[译]The Python Tutorial#Data Structures
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[译]The Python Tutorial#Data Structures
5.1 Data Structures
本章节详细介绍之前介绍过的一些内容，并且也会介绍一些新的内容。
5.1 More on Lists
列表数据类型拥有更多方法，以下是列表对象的所有方法：
list.append(x)
在列表末尾添加新项，等同于a[len(a):] = [x]list.extend(iterable)
添加可迭代对象中所有的项来扩展列表，等同于a[len(a):] = iterablelist.insert(i, x)
在指定位置插入项。第一个参数为元素索引，新的项会在这个索引之前插入，因此a.insert(0, x)会在列表最前面插入，a.insert(len(a), x)等同于a.append(x)。list.remove(x)
从列表中移除值为x的第一个项，若x不存在，方法抛出异常(ValueError异常)list.pop([i])
从列表中移除指定位置的项并返回。如果没有指定索引，a.pop()移除并返回列表中最后一个项。（方法签名中包裹i的方括号表示参数是可选的，而不是在这个位置写一个方括号。这种记号法在Python Library Reference中经常用到）list.clear()
移除列表中的所有项，等同于del a[:]list.index(x[, start[, end]])
返回第一个值为x的项的基于0的索引，如果x不存在抛出ValueError异常。
可选参数start和end被解释为切片记号法，用来将搜索限制在列表特定的子列表内。返回的索引是相对于完整列表索引，而不是相对于start参数的。list.count(x)
返回列表中x出现的次数list.sort(key=None, reverse=False)
对列表的所有项进行排序（参数用来自定义排序，参见sorted()获取更多信息）list.reverse()
反转列表元素list.copy()
返回列表的浅拷贝，等同于a[:]
以下是演示列表方法的例子：
<code class="sourceCode python"><span class="op">>>></span> fruits <span class="op">=</span> [<span class="st">'orange'</span>, <span class="st">'apple'</span>, <span class="st">'pear'</span>, <span class="st">'banana'</span>, <span class="st">'kiwi'</span>, <span class="st">'apple'</span>, <span class="st">'banana'</span>] <span class="op">>>></span> fruits.count(<span class="st">'apple'</span>) <span class="dv">2</span> <span class="op">>>></span> fruits.count(<span class="st">'tangerine'</span>) <span class="dv">0</span> <span class="op">>>></span> fruits.index(<span class="st">'banana'</span>) <span class="dv">3</span> <span class="op">>>></span> fruits.index(<span class="st">'banana'</span>, <span class="dv">4</span>) <span class="co"># Find next banana starting a position 4</span> <span class="dv">6</span> <span class="op">>>></span> fruits.reverse() <span class="op">>>></span> fruits [<span class="st">'banana'</span>, <span class="st">'apple'</span>, <span class="st">'kiwi'</span>, <span class="st">'banana'</span>, <span class="st">'pear'</span>, <span class="st">'apple'</span>, <span class="st">'orange'</span>] <span class="op">>>></span> fruits.append(<span class="st">'grape'</span>) <span class="op">>>></span> fruits [<span class="st">'banana'</span>, <span class="st">'apple'</span>, <span class="st">'kiwi'</span>, <span class="st">'banana'</span>, <span class="st">'pear'</span>, <span class="st">'apple'</span>, <span class="st">'orange'</span>, <span class="st">'grape'</span>] <span class="op">>>></span> fruits.sort() <span class="op">>>></span> fruits [<span class="st">'apple'</span>, <span class="st">'apple'</span>, <span class="st">'banana'</span>, <span class="st">'banana'</span>, <span class="st">'grape'</span>, <span class="st">'kiwi'</span>, <span class="st">'orange'</span>, <span class="st">'pear'</span>] <span class="op">>>></span> fruits.pop() <span class="co">'pear'</span></code>
诸如insert, reverse或者sort的这样，只改变了列表但是没有返回值打印，它们返回默认的None[1]。这是Python可变数据结构适用的设计原则。
5.1.1 Using Lists as Stacks
列表方法使得将其用作栈非常容易，栈中最后一个加入的元素第一个被释放（后进先出）。使用append()方法添加元素到栈顶，使用不带参数的pop()将栈顶元素出栈。示例：
<code class="sourceCode python"><span class="op">>>></span> stack <span class="op">=</span> [<span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>] <span class="op">>>></span> stack.append(<span class="dv">6</span>) <span class="op">>>></span> stack.append(<span class="dv">7</span>) <span class="op">>>></span> stack [<span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>, <span class="dv">7</span>] <span class="op">>>></span> stack.pop() <span class="dv">7</span> <span class="op">>>></span> stack [<span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>] <span class="op">>>></span> stack.pop() <span class="dv">6</span> <span class="op">>>></span> stack.pop() <span class="dv">5</span> <span class="op">>>></span> stack [<span class="dv">3</span>, <span class="dv">4</span>]</code>
5.1.2 Using Lists as Queues
将列表用作队列也是可能的，队列中先添加的元素先释放（先进先出）；然而，这样用列表效率非常不高。因为在列表末尾添加和取出元素很快，但是在列表开头插入或者删除元素很慢（因为不得不将其他所有元素位移一位）。
经过特殊设计的collections.deque在首尾两端添加和删除元素都很快，可以使用它来实现队列。示例：
<code class="sourceCode python"><span class="op">>>></span> <span class="im">from</span> collections <span class="im">import</span> deque <span class="op">>>></span> queue <span class="op">=</span> deque([<span class="st">"Eric"</span>, <span class="st">"John"</span>, <span class="st">"Michael"</span>]) <span class="op">>>></span> queue.append(<span class="st">"Terry"</span>) <span class="co"># Terry arrives</span> <span class="op">>>></span> queue.append(<span class="st">"Graham"</span>) <span class="co"># Graham arrives</span> <span class="op">>>></span> queue.popleft() <span class="co"># The first to arrive now leaves</span> <span class="co">'Eric'</span> <span class="op">>>></span> queue.popleft() <span class="co"># The second to arrive now leaves</span> <span class="co">'John'</span> <span class="op">>>></span> queue <span class="co"># Remaining queue in order of arrival</span> deque([<span class="st">'Michael'</span>, <span class="st">'Terry'</span>, <span class="st">'Graham'</span>])</code>
5.1.3 List Comprehensions
列表推导式为创建列表提供了简洁方式。一般的应用方式是：创建新列表，列表元素是对其他序列或者可迭代对象操作的结果；或者创建元素满足特定条件的子序列。
假如希望创建一个平方列表：
<code class="sourceCode python"><span class="op">>>></span> squares <span class="op">=</span> [] <span class="op">>>></span> <span class="cf">for</span> x <span class="op">in</span> <span class="bu">range</span>(<span class="dv">10</span>): ... squares.append(x<span class="op">**</span><span class="dv">2</span>) ... <span class="op">>>></span> squares [<span class="dv">0</span>, <span class="dv">1</span>, <span class="dv">4</span>, <span class="dv">9</span>, <span class="dv">16</span>, <span class="dv">25</span>, <span class="dv">36</span>, <span class="dv">49</span>, <span class="dv">64</span>, <span class="dv">81</span>]</code>
注意以上创建（或者重写）了名为x的变量，该变量在循环结束之后仍然存在。使用以下方法可创建没有任何副作用的平方列表：
<code class="sourceCode python">squares <span class="op">=</span> <span class="bu">list</span>(<span class="bu">map</span>(<span class="kw">lambda</span> x: x<span class="op">**</span><span class="dv">2</span>, <span class="bu">range</span>(<span class="dv">10</span>)))</code>
或者，等用于：
<code class="sourceCode python">squares <span class="op">=</span> [x<span class="op">**</span><span class="dv">2</span> <span class="cf">for</span> x <span class="op">in</span> <span class="bu">range</span>(<span class="dv">10</span>)]</code>
这种方式更加简洁和易读。
跟随着for子句，紧接零个或者多个for子句或者if子句的表达式再加上中括号，构成了列表推导式。其返回结果是一个新的列表，列表的元素是表达式中for和if子句的计算结果。例如，以下列表推导式组合两个列表中不相等的元素：
<code class="sourceCode python"><span class="op">>>></span> [(x, y) <span class="cf">for</span> x <span class="op">in</span> [<span class="dv">1</span>,<span class="dv">2</span>,<span class="dv">3</span>] <span class="cf">for</span> y <span class="op">in</span> [<span class="dv">3</span>,<span class="dv">1</span>,<span class="dv">4</span>] <span class="cf">if</span> x <span class="op">!=</span> y] [(<span class="dv">1</span>, <span class="dv">3</span>), (<span class="dv">1</span>, <span class="dv">4</span>), (<span class="dv">2</span>, <span class="dv">3</span>), (<span class="dv">2</span>, <span class="dv">1</span>), (<span class="dv">2</span>, <span class="dv">4</span>), (<span class="dv">3</span>, <span class="dv">1</span>), (<span class="dv">3</span>, <span class="dv">4</span>)]</code>
等价于：
<code class="sourceCode python"><span class="op">>>></span> combs <span class="op">=</span> [] <span class="op">>>></span> <span class="cf">for</span> x <span class="op">in</span> [<span class="dv">1</span>,<span class="dv">2</span>,<span class="dv">3</span>]: ... <span class="cf">for</span> y <span class="op">in</span> [<span class="dv">3</span>,<span class="dv">1</span>,<span class="dv">4</span>]: ... <span class="cf">if</span> x <span class="op">!=</span> y: ... combs.append((x, y)) ... <span class="op">>>></span> combs [(<span class="dv">1</span>, <span class="dv">3</span>), (<span class="dv">1</span>, <span class="dv">4</span>), (<span class="dv">2</span>, <span class="dv">3</span>), (<span class="dv">2</span>, <span class="dv">1</span>), (<span class="dv">2</span>, <span class="dv">4</span>), (<span class="dv">3</span>, <span class="dv">1</span>), (<span class="dv">3</span>, <span class="dv">4</span>)]</code>
注意上面两个代码段中for和if语句的顺序是相同的。
如果表达式是一个元组（如上所示的(x, y)），必须将其加上括号。
<code class="sourceCode python"><span class="op">>>></span> vec <span class="op">=</span> [<span class="op">-</span><span class="dv">4</span>, <span class="op">-</span><span class="dv">2</span>, <span class="dv">0</span>, <span class="dv">2</span>, <span class="dv">4</span>]
<span class="op">>>></span> <span class="co"># create a new list with the values doubled</span>
<span class="op">>>></span> [x<span class="op">*</span><span class="dv">2</span> <span class="cf">for</span> x <span class="op">in</span> vec]
[<span class="op">-</span><span class="dv">8</span>, <span class="op">-</span><span class="dv">4</span>, <span class="dv">0</span>, <span class="dv">4</span>, <span class="dv">8</span>]
<span class="op">>>></span> <span class="co"># filter the list to exclude negative numbers</span>
<span class="op">>>></span> [x <span class="cf">for</span> x <span class="op">in</span> vec <span class="cf">if</span> x <span class="op">>=</span> <span class="dv">0</span>]
[<span class="dv">0</span>, <span class="dv">2</span>, <span class="dv">4</span>]
<span class="op">>>></span> <span class="co"># apply a function to all the elements</span>
<span class="op">>>></span> [<span class="bu">abs</span>(x) <span class="cf">for</span> x <span class="op">in</span> vec]
[<span class="dv">4</span>, <span class="dv">2</span>, <span class="dv">0</span>, <span class="dv">2</span>, <span class="dv">4</span>]
<span class="op">>>></span> <span class="co"># call a method on each element</span>
<span class="op">>>></span> freshfruit <span class="op">=</span> [<span class="st">' banana'</span>, <span class="st">' loganberry '</span>, <span class="st">'passion fruit '</span>]
<span class="op">>>></span> [weapon.strip() <span class="cf">for</span> weapon <span class="op">in</span> freshfruit]
[<span class="st">'banana'</span>, <span class="st">'loganberry'</span>, <span class="st">'passion fruit'</span>]
<span class="op">>>></span> <span class="co"># create a list of 2-tuples like (number, square)</span>
<span class="op">>>></span> [(x, x<span class="op">**</span><span class="dv">2</span>) <span class="cf">for</span> x <span class="op">in</span> <span class="bu">range</span>(<span class="dv">6</span>)]
[(<span class="dv">0</span>, <span class="dv">0</span>), (<span class="dv">1</span>, <span class="dv">1</span>), (<span class="dv">2</span>, <span class="dv">4</span>), (<span class="dv">3</span>, <span class="dv">9</span>), (<span class="dv">4</span>, <span class="dv">16</span>), (<span class="dv">5</span>, <span class="dv">25</span>)]
<span class="op">>>></span> <span class="co"># the tuple must be parenthesized, otherwise an error is raised</span>
<span class="op">>>></span> [x, x<span class="op">**</span><span class="dv">2</span> <span class="cf">for</span> x <span class="op">in</span> <span class="bu">range</span>(<span class="dv">6</span>)]
File <span class="st">"<stdin>"</span>, line <span class="dv">1</span>, <span class="op">in</span> <span class="op"><</span>module<span class="op">></span>
[x, x<span class="op">**</span><span class="dv">2</span> <span class="cf">for</span> x <span class="op">in</span> <span class="bu">range</span>(<span class="dv">6</span>)]
<span class="op">^</span>
<span class="pp">SyntaxError</span>: invalid syntax
<span class="op">>>></span> <span class="co"># flatten a list using a listcomp with two 'for'</span>
<span class="op">>>></span> vec <span class="op">=</span> [[<span class="dv">1</span>,<span class="dv">2</span>,<span class="dv">3</span>], [<span class="dv">4</span>,<span class="dv">5</span>,<span class="dv">6</span>], [<span class="dv">7</span>,<span class="dv">8</span>,<span class="dv">9</span>]]
<span class="op">>>></span> [num <span class="cf">for</span> elem <span class="op">in</span> vec <span class="cf">for</span> num <span class="op">in</span> elem]
[<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>, <span class="dv">6</span>, <span class="dv">7</span>, <span class="dv">8</span>, <span class="dv">9</span>]</code>列表推导式可以包含复杂的表达式甚至嵌套函数：
<code class="sourceCode python"><span class="op">>>></span> <span class="im">from</span> math <span class="im">import</span> pi <span class="op">>>></span> [<span class="bu">str</span>(<span class="bu">round</span>(pi, i)) <span class="cf">for</span> i <span class="op">in</span> <span class="bu">range</span>(<span class="dv">1</span>, <span class="dv">6</span>)] [<span class="st">'3.1'</span>, <span class="st">'3.14'</span>, <span class="st">'3.142'</span>, <span class="st">'3.1416'</span>, <span class="st">'3.14159'</span>]</code>
5.1.4 Nested List Comprehensions
列表推导式开头的表达式可以是任意表达式，包括另一个列表推导式。
考虑以下示例，一个包含3个长度为4的列表的列表实现了3x4的矩阵：
<code class="sourceCode python">matrix <span class="op">=</span> [
[<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>],
[<span class="dv">5</span>, <span class="dv">6</span>, <span class="dv">7</span>, <span class="dv">8</span>],
[<span class="dv">9</span>, <span class="dv">10</span>, <span class="dv">11</span>, <span class="dv">12</span>],
]</code>以下列表推导式反转行列：
<code class="sourceCode python"><span class="op">>>></span> [[row[i] <span class="cf">for</span> row <span class="op">in</span> matrix] <span class="cf">for</span> i <span class="op">in</span> <span class="bu">range</span>(<span class="dv">4</span>)] [[<span class="dv">1</span>, <span class="dv">5</span>, <span class="dv">9</span>], [<span class="dv">2</span>, <span class="dv">6</span>, <span class="dv">10</span>], [<span class="dv">3</span>, <span class="dv">7</span>, <span class="dv">11</span>], [<span class="dv">4</span>, <span class="dv">8</span>, <span class="dv">12</span>]]</code>
前面的章节提到，嵌套的列表推导式是在其后跟随的for的上下文中求值的，因此这个示例等同于：
<code class="sourceCode python"><span class="op">>>></span> transposed <span class="op">=</span> [] <span class="op">>>></span> <span class="cf">for</span> i <span class="op">in</span> <span class="bu">range</span>(<span class="dv">4</span>): ... transposed.append([row[i] <span class="cf">for</span> row <span class="op">in</span> matrix]) ... <span class="op">>>></span> transposed [[<span class="dv">1</span>, <span class="dv">5</span>, <span class="dv">9</span>], [<span class="dv">2</span>, <span class="dv">6</span>, <span class="dv">10</span>], [<span class="dv">3</span>, <span class="dv">7</span>, <span class="dv">11</span>], [<span class="dv">4</span>, <span class="dv">8</span>, <span class="dv">12</span>]]</code>
依次等同于：
<code class="sourceCode python"><span class="op">>>></span> transposed <span class="op">=</span> [] <span class="op">>>></span> <span class="cf">for</span> i <span class="op">in</span> <span class="bu">range</span>(<span class="dv">4</span>): ... <span class="co"># the following 3 lines implement the nested listcomp</span> ... transposed_row <span class="op">=</span> [] ... <span class="cf">for</span> row <span class="op">in</span> matrix: ... transposed_row.append(row[i]) ... transposed.append(transposed_row) <span class="op">>>></span> transposed [[<span class="dv">1</span>, <span class="dv">5</span>, <span class="dv">9</span>], [<span class="dv">2</span>, <span class="dv">6</span>, <span class="dv">10</span>], [<span class="dv">3</span>, <span class="dv">7</span>, <span class="dv">11</span>], [<span class="dv">4</span>, <span class="dv">8</span>, <span class="dv">12</span>]]</code>
在实践中，应该选择built-in函数来复合流程语句。在以上的用例中zip()函数更有用：
<code class="sourceCode python"><span class="op">>>></span> <span class="bu">list</span>(<span class="bu">zip</span>(<span class="op">*</span>matrix)) [(<span class="dv">1</span>, <span class="dv">5</span>, <span class="dv">9</span>), (<span class="dv">2</span>, <span class="dv">6</span>, <span class="dv">10</span>), (<span class="dv">3</span>, <span class="dv">7</span>, <span class="dv">11</span>), (<span class="dv">4</span>, <span class="dv">8</span>, <span class="dv">12</span>)]</code>
参见 Unpacking Argument Lists了解关于上面*使用的更多详细信息。
5.2 The del statement
在提供列表索引而不是值的情况下，有一种方法可以移除列表中的元素：del语句。这种方式与返回值的pop()方法不同。del语句也可以用来移除部分列表或者清除整个列表（之前使用将空的列表赋值给列表片段的方式实现）。示例：
<code class="sourceCode python"><span class="op">>>></span> a <span class="op">=</span> [<span class="op">-</span><span class="dv">1</span>, <span class="dv">1</span>, <span class="fl">66.25</span>, <span class="dv">333</span>, <span class="dv">333</span>, <span class="fl">1234.5</span>] <span class="op">>>></span> <span class="kw">del</span> a[<span class="dv">0</span>] <span class="op">>>></span> a [<span class="dv">1</span>, <span class="fl">66.25</span>, <span class="dv">333</span>, <span class="dv">333</span>, <span class="fl">1234.5</span>] <span class="op">>>></span> <span class="kw">del</span> a[<span class="dv">2</span>:<span class="dv">4</span>] <span class="op">>>></span> a [<span class="dv">1</span>, <span class="fl">66.25</span>, <span class="fl">1234.5</span>] <span class="op">>>></span> <span class="kw">del</span> a[:] <span class="op">>>></span> a []</code>
del也可以用来删除整个变量：
<code class="sourceCode python"><span class="op">>>></span> <span class="kw">del</span> a</code>
此后引用名字a会抛出异常（至少在其他值赋值给名字a之前）。接下来会有更多del的使用
5.3 Tuples and Sequences
列表和字符串有很多常用属性，比如索引和切片操作。它们是序列数据类型（参见 Sequence Types - list, tuple, range）的两种。Python是一种不断进化的语言，其他的序列类型也可以加入。元组是另一种标准的序列数据类型。
元组包含若干由逗号分隔的值，示例：
<code class="sourceCode python"><span class="op">>>></span> t <span class="op">=</span> <span class="dv">12345</span>, <span class="dv">54321</span>, <span class="st">'hello!'</span> <span class="op">>>></span> t[<span class="dv">0</span>] <span class="dv">12345</span> <span class="op">>>></span> t (<span class="dv">12345</span>, <span class="dv">54321</span>, <span class="st">'hello!'</span>) <span class="op">>>></span> <span class="co"># Tuples may be nested:</span> ... u <span class="op">=</span> t, (<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>) <span class="op">>>></span> u ((<span class="dv">12345</span>, <span class="dv">54321</span>, <span class="st">'hello!'</span>), (<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>, <span class="dv">4</span>, <span class="dv">5</span>)) <span class="op">>>></span> <span class="co"># Tuples are immutable:</span> ... t[<span class="dv">0</span>] <span class="op">=</span> <span class="dv">88888</span> Traceback (most recent call last): File <span class="st">"<stdin>"</span>, line <span class="dv">1</span>, <span class="op">in</span> <span class="op"><</span>module<span class="op">></span> <span class="pp">TypeError</span>: <span class="st">'tuple'</span> <span class="bu">object</span> does <span class="op">not</span> support item assignment <span class="op">>>></span> <span class="co"># but they can contain mutable objects:</span> ... v <span class="op">=</span> ([<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>], [<span class="dv">3</span>, <span class="dv">2</span>, <span class="dv">1</span>]) <span class="op">>>></span> v ([<span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">3</span>], [<span class="dv">3</span>, <span class="dv">2</span>, <span class="dv">1</span>])</code>
可见，输出的元组总是放在圆括号中，以便于嵌套的元组可以被正确解析；虽然圆括号总是必须的（如果元组是其他更大表达式的一部分），但是在输入元组的时候可以选择使用圆括号。不能对元组的单个项赋值，但是可以创建包含如列表的可变对象的元组。
虽然元组和列表有些相似，但是他们通常以不同的目的，用于不同的场景。元组是不可变的，通常包含不同类型的元素，可以通过拆包操作（参见后续章节）或者索引（或者当元组是命名元组时，甚至可以通过属性来访问）来访问。列表是可变的，通常其元素也是不同类型的，可以通过对列表的迭代访问元素。
构建包含零个或者1个项的元组比较特殊：一种额外的奇怪语法可以适用于这种情况。空元组由一对空的圆括号创建；一个元素的元组由一个跟着逗号的值创建（在圆括号中放入单个值是不够的。译注：这种情况：(1)表示整数而不是元组，使用(1, )表示元组也是可行的）。丑陋但是有效。示例：
<code class="sourceCode python"><span class="op">>>></span> empty <span class="op">=</span> () <span class="op">>>></span> singleton <span class="op">=</span> <span class="st">'hello'</span>, <span class="co"># <-- note trailing comma</span> <span class="op">>>></span> <span class="bu">len</span>(empty) <span class="dv">0</span> <span class="op">>>></span> <span class="bu">len</span>(singleton) <span class="dv">1</span> <span class="op">>>></span> singleton (<span class="st">'hello'</span>,)</code>
语句t = 12345, 54321, 'hello!'是封装元组的一个示例：值12345, 54321和hello!被封装到了一个元组中。逆向操作也是可行的：
<code class="sourceCode python"><span class="op">>>></span> x, y, z <span class="op">=</span> t</code>
非常恰当地称之为序列解包，适用于任何在等号右边的序列（译注：等号右操作数）。序列解包要求等号左边待赋值的变量数量与序列包含元素数目相同。注意多重赋值只是封装元组和序列解包的结合（译注：多重赋值：i, j = 1, 2）
5.4 Set
Python也包含实现了集合的数据类型。集合是无序不重复的元素集。基本功能包括成员关系测试和重复实体消除。集合对象也支持并集，交集，差集以及对称差集等数学操作。
可以使用花括号和set()函数创建集合。谨记：创建空集合必须使用set函数，不能使用{}，后者用于创建空字典。
以下是简单示范：
<code class="sourceCode python"><span class="op">>>></span> basket <span class="op">=</span> {<span class="st">'apple'</span>, <span class="st">'orange'</span>, <span class="st">'apple'</span>, <span class="st">'pear'</span>, <span class="st">'orange'</span>, <span class="st">'banana'</span>}
<span class="op">>>></span> <span class="bu">print</span>(basket) <span class="co"># show that duplicates have been removed</span>
{<span class="st">'orange'</span>, <span class="st">'banana'</span>, <span class="st">'pear'</span>, <span class="st">'apple'</span>}
<span class="op">>>></span> <span class="st">'orange'</span> <span class="op">in</span> basket <span class="co"># fast membership testing</span>
<span class="va">True</span>
<span class="op">>>></span> <span class="st">'crabgrass'</span> <span class="op">in</span> basket
<span class="va">False</span>
<span class="op">>>></span> <span class="co"># Demonstrate set operations on unique letters from two words</span>
...
<span class="op">>>></span> a <span class="op">=</span> <span class="bu">set</span>(<span class="st">'abracadabra'</span>)
<span class="op">>>></span> b <span class="op">=</span> <span class="bu">set</span>(<span class="st">'alacazam'</span>)
<span class="op">>>></span> a <span class="co"># unique letters in a</span>
{<span class="st">'a'</span>, <span class="st">'r'</span>, <span class="st">'b'</span>, <span class="st">'c'</span>, <span class="st">'d'</span>}
<span class="op">>>></span> a <span class="op">-</span> b <span class="co"># letters in a but not in b</span>
{<span class="st">'r'</span>, <span class="st">'d'</span>, <span class="st">'b'</span>}
<span class="op">>>></span> a <span class="op">|</span> b <span class="co"># letters in a or b or both</span>
{<span class="st">'a'</span>, <span class="st">'c'</span>, <span class="st">'r'</span>, <span class="st">'d'</span>, <span class="st">'b'</span>, <span class="st">'m'</span>, <span class="st">'z'</span>, <span class="st">'l'</span>}
<span class="op">>>></span> a <span class="op">&</span> b <span class="co"># letters in both a and b</span>
{<span class="st">'a'</span>, <span class="st">'c'</span>}
<span class="op">>>></span> a <span class="op">^</span> b <span class="co"># letters in a or b but not both</span>
{<span class="st">'r'</span>, <span class="st">'d'</span>, <span class="st">'b'</span>, <span class="st">'m'</span>, <span class="st">'z'</span>, <span class="st">'l'</span>}</code>与列表推导式相同，Python也支持集合推导式：
<code class="sourceCode python"><span class="op">>>></span> a <span class="op">=</span> {x <span class="cf">for</span> x <span class="op">in</span> <span class="st">'abracadabra'</span> <span class="cf">if</span> x <span class="op">not</span> <span class="op">in</span> <span class="st">'abc'</span>}
<span class="op">>>></span> a
{<span class="st">'r'</span>, <span class="st">'d'</span>}</code>5.5 Dictionaries
另一个内嵌入Python中的数据结构是字典（参见 Mapping Types - dict）。字典在其他一些语言中被称为“联合存储”或者“联合数组”。与序列不同，序列以一系列数字作索引，字典以键作索引，键可以是任何不可变类型；通常使用字符串和数字作为键。只包含字符串，数字或者其他元组的元组也可以作为键；直接或者间接包含可变对象的元组不能作为键。因为列表可以使用索引赋值，切片赋值或者append()以及extend()等方法改变自身，所以列表不能作为键。
最好的理解字典的方式是将其认为是键值对的无序集合，同一集合中键唯一。一对花括号创建空字典：{}。在花括号中放置由逗号分隔键值对列表可以为字典添加初始键值对；这也是字典输出的格式。
字典提供的主要操作是：使用键存储值以及取值。可以使用del删除一个键值对。如果使用已经存在的键来存储值，那么与键关联的旧值会被重写。使用不存在的键来取值会抛出异常。
在字典上执行list(d.keys())返回字典所有键的无序列表（使用sorted(d.keys())使其有序）[2]。使用关键字in检查键在字典中是否存在。
以下是使用字典的示例：
<code class="sourceCode python"><span class="op">>>></span> tel <span class="op">=</span> {<span class="st">'jack'</span>: <span class="dv">4098</span>, <span class="st">'sape'</span>: <span class="dv">4139</span>}
<span class="op">>>></span> tel[<span class="st">'guido'</span>] <span class="op">=</span> <span class="dv">4127</span>
<span class="op">>>></span> tel
{<span class="st">'sape'</span>: <span class="dv">4139</span>, <span class="st">'guido'</span>: <span class="dv">4127</span>, <span class="st">'jack'</span>: <span class="dv">4098</span>}
<span class="op">>>></span> tel[<span class="st">'jack'</span>]
<span class="dv">4098</span>
<span class="op">>>></span> <span class="kw">del</span> tel[<span class="st">'sape'</span>]
<span class="op">>>></span> tel[<span class="st">'irv'</span>] <span class="op">=</span> <span class="dv">4127</span>
<span class="op">>>></span> tel
{<span class="st">'guido'</span>: <span class="dv">4127</span>, <span class="st">'irv'</span>: <span class="dv">4127</span>, <span class="st">'jack'</span>: <span class="dv">4098</span>}
<span class="op">>>></span> <span class="bu">list</span>(tel.keys())
[<span class="st">'irv'</span>, <span class="st">'guido'</span>, <span class="st">'jack'</span>]
<span class="op">>>></span> <span class="bu">sorted</span>(tel.keys())
[<span class="st">'guido'</span>, <span class="st">'irv'</span>, <span class="st">'jack'</span>]
<span class="op">>>></span> <span class="st">'guido'</span> <span class="op">in</span> tel
<span class="va">True</span>
<span class="op">>>></span> <span class="st">'jack'</span> <span class="op">not</span> <span class="op">in</span> tel
<span class="va">False</span></code>dict()构造器直接使用键值对序列构造字典：
<code class="sourceCode python"><span class="op">>>></span> <span class="bu">dict</span>([(<span class="st">'sape'</span>, <span class="dv">4139</span>), (<span class="st">'guido'</span>, <span class="dv">4127</span>), (<span class="st">'jack'</span>, <span class="dv">4098</span>)])
{<span class="st">'sape'</span>: <span class="dv">4139</span>, <span class="st">'jack'</span>: <span class="dv">4098</span>, <span class="st">'guido'</span>: <span class="dv">4127</span>}</code>此外，字典推导式可以从任意键值表达式中创建字典：
<code class="sourceCode python"><span class="op">>>></span> {x: x<span class="op">**</span><span class="dv">2</span> <span class="cf">for</span> x <span class="op">in</span> (<span class="dv">2</span>, <span class="dv">4</span>, <span class="dv">6</span>)}
{<span class="dv">2</span>: <span class="dv">4</span>, <span class="dv">4</span>: <span class="dv">16</span>, <span class="dv">6</span>: <span class="dv">36</span>}</code>当键是简单的字符串时，可以使用关键字参数来指定键值对：
<code class="sourceCode python"><span class="op">>>></span> <span class="bu">dict</span>(sape<span class="op">=</span><span class="dv">4139</span>, guido<span class="op">=</span><span class="dv">4127</span>, jack<span class="op">=</span><span class="dv">4098</span>)
{<span class="st">'sape'</span>: <span class="dv">4139</span>, <span class="st">'jack'</span>: <span class="dv">4098</span>, <span class="st">'guido'</span>: <span class="dv">4127</span>}</code>5.6 Looping Techniques
遍历字典时，使用items()方法可以同时检索键及其对应的值。
<code class="sourceCode python"><span class="op">>>></span> knights <span class="op">=</span> {<span class="st">'gallahad'</span>: <span class="st">'the pure'</span>, <span class="st">'robin'</span>: <span class="st">'the brave'</span>}
<span class="op">>>></span> <span class="cf">for</span> k, v <span class="op">in</span> knights.items():
... <span class="bu">print</span>(k, v)
...
gallahad the pure
robin the brave</code>遍历序列时，使用enumerate()函数可以同时检索位置索引及其对应的值：
<code class="sourceCode python"><span class="op">>>></span> <span class="cf">for</span> i, v <span class="op">in</span> <span class="bu">enumerate</span>([<span class="st">'tic'</span>, <span class="st">'tac'</span>, <span class="st">'toe'</span>]): ... <span class="bu">print</span>(i, v) ... <span class="dv">0</span> tic <span class="dv">1</span> tac <span class="dv">2</span> toe</code>
同时遍历两个或者更多序列时，使用zip()函数可以将元素组成对：
<code class="sourceCode python"><span class="op">>>></span> questions <span class="op">=</span> [<span class="st">'name'</span>, <span class="st">'quest'</span>, <span class="st">'favorite color'</span>]
<span class="op">>>></span> answers <span class="op">=</span> [<span class="st">'lancelot'</span>, <span class="st">'the holy grail'</span>, <span class="st">'blue'</span>]
<span class="op">>>></span> <span class="cf">for</span> q, a <span class="op">in</span> <span class="bu">zip</span>(questions, answers):
... <span class="bu">print</span>(<span class="st">'What is your </span><span class="sc">{0}</span><span class="st">? It is </span><span class="sc">{1}</span><span class="st">.'</span>.<span class="bu">format</span>(q, a))
...
What <span class="op">is</span> your name? It <span class="op">is</span> lancelot.
What <span class="op">is</span> your quest? It <span class="op">is</span> the holy grail.
What <span class="op">is</span> your favorite color? It <span class="op">is</span> blue.</code>需要逆序遍历序列时，首先指定一个正向的序列，然后调用reversed()函数：
<code class="sourceCode python"><span class="op">>>></span> <span class="cf">for</span> i <span class="op">in</span> <span class="bu">reversed</span>(<span class="bu">range</span>(<span class="dv">1</span>, <span class="dv">10</span>, <span class="dv">2</span>)): ... <span class="bu">print</span>(i) ... <span class="dv">9</span> <span class="dv">7</span> <span class="dv">5</span> <span class="dv">3</span> <span class="dv">1</span></code>
需要以特定顺序遍历序列时，使用sorted()函数返回新的有序序列，原序列不会改动：
<code class="sourceCode python"><span class="op">>>></span> basket <span class="op">=</span> [<span class="st">'apple'</span>, <span class="st">'orange'</span>, <span class="st">'apple'</span>, <span class="st">'pear'</span>, <span class="st">'orange'</span>, <span class="st">'banana'</span>] <span class="op">>>></span> <span class="cf">for</span> f <span class="op">in</span> <span class="bu">sorted</span>(<span class="bu">set</span>(basket)): ... <span class="bu">print</span>(f) ... apple banana orange pear</code>
有时需要在遍历序列的同时修改序列，创建新的替代序列更加简单并且安全：
<code class="sourceCode python"><span class="op">>>></span> <span class="im">import</span> math <span class="op">>>></span> raw_data <span class="op">=</span> [<span class="fl">56.2</span>, <span class="bu">float</span>(<span class="st">'NaN'</span>), <span class="fl">51.7</span>, <span class="fl">55.3</span>, <span class="fl">52.5</span>, <span class="bu">float</span>(<span class="st">'NaN'</span>), <span class="fl">47.8</span>] <span class="op">>>></span> filtered_data <span class="op">=</span> [] <span class="op">>>></span> <span class="cf">for</span> value <span class="op">in</span> raw_data: ... <span class="cf">if</span> <span class="op">not</span> math.isnan(value): ... filtered_data.append(value) ... <span class="op">>>></span> filtered_data [<span class="fl">56.2</span>, <span class="fl">51.7</span>, <span class="fl">55.3</span>, <span class="fl">52.5</span>, <span class="fl">47.8</span>]</code>
5.7 More on Conditions
while和if语句中使用的条件可以包含任意操作符，不仅仅是比较运算符。
比较运算符in和not in检查指定值在序列中是否存在（不存在）。操作符is和is not比较两个对象是否真正相同（内存地址比较）；这两个操作符只对像列表那样的可变对象重要。所有的比较运算符拥有相同的优先级，并且都低于数字运算符。
比较运算符可以链接起来。例如a ebee1f8a764ba39dad659ec343d8da37比较不同类型的对象是合法的。例如，混合数字类型之间的比较是根据其数字上的值，0等于0.0。否则，解释器会抛出TypeException异常，而不是随意提供结果
Footnotes
[1] 其他语言可能返回改变后的对象，从而允许方法链接，如：d->insert("a")>remove("b")->sort();
[2] 调用d.keys()返回一个dictionary view对象。从而支持如成员关系测试和迭代之类的操作，但是其内容并不是独立于原始字典的，只是一个视图
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