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适合python初学者,一本很好的python学习书籍

important role in places where a constant hash value is needed.  For
example as a key in a dictionary.

<P>
<a id='l2h-70' xml:id='l2h-70'></a>
</DD>
<DT><STRONG>integer division</STRONG></DT>
<DD>Mathematical division discarding any remainder.  For example, the
expression <code>11/4</code> currently evaluates to <code>2</code> in contrast
to the <code>2.75</code> returned by float division.  Also called
<em>floor division</em>.  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
<tt class="class">float</tt>), the result will be coerced (see <em>coercion</em>) to
a common type.  For example, an 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>//</code> operator instead of the <code>/</code>
operator.  See also <em>__future__</em>.

<P>
<a id='l2h-71' xml:id='l2h-71'></a>
</DD>
<DT><STRONG>interactive</STRONG></DT>
<DD>Python has an interactive interpreter which means that you can try out
things and directly see its result.  Just launch <code>python</code> 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)</code>).

<P>
<a id='l2h-72' xml:id='l2h-72'></a>
</DD>
<DT><STRONG>interpreted</STRONG></DT>
<DD>Python is an interpreted language, as opposed to a compiled one.  This means
that the source files can be run directly without first creating an
executable which is then run.  Interpreted languages typically have a
shorter development/debug cycle than compiled ones, though their programs
generally also run more slowly.  See also <em>interactive</em>.

<P>
<a id='l2h-73' xml:id='l2h-73'></a>
</DD>
<DT><STRONG>iterable</STRONG></DT>
<DD>A container object capable of returning its members one at a time.
Examples of iterables include all sequence types (such as <tt class="class">list</tt>,
<tt class="class">str</tt>, and <tt class="class">tuple</tt>) and some non-sequence types like
<tt class="class">dict</tt> and <tt class="class">file</tt> and objects of any classes you define
with an <tt class="method">__iter__()</tt> or <tt class="method">__getitem__()</tt> method.  Iterables
can be used in a <tt class="keyword">for</tt> loop and in many other places where a
sequence is needed (<tt class="function">zip()</tt>, <tt class="function">map()</tt>, ...).  When an
iterable object is passed as an argument to the builtin function
<tt class="function">iter()</tt>, 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 <tt class="function">iter()</tt> or
deal with iterator objects yourself.  The <code>for</code> statement does
that automatically for you, creating a temporary unnamed variable to
hold the iterator for the duration of the loop.  See also
<em>iterator</em>, <em>sequence</em>, and <em>generator</em>.

<P>
<a id='l2h-74' xml:id='l2h-74'></a>
</DD>
<DT><STRONG>iterator</STRONG></DT>
<DD>An object representing a stream of data.  Repeated calls to the
iterator's <tt class="method">next()</tt> method return successive items in the
stream.  When no more data is available a <tt class="exception">StopIteration</tt>
exception is raised instead.  At this point, the iterator object is
exhausted and any further calls to its <tt class="method">next()</tt> method just
raise <tt class="exception">StopIteration</tt> again.  Iterators are required to have
an <tt class="method">__iter__()</tt> 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 <tt class="class">list</tt>) produces a fresh new iterator each time you
pass it to the <tt class="function">iter()</tt> function or use it in a
<tt class="keyword">for</tt> 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.

<P>
<a id='l2h-75' xml:id='l2h-75'></a>
</DD>
<DT><STRONG>list comprehension</STRONG></DT>
<DD>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]</code> generates a list of strings
containing hex numbers (0x..) that are even and in the range from 0 to 255.
The <tt class="keyword">if</tt> clause is optional.  If omitted, all elements in
<code>range(256)</code> are processed in that case.

<P>
<a id='l2h-76' xml:id='l2h-76'></a>
</DD>
<DT><STRONG>mapping</STRONG></DT>
<DD>A container object (such as <tt class="class">dict</tt>) that supports arbitrary key
lookups using the special method <tt class="method">__getitem__()</tt>.

<P>
<a id='l2h-77' xml:id='l2h-77'></a>
</DD>
<DT><STRONG>metaclass</STRONG></DT>
<DD>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.

<P>
<a id='l2h-78' xml:id='l2h-78'></a>
</DD>
<DT><STRONG>LBYL</STRONG></DT>
<DD>Look before you leap.  This coding style explicitly tests for
pre-conditions before making calls or lookups.  This style contrasts
with the <em>EAFP</em> approach and is characterized the presence of
many <tt class="keyword">if</tt> statements.

<P>
<a id='l2h-79' xml:id='l2h-79'></a>
</DD>
<DT><STRONG>mutable</STRONG></DT>
<DD>Mutable objects can change their value but keep their <tt class="function">id()</tt>.
See also <em>immutable</em>.

<P>
<a id='l2h-80' xml:id='l2h-80'></a>
</DD>
<DT><STRONG>namespace</STRONG></DT>
<DD>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 <tt class="function">__builtin__.open()</tt> and <tt class="function">os.open()</tt> are
distinguished by their namespaces.  Namespaces also aid readability
and maintainability by making it clear which modules implement a
function.  For instance, writing <tt class="function">random.seed()</tt> or
<tt class="function">itertools.izip()</tt> makes it clear that those functions are
implemented by the <a class="ulink" href="../lib/module-random.html"
  ><tt class="module">random</tt></a>
and <a class="ulink" href="../lib/module-itertools.html"
  ><tt class="module">itertools</tt></a> modules
respectively.

<P>
<a id='l2h-81' xml:id='l2h-81'></a>
</DD>
<DT><STRONG>nested scope</STRONG></DT>
<DD>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.

<P>
<a id='l2h-82' xml:id='l2h-82'></a>
</DD>
<DT><STRONG>new-style class</STRONG></DT>
<DD>Any class that inherits from <tt class="class">object</tt>.  This includes all
built-in types like <tt class="class">list</tt> and <tt class="class">dict</tt>.  Only new-style
classes can use Python's newer, versatile features like
<tt class="method">__slots__</tt>, descriptors, properties,
<tt class="method">__getattribute__()</tt>, class methods, and static methods.

<P>
<a id='l2h-83' xml:id='l2h-83'></a>
</DD>
<DT><STRONG>Python3000</STRONG></DT>
<DD>A mythical python release, allowed not to be backward compatible, with
telepathic interface.

<P>
<a id='l2h-84' xml:id='l2h-84'></a>
</DD>
<DT><STRONG>__slots__</STRONG></DT>
<DD>A declaration inside a <em>new-style class</em> 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.

<P>
<a id='l2h-85' xml:id='l2h-85'></a>
</DD>
<DT><STRONG>sequence</STRONG></DT>
<DD>An <em>iterable</em> which supports efficient element access using
integer indices via the <tt class="method">__getitem__()</tt> and
<tt class="method">__len__()</tt> special methods.  Some built-in sequence types
are <tt class="class">list</tt>, <tt class="class">str</tt>, <tt class="class">tuple</tt>, and <tt class="class">unicode</tt>.
Note that <tt class="class">dict</tt> also supports <tt class="method">__getitem__()</tt> and
<tt class="method">__len__()</tt>, but is considered a mapping rather than a
sequence because the lookups use arbitrary <em>immutable</em> keys
rather than integers.

<P>
<a id='l2h-86' xml:id='l2h-86'></a>
</DD>
<DT><STRONG>Zen of Python</STRONG></DT>
<DD>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</code>'' at the interactive prompt.

<P>
</DD>
</DL>

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