이 장에서는 이전에 소개된 콘텐츠 중 일부를 자세히 설명하고 새로운 콘텐츠도 소개합니다.
목록 데이터 유형에는 더 많은 메서드가 있으며 다음은 목록 개체의 모든 메서드입니다.
list.append(x)
a[len(a):] = [x]
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):] = iterable
list.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。
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>
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>
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
에 해당하는 목록 끝에 새 항목을 추가합니다.
list.extend(반복 가능)
a[len(a):] = iterable
list.insert(i, x)
a.insert(0, x)
가 목록 앞에 삽입됩니다(a.insert). (len( a), x)
는 a.append(x)
와 동일합니다. list.remove(x)
x
인 첫 번째 항목을 제거합니다. x
가 없으면 메서드에서 예외가 발생합니다(ValueError
예외)🎜
🎜🎜list.pop([i])
a.pop()
는 목록의 마지막 항목을 제거하고 반환합니다. (메서드 서명에서 i
를 둘러싼 대괄호는 이 위치에 대괄호를 쓰는 대신 매개변수가 선택 사항임을 나타냅니다. 이 표기법은 Python 라이브러리 참조에서 자주 사용됩니다) 🎜
🎜🎜list.clear()
del a[:]
🎜에 해당하는 목록에서 모든 항목을 제거합니다.
🎜🎜list.index(x[, start[, end]])
x
인 첫 번째 항목의 0부터 시작하는 인덱스를 반환하거나, x
가 존재하지 않으면 ValueError
예외를 발생시킵니다. list.count(x)
list.sort(key=None, reverse=False)
sorted()
를 참조하세요) 🎜
🎜🎜list.reverse()
list.copy()
a[:]
🎜와 동일한 목록의 얕은 복사본을 반환합니다.
🎜다음은 목록 방법을 보여주는 예입니다. 🎜
🎜rreee🎜
🎜insert, reverse
또는 sort
등은 목록만 변경하고 반환 값은 인쇄하지 않습니다. 기본 None
[을 반환합니다. 1]. 이는 Python의 변경 가능한 데이터 구조에 적용되는 설계 원칙입니다. 🎜
append()
메서드를 사용하여 스택 맨 위에 요소를 추가하고, 매개변수 없이 pop()
을 사용하여 스택에서 맨 위 요소를 팝합니다. 예: 🎜
🎜rreee🎜
collections.deque
는 양쪽 끝에서 요소를 빠르게 추가 및 삭제하고 대기열을 구현하는 데 사용할 수 있습니다. 예: 🎜
🎜rreee🎜
x
라는 변수를 생성(또는 다시 작성)합니다. 부작용 없이 제곱 목록을 만들려면 다음 방법을 사용하세요. 🎜
🎜rreee🎜
🎜또는 등: 🎜
🎜rreee🎜
🎜이 방법이 더 간결하고 읽기 쉽습니다. 🎜
🎜for
절 다음에 0개 이상의 for
절이나 if
절과 대괄호를 더한 표현식이 뒤따라 목록 이해를 형성합니다. 반환 결과는 표현식에 있는 for
및 if
절의 평가 결과를 요소로 포함하는 새 목록입니다. 예를 들어, 다음 목록 이해는 두 목록의 동일하지 않은 요소를 결합합니다. 🎜
🎜rreee🎜
🎜동일: 🎜
🎜rreee🎜
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>
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。
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
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
)
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>
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>
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>
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
[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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