文章目录
在了解Python的数据结构时,容器(container)、可迭代对象(iterable)、迭代器(iterator)、生成器(generator)、列表/集合/字典推导式(list,set,dict comprehension)众多概念参杂在一起,难免让初学者一头雾水,我将用一篇文章试图将这些概念以及它们之间的关系捋清楚。

容器(container)
容器是一种把多个元素组织在一起的数据结构,容器中的元素可以逐个地迭代获取,可以用in
, not in
关键字判断元素是否包含在容器中。通常这类数据结构把所有的元素存储在内存中(也有一些特例,并不是所有的元素都放在内存,比如迭代器和生成器对象)在Python中,常见的容器对象有:
- list, deque, ....
- set, frozensets, ....
- dict, defaultdict, OrderedDict, Counter, ....
- tuple, namedtuple, …
- str
容器比较容易理解,因为你就可以把它看作是一个盒子、一栋房子、一个柜子,里面可以塞任何东西。从技术角度来说,当它可以用来询问某个元素是否包含在其中时,那么这个对象就可以认为是一个容器,比如 list,set,tuples都是容器对象:
1 2 3 4 5 6 |
<span class="o">>>></span> <span class="k">assert</span> <span class="mi">1</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="c1"># lists</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">4</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">1</span> <span class="ow">in</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">}</span> <span class="c1"># sets</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">4</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">{</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">}</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">1</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span> <span class="c1"># tuples</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">4</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span> |
询问某元素是否在dict中用dict的中key:
1 2 3 |
<span class="o">>>></span> <span class="n">d</span> <span class="o">=</span> <span class="p">{</span><span class="mi">1</span><span class="p">:</span> <span class="s1">'foo'</span><span class="p">,</span> <span class="mi">2</span><span class="p">:</span> <span class="s1">'bar'</span><span class="p">,</span> <span class="mi">3</span><span class="p">:</span> <span class="s1">'qux'</span><span class="p">}</span> <span class="o">>>></span> <span class="k">assert</span> <span class="mi">1</span> <span class="ow">in</span> <span class="n">d</span> <span class="o">>>></span> <span class="k">assert</span> <span class="s1">'foo'</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">d</span> <span class="c1"># 'foo' 不是dict中的元素</span> |
询问某substring是否在string中:
1 2 3 4 |
<span class="o">>>></span> <span class="n">s</span> <span class="o">=</span> <span class="s1">'foobar'</span> <span class="o">>>></span> <span class="k">assert</span> <span class="s1">'b'</span> <span class="ow">in</span> <span class="n">s</span> <span class="o">>>></span> <span class="k">assert</span> <span class="s1">'x'</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">s</span> <span class="o">>>></span> <span class="k">assert</span> <span class="s1">'foo'</span> <span class="ow">in</span> <span class="n">s</span> |
尽管绝大多数容器都提供了某种方式来获取其中的每一个元素,但这并不是容器本身提供的能力,而是可迭代对象赋予了容器这种能力,当然并不是所有的容器都是可迭代的,比如:Bloom filter,虽然Bloom filter可以用来检测某个元素是否包含在容器中,但是并不能从容器中获取其中的每一个值,因为Bloom filter压根就没把元素存储在容器中,而是通过一个散列函数映射成一个值保存在数组中。
可迭代对象(iterable)
刚才说过,很多容器都是可迭代对象,此外还有更多的对象同样也是可迭代对象,比如处于打开状态的files,sockets等等。但凡是可以返回一个迭代器的对象都可称之为可迭代对象,听起来可能有点困惑,没关系,先看一个例子:
1 2 3 4 5 6 7 8 9 10 11 12 13 |
<span class="o">>>></span> <span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">>>></span> <span class="n">y</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">>>></span> <span class="n">z</span> <span class="o">=</span> <span class="nb">iter</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">y</span><span class="p">)</span> <span class="mi">1</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">y</span><span class="p">)</span> <span class="mi">2</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">z</span><span class="p">)</span> <span class="mi">1</span> <span class="o">>>></span> <span class="nb">type</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o"><</span><span class="k">class</span> <span class="err">'</span><span class="nc">list</span><span class="s1">'></span> <span class="o">>>></span> <span class="nb">type</span><span class="p">(</span><span class="n">y</span><span class="p">)</span> <span class="o"><</span><span class="k">class</span> <span class="err">'</span><span class="nc">list_iterator</span><span class="s1">'></span> |
这里x
是一个可迭代对象,可迭代对象和容器一样是一种通俗的叫法,并不是指某种具体的数据类型,list是可迭代对象,dict是可迭代对象,set也是可迭代对象。y
和z
是两个独立的迭代器,迭代器内部持有一个状态,该状态用于记录当前迭代所在的位置,以方便下次迭代的时候获取正确的元素。迭代器有一种具体的迭代器类型,比如list_iterator
,set_iterator
。可迭代对象实现了__iter__
方法,该方法返回一个迭代器对象。
当运行代码:
1 2 3 |
<span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="k">for</span> <span class="n">elem</span> <span class="ow">in</span> <span class="n">x</span><span class="p">:</span> <span class="o">...</span> |
实际执行情况是:
反编译该段代码,你可以看到解释器显示地调用GET_ITER
指令,相当于调用iter(x)
,FOR_ITER
指令就是调用next()
方法,不断地获取迭代器中的下一个元素,但是你没法直接从指令中看出来,因为他被解释器优化过了。
1 2 3 4 5 6 7 8 9 10 11 12 |
<span class="o">>>></span> <span class="kn">import</span> <span class="nn">dis</span> <span class="o">>>></span> <span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">>>></span> <span class="n">dis</span><span class="o">.</span><span class="n">dis</span><span class="p">(</span><span class="s1">'for _ in x: pass'</span><span class="p">)</span> <span class="mi">1</span> <span class="mi">0</span> <span class="n">SETUP_LOOP</span> <span class="mi">14</span> <span class="p">(</span><span class="n">to</span> <span class="mi">17</span><span class="p">)</span> <span class="mi">3</span> <span class="n">LOAD_NAME</span> <span class="mi">0</span> <span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="mi">6</span> <span class="n">GET_ITER</span> <span class="o">>></span> <span class="mi">7</span> <span class="n">FOR_ITER</span> <span class="mi">6</span> <span class="p">(</span><span class="n">to</span> <span class="mi">16</span><span class="p">)</span> <span class="mi">10</span> <span class="n">STORE_NAME</span> <span class="mi">1</span> <span class="p">(</span><span class="n">_</span><span class="p">)</span> <span class="mi">13</span> <span class="n">JUMP_ABSOLUTE</span> <span class="mi">7</span> <span class="o">>></span> <span class="mi">16</span> <span class="n">POP_BLOCK</span> <span class="o">>></span> <span class="mi">17</span> <span class="n">LOAD_CONST</span> <span class="mi">0</span> <span class="p">(</span><span class="bp">None</span><span class="p">)</span> <span class="mi">20</span> <span class="n">RETURN_VALUE</span> |
迭代器(iterator)
那么什么迭代器呢?它是一个带状态的对象,他能在你调用next()
方法的时候返回容器中的下一个值,任何实现了__iter__
和__next__()
(python2中实现next()
)方法的对象都是迭代器,__iter__
返回迭代器自身,__next__
返回容器中的下一个值,如果容器中没有更多元素了,则抛出StopIteration异常,至于它们到底是如何实现的这并不重要。
所以,迭代器就是实现了工厂模式的对象,它在你每次你询问要下一个值的时候给你返回。有很多关于迭代器的例子,比如itertools
函数返回的都是迭代器对象。
生成无限序列:
1 2 3 4 5 6 |
<span class="o">>>></span> <span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">count</span> <span class="o">>>></span> <span class="n">counter</span> <span class="o">=</span> <span class="n">count</span><span class="p">(</span><span class="n">start</span><span class="o">=</span><span class="mi">13</span><span class="p">)</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">counter</span><span class="p">)</span> <span class="mi">13</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">counter</span><span class="p">)</span> <span class="mi">14</span> |
从一个有限序列中生成无限序列:
1 2 3 4 5 6 7 8 9 10 |
<span class="o">>>></span> <span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">cycle</span> <span class="o">>>></span> <span class="n">colors</span> <span class="o">=</span> <span class="n">cycle</span><span class="p">([</span><span class="s1">'red'</span><span class="p">,</span> <span class="s1">'white'</span><span class="p">,</span> <span class="s1">'blue'</span><span class="p">])</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span> <span class="s1">'red'</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span> <span class="s1">'white'</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span> <span class="s1">'blue'</span> <span class="o">>>></span> <span class="nb">next</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span> <span class="s1">'red'</span> |
从无限的序列中生成有限序列:
1 2 3 4 5 6 7 8 9 |
<span class="o">>>></span> <span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">islice</span> <span class="o">>>></span> <span class="n">colors</span> <span class="o">=</span> <span class="n">cycle</span><span class="p">([</span><span class="s1">'red'</span><span class="p">,</span> <span class="s1">'white'</span><span class="p">,</span> <span class="s1">'blue'</span><span class="p">])</span> <span class="c1"># infinite</span> <span class="o">>>></span> <span class="n">limited</span> <span class="o">=</span> <span class="n">islice</span><span class="p">(</span><span class="n">colors</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">4</span><span class="p">)</span> <span class="c1"># finite</span> <span class="o">>>></span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">limited</span><span class="p">:</span> <span class="o">...</span> <span class="k">print</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="n">red</span> <span class="n">white</span> <span class="n">blue</span> <span class="n">red</span> |
为了更直观地感受迭代器内部的执行过程,我们自定义一个迭代器,以斐波那契数列为例:
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 |
<span class="k">class</span> <span class="nc">Fib</span><span class="p">:</span> <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev</span> <span class="o">=</span> <span class="mi">0</span> <span class="bp">self</span><span class="o">.</span><span class="n">curr</span> <span class="o">=</span> <span class="mi">1</span> <span class="k">def</span> <span class="nf">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> <span class="k">return</span> <span class="bp">self</span> <span class="k">def</span> <span class="nf">__next__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span> <span class="n">value</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">curr</span> <span class="bp">self</span><span class="o">.</span><span class="n">curr</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev</span> <span class="bp">self</span><span class="o">.</span><span class="n">prev</span> <span class="o">=</span> <span class="n">value</span> <span class="k">return</span> <span class="n">value</span> <span class="o">>>></span> <span class="n">f</span> <span class="o">=</span> <span class="n">Fib</span><span class="p">()</span> <span class="o">>>></span> <span class="nb">list</span><span class="p">(</span><span class="n">islice</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">34</span><span class="p">,</span> <span class="mi">55</span><span class="p">]</span> |
Fib既是一个可迭代对象(因为它实现了__iter__
方法),又是一个迭代器(因为实现了__next__
方法)。实例变量prev
和curr
用户维护迭代器内部的状态。每次调用next()
方法的时候做两件事:
- 为下一次调用
next()
方法修改状态 - 为当前这次调用生成返回结果
迭代器就像一个懒加载的工厂,等到有人需要的时候才给它生成值返回,没调用的时候就处于休眠状态等待下一次调用。
生成器(generator)
生成器算得上是Python语言中最吸引人的特性之一,生成器其实是一种特殊的迭代器,不过这种迭代器更加优雅。它不需要再像上面的类一样写__iter__()
和__next__()
方法了,只需要一个yiled
关键字。 生成器一定是迭代器(反之不成立),因此任何生成器也是以一种懒加载的模式生成值。用生成器来实现斐波那契数列的例子是:
1 2 3 4 5 6 7 8 9 |
<span class="k">def</span> <span class="nf">fib</span><span class="p">():</span> <span class="n">prev</span><span class="p">,</span> <span class="n">curr</span> <span class="o">=</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span> <span class="k">while</span> <span class="bp">True</span><span class="p">:</span> <span class="k">yield</span> <span class="n">curr</span> <span class="n">prev</span><span class="p">,</span> <span class="n">curr</span> <span class="o">=</span> <span class="n">curr</span><span class="p">,</span> <span class="n">curr</span> <span class="o">+</span> <span class="n">prev</span> <span class="o">>>></span> <span class="n">f</span> <span class="o">=</span> <span class="n">fib</span><span class="p">()</span> <span class="o">>>></span> <span class="nb">list</span><span class="p">(</span><span class="n">islice</span><span class="p">(</span><span class="n">f</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">10</span><span class="p">))</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">8</span><span class="p">,</span> <span class="mi">13</span><span class="p">,</span> <span class="mi">21</span><span class="p">,</span> <span class="mi">34</span><span class="p">,</span> <span class="mi">55</span><span class="p">]</span> |
fib
就是一个普通的python函数,它特殊的地方在于函数体中没有return
关键字,函数的返回值是一个生成器对象。当执行f=fib()
返回的是一个生成器对象,此时函数体中的代码并不会执行,只有显示或隐示地调用next的时候才会真正执行里面的代码。
生成器在Python中是一个非常强大的编程结构,可以用更少地中间变量写流式代码,此外,相比其它容器对象它更能节省内存和CPU,当然它可以用更少的代码来实现相似的功能。现在就可以动手重构你的代码了,但凡看到类似:
1 2 3 4 5 |
<span class="k">def</span> <span class="nf">something</span><span class="p">():</span> <span class="n">result</span> <span class="o">=</span> <span class="p">[]</span> <span class="k">for</span> <span class="o">...</span> <span class="ow">in</span> <span class="o">...</span><span class="p">:</span> <span class="n">result</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">return</span> <span class="n">result</span> |
都可以用生成器函数来替换:
1 2 3 |
<span class="k">def</span> <span class="nf">iter_something</span><span class="p">():</span> <span class="k">for</span> <span class="o">...</span> <span class="ow">in</span> <span class="o">...</span><span class="p">:</span> <span class="k">yield</span> <span class="n">x</span> |
生成器表达式(generator expression)
生成器表达式是列表推倒式的生成器版本,看起来像列表推导式,但是它返回的是一个生成器对象而不是列表对象。
1 2 3 4 5 |
<span class="o">>>></span> <span class="n">a</span> <span class="o">=</span> <span class="p">(</span><span class="n">x</span><span class="o">*</span><span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">10</span><span class="p">))</span> <span class="o">>>></span> <span class="n">a</span> <span class="o"><</span><span class="n">generator</span> <span class="nb">object</span> <span class="o"><</span><span class="n">genexpr</span><span class="o">></span> <span class="n">at</span> <span class="mh">0x401f08</span><span class="o">></span> <span class="o">>>></span> <span class="nb">sum</span><span class="p">(</span><span class="n">a</span><span class="p">)</span> <span class="mi">285</span> |
总结
- 容器是一系列元素的集合,str、list、set、dict、file、sockets对象都可以看作是容器,容器都可以被迭代(用在for,while等语句中),因此他们被称为可迭代对象。
- 可迭代对象实现了
__iter__
方法,该方法返回一个迭代器对象。 - 迭代器持有一个内部状态的字段,用于记录下次迭代返回值,它实现了
__next__
和__iter__
方法,迭代器不会一次性把所有元素加载到内存,而是需要的时候才生成返回结果。 - 生成器是一种特殊的迭代器,它的返回值不是通过
return
而是用yield
。
英文原文:http://nvie.com/posts/iterators-vs-generators/
