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[译]파이썬 튜토리얼#데이터 구조

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2017-07-05 18:13:371306검색

[번역]파이썬 튜토리얼#데이터 구조

5.1 데이터 구조

이 장에서는 이전에 소개된 콘텐츠 중 일부를 자세히 설명하고 새로운 콘텐츠도 소개합니다.

5.1 목록에 대한 추가 정보

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startend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forif에 해당하는 목록 끝에 새 항목을 추가합니다.

list.extend(반복 가능)
a[len(a):] = iterable
과 동일하게 반복 가능한 객체에 모든 항목을 추가하여 목록을 확장합니다.

list.insert(i, x)
지정된 위치에 항목을 삽입합니다. 첫 번째 매개변수는 요소 인덱스입니다. 새 항목은 이 인덱스 앞에 삽입되므로 a.insert(0, x)가 목록 앞에 삽입됩니다(a.insert). (len( a), x)a.append(x)와 동일합니다.
🎜list.remove(x)
목록에서 값이 x인 첫 번째 항목을 제거합니다. x가 없으면 메서드에서 예외가 발생합니다(ValueError 예외)🎜 🎜🎜list.pop([i])
목록에서 지정된 위치에 있는 항목을 제거하고 반환합니다. 인덱스가 지정되지 않으면 a.pop()는 목록의 마지막 항목을 제거하고 반환합니다. (메서드 서명에서 i를 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]])
값이 x인 첫 번째 항목의 0부터 시작하는 인덱스를 반환하거나, x가 존재하지 않으면 ValueError 예외를 발생시킵니다.
선택적 인수 startend는 슬라이스 표기법으로 해석되며 검색을 목록의 특정 하위 목록으로 제한하는 데 사용됩니다. 반환된 인덱스는 start 매개변수가 아닌 전체 목록 인덱스를 기준으로 합니다. 🎜 🎜🎜list.count(x)
x가 목록에 나타나는 횟수를 반환합니다🎜 🎜🎜list.sort(key=None, reverse=False)
목록의 모든 항목을 정렬합니다(매개변수는 정렬을 사용자 정의하는 데 사용됩니다. 자세한 내용은 sorted()를 참조하세요) 🎜 🎜🎜list.reverse()
역방향 목록 요소🎜 🎜🎜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. 🎜

5.1.1 목록을 스택으로 사용

🎜리스트 방식을 사용하면 스택으로 사용하기가 매우 쉽습니다. 스택에 추가된 마지막 요소가 가장 먼저 해제됩니다(후입 선출). append() 메서드를 사용하여 스택 맨 위에 요소를 추가하고, 매개변수 없이 pop()을 사용하여 스택에서 맨 위 요소를 팝합니다. 예: 🎜 🎜rreee🎜

5.1.2 목록을 대기열로 사용

🎜목록을 대기열로 사용하는 것도 가능합니다. 대기열에 먼저 추가된 요소가 먼저 해제됩니다(선입선출). 그러나 이런 방식으로 목록을 사용하는 것은 매우 비효율적입니다. 목록 끝에 요소를 추가하고 제거하는 것은 빠르지만 목록의 시작 부분에 요소를 삽입하거나 삭제하는 것은 느리기 때문입니다(다른 모든 요소는 1씩 이동해야 하기 때문입니다). 🎜 🎜특별히 설계된 collections.deque는 양쪽 끝에서 요소를 빠르게 추가 및 삭제하고 대기열을 구현하는 데 사용할 수 있습니다. 예: 🎜 🎜rreee🎜

5.1.3 목록 이해

🎜List comprehension은 목록을 만드는 간결한 방법을 제공합니다. 일반적인 적용 방법은 다음과 같습니다. 새 목록을 생성하거나, 목록 요소가 다른 시퀀스나 반복 가능한 객체에 대한 작업의 결과이거나, 요소가 특정 조건을 충족하는 하위 시퀀스를 생성하는 것입니다. 🎜 🎜정사각형 목록을 만들고 싶다면: 🎜 🎜rreee🎜 🎜위의 내용은 루프가 끝난 후에도 여전히 존재하는 x라는 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 forif 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forif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, 54321hello!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

whileif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innot in检查指定值在序列中是否存在(不存在)。操作符isis 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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