blocks|key|1840329|text|Sequence和Iterable抽象基类(也可以用作类型注释)遵循序列和可迭代的定义。具体而言：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|1840330|Iterable是定义__iter__、或+__getitem__的任何对象。|unordered-list-item|BOLD|1840331|Sequence是定义__getitem__和__len__的任何对象。根据定义，任何序列都是可迭代的。Sequence类还定义了其他方法，如调用两个必需方法的__contains__、__reversed__。|1840332|下面是一些例子：|1840333|list、tuple、str是最常见的序列。|1840334|一些内置的迭代器不是序列。例如，reversed返回不能订阅的reversed对象(或列表的list_reverseiterator+)。|1840335|entityMap|0|LINK|mutability|MUTABLE|url|https://docs.python.org/3/glossary.html#term-sequence|1|https://docs.python.org/3/glossary.html#term-iterable^0|0|8|9|8|Y|2|0|11|3|1|0|0|8|K|1|B|8|M|B|0|0|8|B|B|N|7|1G|8|28|C|2L|C|0|0|0|4|5|5|B|3|0|G|8|V|8|1A|K|0^^$0|@$1|2|3|4|5|6|7|11|8|@$9|12|A|13|B|C]|$9|14|A|15|B|C]]|D|@$9|16|A|17|1|18]|$9|19|A|1A|1|1B]]|E|$]]|$1|F|3|G|5|H|7|1C|8|@$9|1D|A|1E|B|I]|$9|1F|A|1G|B|I]|$9|1H|A|1I|B|C]|$9|1J|A|1K|B|C]]|D|@]|E|$]]|$1|J|3|K|5|H|7|1L|8|@$9|1M|A|1N|B|I]|$9|1O|A|1P|B|C]|$9|1Q|A|1R|B|C]|$9|1S|A|1T|B|C]|$9|1U|A|1V|B|C]|$9|1W|A|1X|B|C]]|D|@]|E|$]]|$1|L|3|M|5|6|7|1Y|8|@]|D|@]|E|$]]|$1|N|3|O|5|H|7|1Z|8|@$9|20|A|21|B|C]|$9|22|A|23|B|C]|$9|24|A|25|B|C]]|D|@]|E|$]]|$1|P|3|Q|5|H|7|26|8|@$9|27|A|28|B|C]|$9|29|A|2A|B|C]|$9|2B|A|2C|B|C]]|D|@]|E|$]]|$1|R|3|-4|5|6|7|2D|8|@]|D|@]|E|$]]]|S|$T|$5|U|V|W|E|$X|Y]]|Z|$5|U|V|W|E|$X|10]]]]

The <code>Sequence</code> and <code>Iterable</code> abstract base classes (can also be used as type annotations) follow Python's definition of <a href="https://docs.python.org/3/glossary.html#term-sequence" rel="noreferrer">sequence</a> and <a href="https://docs.python.org/3/glossary.html#term-iterable" rel="noreferrer">iterable</a>. To be specific:
<ul>
<li>Iterable is any object that defines <code>__iter__</code> or <code>__getitem__</code>.</li>
<li>Sequence is any object that defines <code>__getitem__</code> and <code>__len__</code>. By definition, any sequence is an iterable. The <code>Sequence</code> class also defines other methods such as <code>__contains__</code>, <code>__reversed__</code> that calls the two required methods.</li>
</ul>
Some examples:
<ul>
<li><code>list</code>, <code>tuple</code>, <code>str</code> are the most common sequences.</li>
<li>Some built-in iterables are not sequences. For example, <code>reversed</code> returns a <code>reversed</code> object (or <code>list_reverseiterator</code> for lists) that cannot be subscripted.</li>
</ul>

blocks|key|986029|text|在编写带有items参数的函数/方法时，我通常更喜欢Iterable而不是Sequence。这就是为什么，我希望这将有助于理解不同之处。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|986030|假设my_func_1是：|986031|from+typing+import+Iterable
def+my_func_1(items:+Iterable[int])+->+None:
++++for+item+in+items:
++++++++...
++++++++if+condition:
++++++++++++break
++++return|code-block|syntax|javascript|986032|Iterable为调用者提供了最大的可能性。正确的呼叫包括：|986033|my_func_1((1,+2,+3))+#+tuple+is+Sequence,+Collection,+Iterator
my_func_1([1,+2,+3])+#+list+is+MutableSequence,+Sequence,+Collection,+Iterator
my_func_1({1,+2,+3})+#+set+is+Collection,+Iterator
my_func_1(my_dict)+#+dict+is+Mapping,+Collection,+Iterator
my_func_1(my_dict.keys())+#+dict.keys()+is+MappingKeys,+Set,+Collection,+Iterator
my_func_1(range(10))+#+range+is+Sequence,+Collection,+Iterator
my_func_1(x**2+for+x+in+range(100))+#+"strict'+Iterator,+i.e.+neither+a+Collection+nor+a+Sequence
...+|986034|..。因为一切都是Iterable。|986035|给函数调用者的隐式消息是:按原样传输数据，只是不对其进行转换。|986036|如果调用者没有数据作为Sequence+(例如tuple、list)或非Sequence+Collection+(例如set)，并且由于迭代在StopIteration之前中断，如果他提供了一个“严格的”Iterator，那么它也会更好地执行。|986037|但是，如果函数算法(例如my_func_2)需要多个迭代，那么如果调用方提供了“严格”的Iterator，那么Iterable就会失败，因为第一次迭代会耗尽它。因此，请使用Collection|986038|from+typing+import+Collection
def+my_func_2(items:+Collection[int])+->+None:
++++for+item+in+items:
++++++++...
++++for+item+in+items:
++++++++...
++++return|986039|如果函数算法(my_func_3)必须通过索引访问特定项)，那么如果调用方提供集合、Mapping或“严格”的Iterator，则Iterable和Collection都将失败。因此，请使用Sequence|986040|from+typing+import+Sequence
def+my_func_3(items:+Sequence[int])+->+None:
++++return+items[5]|986041|结论:策略是：“使用功能所能处理的最通用类型”。不要忘记，所有这些仅仅是关于输入，以帮助静态类型检查器报告不正确的调用(例如，在需要set时使用Sequence+)。然后，调用方有责任在必要时转换数据，例如：|986042|my_func_3(tuple(x**2+for+x+in+range(100)))|986043|实际上，所有这些实际上都是关于在缩放项的长度时的性能。如果可能的话，总是更喜欢Iterator。工作表现应作为日常任务处理，而不是作为消防队员工作队处理。|986044|在这个方向上，您可能会遇到这样的情况:函数只处理空用例并委托其他用例，并且不希望将项转换为Collection或Sequence。然后做这样的事情：|986045|from+more_itertools+import+spy
def+my_func_4(items:+Iterable[int])+->+None:
++++(first,+items)+=+spy(items)
++++if+not+first:+#+i.e.+items+is+empty
++++++++...
++++else:
++++++++my_func_1(items)+#+Here+'items'+is+always+a+'strict'+Iterator
++++return|986046|entityMap^0|5|5|Q|8|11|8|0|2|9|0|0|0|8|0|0|9|8|0|0|B|8|N|5|T|4|10|8|19|A|1N|3|1Z|D|2U|8|0|C|9|18|8|1J|8|2E|A|0|0|7|A|16|7|1J|8|1T|8|22|A|2N|8|0|0|1U|3|20|8|0|0|13|8|0|19|A|1K|8|0|0^^$0|@$1|2|3|4|5|6|7|1G|8|@$9|1H|A|1I|B|C]|$9|1J|A|1K|B|C]|$9|1L|A|1M|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1N|8|@$9|1O|A|1P|B|C]]|D|@]|E|$]]|$1|H|3|I|5|J|7|1Q|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1R|8|@$9|1S|A|1T|B|C]]|D|@]|E|$]]|$1|O|3|P|5|J|7|1U|8|@]|D|@]|E|$K|L]]|$1|Q|3|R|5|6|7|1V|8|@$9|1W|A|1X|B|C]]|D|@]|E|$]]|$1|S|3|T|5|6|7|1Y|8|@]|D|@]|E|$]]|$1|U|3|V|5|6|7|1Z|8|@$9|20|A|21|B|C]|$9|22|A|23|B|C]|$9|24|A|25|B|C]|$9|26|A|27|B|C]|$9|28|A|29|B|C]|$9|2A|A|2B|B|C]|$9|2C|A|2D|B|C]|$9|2E|A|2F|B|C]]|D|@]|E|$]]|$1|W|3|X|5|6|7|2G|8|@$9|2H|A|2I|B|C]|$9|2J|A|2K|B|C]|$9|2L|A|2M|B|C]|$9|2N|A|2O|B|C]]|D|@]|E|$]]|$1|Y|3|Z|5|J|7|2P|8|@]|D|@]|E|$K|L]]|$1|10|3|11|5|6|7|2Q|8|@$9|2R|A|2S|B|C]|$9|2T|A|2U|B|C]|$9|2V|A|2W|B|C]|$9|2X|A|2Y|B|C]|$9|2Z|A|30|B|C]|$9|31|A|32|B|C]]|D|@]|E|$]]|$1|12|3|13|5|J|7|33|8|@]|D|@]|E|$K|L]]|$1|14|3|15|5|6|7|34|8|@$9|35|A|36|B|C]|$9|37|A|38|B|C]]|D|@]|E|$]]|$1|16|3|17|5|J|7|39|8|@]|D|@]|E|$K|L]]|$1|18|3|19|5|6|7|3A|8|@$9|3B|A|3C|B|C]]|D|@]|E|$]]|$1|1A|3|1B|5|6|7|3D|8|@$9|3E|A|3F|B|C]|$9|3G|A|3H|B|C]]|D|@]|E|$]]|$1|1C|3|1D|5|J|7|3I|8|@]|D|@]|E|$K|L]]|$1|1E|3|-4|5|6|7|3J|8|@]|D|@]|E|$]]]|1F|$]]

When writing a function/method with an <code>items</code> argument, I often prefer <code>Iterable</code> to <code>Sequence</code>.
Hereafter is why and I hope it will help understanding the difference.
Say <code>my_func_1</code> is:
<pre class="lang-py prettyprint-override"><code>from typing import Iterable
def my_func_1(items: Iterable[int]) -&gt; None:
 for item in items:
 ...
 if condition:
 break
 return
</code></pre>
<code>Iterable</code> offers the maximum possibilities to the caller. Correct calls include:
<pre class="lang-py prettyprint-override"><code>my_func_1((1, 2, 3)) # tuple is Sequence, Collection, Iterator
my_func_1([1, 2, 3]) # list is MutableSequence, Sequence, Collection, Iterator
my_func_1({1, 2, 3}) # set is Collection, Iterator
my_func_1(my_dict) # dict is Mapping, Collection, Iterator
my_func_1(my_dict.keys()) # dict.keys() is MappingKeys, Set, Collection, Iterator
my_func_1(range(10)) # range is Sequence, Collection, Iterator
my_func_1(x**2 for x in range(100)) # &quot;strict' Iterator, i.e. neither a Collection nor a Sequence
... 
</code></pre>
... because all are<code>Iterable</code>.
The implicit message to a function caller is: transfer data &quot;as-is&quot;, just don't transform it.
In case the caller doesn't have data as a <code>Sequence</code> (e.g. <code>tuple</code>, <code>list</code>) or as a non-<code>Sequence</code> <code>Collection</code> (e.g. <code>set</code>), and because the iteration breaks before <code>StopIteration</code>, it is also more performing if he provides an 'strict' <code>Iterator</code>.
However if the function algorithm (say <code>my_func_2</code>) requires more than one iteration, then <code>Iterable</code> will fail if the caller provides a 'strict' <code>Iterator</code> because the first iteration exhausts it. Hence use a <code>Collection</code>:
<pre class="lang-py prettyprint-override"><code>from typing import Collection
def my_func_2(items: Collection[int]) -&gt; None:
 for item in items:
 ...
 for item in items:
 ...
 return
</code></pre>
If the function algorithm (<code>my_func_3)</code> has to access by index to specific items, then both <code>Iterable</code> and <code>Collection</code> will fail if the caller provides a set, a <code>Mapping</code> or a 'strict' <code>Iterator</code>.
Hence use a <code>Sequence</code>:
<pre class="lang-py prettyprint-override"><code>from typing import Sequence
def my_func_3(items: Sequence[int]) -&gt; None:
 return items[5]
</code></pre>
Conclusion: The strategy is: &quot;use the most generic type that the function can handle&quot;. Don't forget that all this is only about typing, to help a static type checker to report incorrect calls (e.g. using a <code>set</code> when a <code>Sequence</code> is required). Then it's the caller responsibility to transform data when necessary, such as:
<pre class="lang-py prettyprint-override"><code>my_func_3(tuple(x**2 for x in range(100)))
</code></pre>
Actually, all this is really about performance when scaling the length of items.
Always prefer <code>Iterator</code> when possible. Performance shall be handle as a daily task, not as a firemen task force.
In that direction, you will probably face the situation when a function only handles the empty use case and delegates the others, and you don't want to transform items into a <code>Collection</code> or a <code>Sequence</code>. Then do something like this:
<pre class="lang-py prettyprint-override"><code>from more_itertools import spy
def my_func_4(items: Iterable[int]) -&gt; None:
 (first, items) = spy(items)
 if not first: # i.e. items is empty
 ...
 else:
 my_func_1(items) # Here 'items' is always a 'strict' Iterator
 return
</code></pre>

I don't understand the difference when hinting <code>Iterable</code> and <code>Sequence</code>.
What is the main difference between those two and when to use which?
I think <code>set</code> is an <code>Iterable</code> but not <code>Sequence</code>, are there any built-in data type that is <code>Sequence</code> but not <code>Iterable</code>?
<pre><code>def foo(baz: Sequence[float]):
 ...

# What is the difference?
def bar(baz: Iterable[float]):
 ...
</code></pre>

Python Iterable vs Sequence

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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当我暗示Iterable和Sequence时，我不明白两者的区别。这两者之间的主要区别是什么?什么时候使用哪一种？我认为set是一个Iterable而不是Sequence，有什么内置的数据类型是Sequence而不是Iterable吗？def foo(baz: Sequence[float]):  ...# What ...

问Python Iterable vs序列
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