 +129,16 @@ 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 2 in contrast
to the 2.75 returned by float division. Also called "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 float), the result will be coerced (see 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, __future__.}
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
@ -147,16 +150,16 @@ 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 typicaly have
making an executable which is then run. Interpreted languages typically have
a shorter development/debug cycle than compiled ones. See also
{}\em{interactive}.}
{}\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 (\class{list},
{}\class{str}, \class{tuple}, etc.) and some non-sequence types like
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 \function{__iter__} or \function{__getitem__} method. Iterables can be
an \method{__iter__} or \function{__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
@ -165,23 +168,23 @@ 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
iterator, sequence and generator.}
\emph{iterator}, \emph{sequence} and \emph{generator}.}
\index{iterator}
\item[iterator]{An object representing a stream of data. Repeated calls to
the iterator's \function{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
exception is raised instead. At this point, the iterator object is exhausted
and any further calls to its \function{next()} method just raise
{}\exception{StopIteration} again. Iterators are required to have an
{}\function{__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 list) produces a
fresh new iterator each time you pass it to the \function{iter()} function
or use it in a \function{for} loop. Attempting this with an iterator will
just return the same exhausted iterator object from the second iteration
pass and on, making it appear like an empty container.}
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 \function{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
@ -209,8 +212,8 @@ 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 EAFP approach and is characterized the presence of many \keyword{if}
statements.}
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
@ -223,7 +226,7 @@ namespace and the nested namespaces in objects (in methods). Namespaces
support modularity by preventing naming conflicts. For instance, the
functions \function{__builtins__.open()} and \function{os.open()} are
distinguished by their namespaces. Namespaces also aid readability and
maintainabilty by making it clear which modules implement a function. For
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 \module{random}
and \module{itertools} modules respectively.}
@ -239,8 +242,8 @@ 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
includes all built-in types like \class{list} and \class{dict}. Only
new-style classes can use Python's newer, versatile features like
{}\var{__slots__}, descriptors, properties, \var{__getattribute__}, class
methods, and static methods.}
@ -249,17 +252,17 @@ methods, and static methods.}
compatible, with telepathic interface.}
\index{sequence}
\item[sequence]{An iterable which supports efficient element access using
\item[sequence]{An \emph{iterable} which supports efficient element access using
integer indices via the \function{__getitem__} and \function{__len()__}
special methods. Some builtin sequence types are \class{list}, \class{str},
{}\class{tuple}, and \class{unicode}. Note that \class{dict} also supports
{}\function{__getitem__} and \function{__len__}, but is considered a mapping
rather than a sequence because the lookups use arbitrary immutable keys
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 "import this" at the interactive prompt.}
be found by typing \code{import this} at the interactive prompt.}
\end{description}