blocks|key|2761952|text|您甚至不需要返回布尔值。文档的要点是，您可以完全自由地控制重载方法可以返回的内容；Python并不强制要求__eq__和__ne__返回一致的布尔值。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|2761953|SQLAlchemy+project完全重载了丰富的比较运算符以返回完全不同的内容。如果您使用：|2761954|model1.column+==+model2.column|code-block|syntax|javascript|2761955|或|2761956|model1.column+!=+model2.column|2761957|2761958|model1.column+<+model2.column|2761959|其中model1和model2都是SQL表模型，那么您得到的不是布尔值，而是SQLAlchemy查询过滤器。|2761960|您可以使用返回值构造SQL查询：|2761961|model1.filter(model1.column+<=+model2.column)|2761962|将导致SQL查询，如下所示：|2761963|select+model1.*
from+model1
left+join+model2+on+model1.foreign_key+==+model2.primary_key
where
++++model1.column+<=+model2.column|2761964|完全在Python代码中，使用Python丰富的比较语法。|2761965|entityMap|0|LINK|mutability|MUTABLE|url|http://www.sqlalchemy.org/^0|1H|6|1O|6|0|0|I|0|0|0|0|0|0|0|2|6|9|6|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|1D|8|@$9|1E|A|1F|B|C]|$9|1G|A|1H|B|C]]|D|@]|E|$]]|$1|F|3|G|5|6|7|1I|8|@]|D|@$9|1J|A|1K|1|1L]]|E|$]]|$1|H|3|I|5|J|7|1M|8|@]|D|@]|E|$K|L]]|$1|M|3|N|5|6|7|1N|8|@]|D|@]|E|$]]|$1|O|3|P|5|J|7|1O|8|@]|D|@]|E|$K|L]]|$1|Q|3|N|5|6|7|1P|8|@]|D|@]|E|$]]|$1|R|3|S|5|J|7|1Q|8|@]|D|@]|E|$K|L]]|$1|T|3|U|5|6|7|1R|8|@$9|1S|A|1T|B|C]|$9|1U|A|1V|B|C]]|D|@]|E|$]]|$1|V|3|W|5|6|7|1W|8|@]|D|@]|E|$]]|$1|X|3|Y|5|J|7|1X|8|@]|D|@]|E|$K|L]]|$1|Z|3|10|5|6|7|1Y|8|@]|D|@]|E|$]]|$1|11|3|12|5|J|7|1Z|8|@]|D|@]|E|$K|L]]|$1|13|3|14|5|6|7|20|8|@]|D|@]|E|$]]|$1|15|3|-4|5|6|7|21|8|@]|D|@]|E|$]]]|16|$17|$5|18|19|1A|E|$1B|1C]]]]

You don't even need to return boolean values. The point the documentation is making is that you are given total freedom over what the overloaded methods can return; Python does not enforce that <code>__eq__</code> and <code>__ne__</code> return consistent boolean values.

The <a href="http://www.sqlalchemy.org/">SQLAlchemy project</a> has overloaded the rich comparison operators altogether to return something else entirely. If you use:

<pre><code>model1.column == model2.column
</code></pre>

or

<pre><code>model1.column != model2.column
</code></pre>

or 

<pre><code>model1.column &lt; model2.column
</code></pre>

where <code>model1</code> and <code>model2</code> are both SQLAlchemy table models then you don't get a boolean value, what you get is a SQL query filter instead.

You use the return values to construct SQL queries:

<pre><code>model1.filter(model1.column &lt;= model2.column)
</code></pre>

would result in a SQL query along the lines of:

<pre><code>select model1.*
from model1
left join model2 on model1.foreign_key == model2.primary_key
where
 model1.column &lt;= model2.column
</code></pre>

entirely in Python code, using Python rich comparison syntax.

blocks|key|164079|text|NumPy使用丰富的比较来向量化==、!=、<等，就像它对大多数其他运算符所做的那样。例如,|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|164080|>>>+x+=+numpy.array([1,+2,+3,+4,+5])
>>>+y+=+numpy.array([2,+2,+1,+4,+4])
>>>+x+==+y
array([False,++True,+False,++True,+False],+dtype=bool)|code-block|syntax|javascript|164081|当将数组x和y与任何比较运算符进行比较时，NumPy将按元素应用运算符，并返回一个结果数组。例如，在将操作应用于符合条件的x单元格时，这很有用：|164082|>>>+x[x==y]+=+6
>>>+x
array([1,+6,+3,+6,+5])|164083|在这里，我选择了与y的相应元素相等的x的所有元素，并将它们设置为6。|164084|entityMap|0|LINK|mutability|MUTABLE|url|http://www.numpy.org/^0|G|2|J|2|M|1|0|5|0|0|0|4|1|6|1|1P|1|0|0|9|1|I|1|0^^$0|@$1|2|3|4|5|6|7|Y|8|@$9|Z|A|10|B|C]|$9|11|A|12|B|C]|$9|13|A|14|B|C]]|D|@$9|15|A|16|1|17]]|E|$]]|$1|F|3|G|5|H|7|18|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|19|8|@$9|1A|A|1B|B|C]|$9|1C|A|1D|B|C]|$9|1E|A|1F|B|C]]|D|@]|E|$]]|$1|M|3|N|5|H|7|1G|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|6|7|1H|8|@$9|1I|A|1J|B|C]|$9|1K|A|1L|B|C]]|D|@]|E|$]]|$1|Q|3|-4|5|6|7|1M|8|@]|D|@]|E|$]]]|R|$S|$5|T|U|V|E|$W|X]]]]

<a href="http://www.numpy.org/" rel="noreferrer">NumPy</a> uses rich comparisons to vectorize <code>==</code>, <code>!=</code>, <code>&lt;</code>, etc, just like it does with most other operators. For example,

<pre><code>&gt;&gt;&gt; x = numpy.array([1, 2, 3, 4, 5])
&gt;&gt;&gt; y = numpy.array([2, 2, 1, 4, 4])
&gt;&gt;&gt; x == y
array([False, True, False, True, False], dtype=bool)
</code></pre>

When arrays <code>x</code> and <code>y</code> are compared with any comparison operator, NumPy applies the operator (roughly) elementwise and returns an array of results. This is useful, for example, to apply an operation to the cells of <code>x</code> that fit the condition:

<pre><code>&gt;&gt;&gt; x[x==y] = 6
&gt;&gt;&gt; x
array([1, 6, 3, 6, 5])
</code></pre>

Here, I've selected all elements of <code>x</code> that equal the corresponding elements of <code>y</code>, and set them equal to 6.

There is a confusion for me for some time: is there a scene that we do need to use rich comparison in Python?

I read the official doc <a href="http://docs.python.org/2/reference/datamodel.html#object.__lt__" rel="noreferrer">here</a>, but it only gives how it works not why we need it.

A snippet of the doc: 

<blockquote>
 The truth of <code>x==y</code> does not imply that <code>x!=y</code> is false. may describe a scene that we need rich comparison. In this scene, we can
 make <code>__eq__</code> and <code>__ne__</code> both return <code>False</code> for disabling the
 comparsion or any other purpose. (We can implement this by using
 <code>__cmp__</code>)
</blockquote>

But this just a guess, I have never encountered such a requirement in a real project yet.

Does anyone need to use rich comparison indeed or is there any other scenario where we need to use rich comparison in theory?

Maybe my example of <code>x==y</code> and <code>x!=y</code> caused some confusion, sorry for that.
Let me make it a bit clearer: 
Are there any scenario where rich comparison can help but <code>__cmp__</code> can not?

Why Python need rich comparison?

Python

有一段时间我有一个困惑:有没有一个场景我们确实需要在Python中使用丰富的比较？我读过官方文档，但它只说明了它是如何工作的，而不是我们为什么需要它。文档的一个片段：x==y的真假并不意味着x!=y就是假的。可以描述一个我们需要丰富对比的场景。在这个场景中，我们可以让__eq__和__ne__都返回False，以禁用比...

问为什么Python需要丰富的比较？
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