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Le didacticiel Python#Structures de données
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[Traduction]Le Tutoriel Python#Les Structures de Données
5.1 Structures de données
Ce chapitre détaille certains des contenus introduits précédemment et présentera également du nouveau contenu.
5.1 Plus sur les listes
Le type de données liste a plus de méthodes, voici toutes les méthodes de l'objet liste :
list.append(x)
Ajoute un nouvel élément à la fin de la liste, équivalent àa[len(a):] = [x]list.extend(iterable)
Étendez la liste en ajoutant tous les éléments de l'objet itérable, équivalent àa[len(a):] = iterablelist.insert(i, x)
Insère un élément à la position spécifiée. Le premier paramètre est l'index de l'élément. Le nouvel élément sera inséré avant cet index, donca.insert(0, x)sera inséré au début de la liste, eta.insert(len(a), x)est équivalent àa.append(x).list.remove(x)
Supprime le premier élément avec la valeurxde la liste Sixn'existe pas, la méthode lève une exception (ValueErrorException) .
list.pop([i])
Supprime l'élément à la position spécifiée de la liste et renvoie. Si aucun index n'est spécifié,a.pop()supprime et renvoie le dernier élément de la liste. (Les crochets entourantidans la signature de la méthode indiquent que le paramètre est facultatif, plutôt que d'écrire un crochet à cette position. Cette notation est souvent utilisée dans la référence de la bibliothèque Python)list.clear()
Supprimez tous les éléments de la liste, équivalent àdel a[:]list.index(x[, start[, end]])
Renvoie l'index de base 0 du premier élément avec la valeurx, ou lève une exceptionxsiValueErrorn'existe pas.
Les arguments facultatifs start et end sont interprétés comme une notation slice et sont utilisés pour limiter la recherche à une sous-liste spécifique de la liste. L'index renvoyé est relatif à l'index de la liste complète, et non à l'argument start.list.count(x)
Renvoie le nombre de fois où x apparaît dans la listelist.sort(key=None, reverse=False)
Trier tous les éléments de la liste (les paramètres sont utilisés pour personnaliser le tri, voirsorted()pour plus d'informations)list.reverse()
Éléments de liste inverséslist.copy()
Renvoie une copie superficielle de la liste, équivalente àa[:]
Ce qui suit est un exemple illustrant la méthode list :
<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>
Comme insert, reverse ou sort modifiez uniquement la liste mais n'imprimez pas la valeur de retour. Ils renvoient la valeur par défaut None[1]. Il s'agit d'un principe de conception qui s'applique aux structures de données mutables de Python.
5.1.1 Utiliser des listes comme piles
Les méthodes de liste rendent très facile son utilisation comme pile, où le dernier élément ajouté à la pile est le premier à être libéré (dernier entré, premier sorti). Utilisez la méthode append() pour ajouter des éléments en haut de la pile et utilisez pop() sans paramètres pour extraire l'élément supérieur de la pile. Exemple :
<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 Utiliser des listes comme files d'attente
Il est également possible d'utiliser une liste comme file d'attente. Les éléments ajoutés en premier dans la file d'attente sont libérés en premier (premier entré, premier sorti) cependant, utiliser une liste de cette manière est très inefficace. Parce que l'ajout et la suppression d'éléments à la fin de la liste sont rapides, mais l'insertion ou la suppression d'éléments au début de la liste est lente (car tous les autres éléments doivent être décalés d'un point).
Le collections.deque spécialement conçu ajoute et supprime rapidement des éléments aux deux extrémités, et vous pouvez l'utiliser pour implémenter des files d'attente. Exemple :
<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 Compréhensions des listes
Les compréhensions de listes fournissent un moyen concis de créer des listes. Les méthodes d'application générales sont : la création d'une nouvelle liste, les éléments de la liste sont les résultats d'opérations sur d'autres séquences ou objets itérables ou la création d'une sous-séquence dont les éléments répondent à des conditions spécifiques ;
Supposons que vous souhaitiez créer une liste carrée :
<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>
Notez que ce qui précède crée (ou réécrit) une variable nommée x, qui existe toujours après la fin de la boucle. Utilisez la méthode suivante pour créer une liste au carré sans aucun effet secondaire :
<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>
Ou, etc. utilisé pour :
<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>
Cette méthode est plus concise et plus facile à lire.
suivi d'une clause for, suivi de zéro ou plusieurs clauses for ou expressions dans des clauses if plus des crochets, forment une compréhension de liste. Le résultat renvoyé est une nouvelle liste dont les éléments sont les résultats de calcul des clauses for et if dans l'expression. Par exemple, la compréhension de liste suivante combine des éléments inégaux dans deux listes :
<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>
équivaut à :
<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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