blocks|key|2802327|text|像int这样的散列依赖于id()，而id()并不能保证两次运行或两次解释器之间的恒定。也就是说，在程序运行期间，hash(int)将始终产生相同的结果，但在同一平台或不同平台上的两次运行之间可能不同。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|2802328|顺便说一句，虽然散列随机化在Python中可用，但默认情况下它是禁用的。既然你的字符串和数字的散列是一样的，显然这不是这里的问题。|2802329|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|F|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|G|8|@]|9|@]|A|$]]|$1|D|3|-4|5|6|7|H|8|@]|9|@]|A|$]]]|E|$]]

Hashing of things like int relies on id(), which is not guaranteed constant between runs or between interpreters. That is, hash(int) will always produce the same result during a program's run, but might not compare equal between runs, either on the same platform or on different platforms.

BTW, while hash randomization is available in Python, it's disabled by default. Since your strings and numbers are hashing equally, clearly it's not the issue here.

blocks|key|185844|text|默认情况下，每次启动prevent+dictionary+insertion+DOS+attacks的最新版本(Python3.3%2B)的新实例时，hash()都是随机的|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|185845|在此之前，hash()对于32位和64位版本是不同的。|185846|如果您想要每次都散列到相同的内容，请使用hashlib中的一个散列|185847|>>>+import+hashlib
>>>+hashlib.algorithms
('md5',+'sha1',+'sha224',+'sha256',+'sha384',+'sha512')|code-block|syntax|javascript|185848|entityMap|0|LINK|mutability|MUTABLE|url|http://mail.python.org/pipermail/python-announce-list/2012-March/009394.html^0|21|6|A|14|0|0|5|6|0|0|0^^$0|@$1|2|3|4|5|6|7|W|8|@$9|X|A|Y|B|C]]|D|@$9|Z|A|10|1|11]]|E|$]]|$1|F|3|G|5|6|7|12|8|@$9|13|A|14|B|C]]|D|@]|E|$]]|$1|H|3|I|5|6|7|15|8|@]|D|@]|E|$]]|$1|J|3|K|5|L|7|16|8|@]|D|@]|E|$M|N]]|$1|O|3|-4|5|6|7|17|8|@]|D|@]|E|$]]]|P|$Q|$5|R|S|T|E|$U|V]]]]

<code>hash()</code> is randomised by default each time you start a new instance of recent versions (Python3.3+) to <a href="http://mail.python.org/pipermail/python-announce-list/2012-March/009394.html" rel="noreferrer">prevent dictionary insertion DOS attacks</a>

Prior to that, <code>hash()</code> was different for 32bit and 64bit builds anyway.

If you want something that does hash to the same thing every time, use one of the hashes in hashlib

<pre><code>&gt;&gt;&gt; import hashlib
&gt;&gt;&gt; hashlib.algorithms
('md5', 'sha1', 'sha224', 'sha256', 'sha384', 'sha512')
</code></pre>

blocks|key|3014610|text|对于旧的python+(至少是我的Python2.7)，似乎|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3014611|hash(<some+type>)+=+id(<type>)+/+16|code-block|syntax|javascript|3014612|对于CPython，id()是内存中的地址-+http://docs.python.org/2/library/functions.html#id|offset|length|style|CODE|3014613|>>>+id(int)+/+hash(int)+++++++++++++++++++++++++++++++++++++++++++++++++++++
16++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
>>>+id(int)+%25+hash(int)+++++++++++++++++++++++++++++++++++++++++++++++++
0+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++|3014614|所以我的猜测是Android端口对内存地址有一些奇怪的约定？|3014615|无论如何，鉴于上述情况，类型的散列(以及其他内置的，我猜)在不同的安装中会有所不同，因为函数位于不同的地址。|3014616|相反，值的哈希值(我认为您所说的“非内部对象”是指“非内部对象”)(在添加随机内容之前)是根据它们的值计算的，因此很可能是可重复的。|3014617|另外，至少还有一个CPython问题：|3014618|>>>+for+i+in+range(-1000,1000):
...+++++if+hash(i)+!=+i:+print(i)
...
-1|3014619|这里有一个答案可以解释这个问题。|3014620|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/2/library/functions.html#id^0|0|0|A|4|N|1E|0|0|0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|18|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|19|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|1A|8|@$I|1B|J|1C|K|L]]|9|@$I|1D|J|1E|1|1F]]|A|$]]|$1|M|3|N|5|D|7|1G|8|@]|9|@]|A|$E|F]]|$1|O|3|P|5|6|7|1H|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1I|8|@]|9|@]|A|$]]|$1|S|3|T|5|6|7|1J|8|@]|9|@]|A|$]]|$1|U|3|V|5|6|7|1K|8|@]|9|@]|A|$]]|$1|W|3|X|5|D|7|1L|8|@]|9|@]|A|$E|F]]|$1|Y|3|Z|5|6|7|1M|8|@]|9|@]|A|$]]|$1|10|3|-4|5|6|7|1N|8|@]|9|@]|A|$]]]|11|$12|$5|13|14|15|A|$16|17]]]]

for old python (at least, my Python 2.7), it seems that

<pre><code>hash(&lt;some type&gt;) = id(&lt;type&gt;) / 16
</code></pre>

and for CPython <code>id()</code> is the address in memory - <a href="http://docs.python.org/2/library/functions.html#id" rel="noreferrer">http://docs.python.org/2/library/functions.html#id</a>

<pre><code>&gt;&gt;&gt; id(int) / hash(int) 
16 
&gt;&gt;&gt; id(int) % hash(int) 
0 
</code></pre>

so my guess is that the Android port has some strange convention for memory addresses?

anyway, given the above, hashes for types (and other built-ins i guess) will differ across installs because functions are at different addresses.

in contrast, hashes for values (what i think you mean by "non-internal objects") (before the random stuff was added) are calculated from their values and so likely repeatable.

PS but there's at least one more CPython wrinkle:

<pre><code>&gt;&gt;&gt; for i in range(-1000,1000):
... if hash(i) != i: print(i)
...
-1
</code></pre>

there's an answer here somewhere explaining that one...

blocks|key|187999|text|对于CPython，出于效率原因，内部对象上的hash()返回与id()相同的值，而后者又返回对象的内存位置(“地址”)。|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|188000|从一个基于CPython的解释器到另一个对象的内存位置可能会发生变化。根据您的操作系统，这可能会从一次运行到另一次运行。|188001|entityMap|0|LINK|mutability|MUTABLE|url|http://docs.python.org/2/library/functions.html#hash|1|http://docs.python.org/2/library/functions.html#id^0|N|6|W|4|N|6|0|W|4|1|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@$9|S|A|T|B|C]|$9|U|A|V|B|C]]|D|@$9|W|A|X|1|Y]|$9|Z|A|10|1|11]]|E|$]]|$1|F|3|G|5|6|7|12|8|@]|D|@]|E|$]]|$1|H|3|-4|5|6|7|13|8|@]|D|@]|E|$]]]|I|$J|$5|K|L|M|E|$N|O]]|P|$5|K|L|M|E|$N|Q]]]]

With CPython, for efficiency reason <a href="http://docs.python.org/2/library/functions.html#hash" rel="nofollow"><code>hash()</code></a> on internal objects returns the same value as <a href="http://docs.python.org/2/library/functions.html#id" rel="nofollow"><code>id()</code></a> which in its turn return the memory location ("address") of the object.

From one CPython-based interpreter to an other memory location of such object is subject to change. Depending on your OS, this could change from one run to an other.

blocks|key|3014697|text|从Python3.3开始，默认的散列算法已经创建了散列值，这些散列值带有一个随机值，即使在同一台机器上的不同Python进程之间也是不同的。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3014698|哈希随机化目前只针对字符串实现-因为它被认为是从外部捕获的最有可能受到攻击的数据类型。|3014699|相同的冻结集在不同的机器甚至不同的进程中一致地产生相同的哈希值|3014700|来源：https://www.quora.com/Do-two-computers-produce-the-same-hash-for-identical-objects-in-Python|offset|length|3014701|entityMap|0|LINK|mutability|MUTABLE|url|https://www.quora.com/Do-two-computers-produce-the-same-hash-for-identical-objects-in-Python^0|0|0|0|3|2K|0|0^^$0|@$1|2|3|4|5|6|7|R|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|S|8|@]|9|@]|A|$]]|$1|D|3|E|5|6|7|T|8|@]|9|@]|A|$]]|$1|F|3|G|5|6|7|U|8|@]|9|@$H|V|I|W|1|X]]|A|$]]|$1|J|3|-4|5|6|7|Y|8|@]|9|@]|A|$]]]|K|$L|$5|M|N|O|A|$P|Q]]]]

From Python 3.3 the default hash algorithm has created hash values which are salted with a random value which is different even between different python processes on the same machine.

Hash randomization only is implemented currently for strings - since it was considered to be the most likely data type captured from outside that could be attacked.

The same frozenset consistently produces the same hash value across different machines or even different processes

Source: <a href="https://www.quora.com/Do-two-computers-produce-the-same-hash-for-identical-objects-in-Python" rel="nofollow noreferrer">https://www.quora.com/Do-two-computers-produce-the-same-hash-for-identical-objects-in-Python</a>

I believed that <code>hash()</code> function works the same in all python interpreters. But it differs when I run it on my mobile using <a href="https://code.google.com/p/python-for-android/">python for android</a>. I get same hash value for hashing strings and numbers but when I hash built-in data types the hash value differs.

PC Python Interpreter (Python 2.7.3)

<pre><code>&gt;&gt;&gt; hash(int)
31585118
&gt;&gt;&gt; hash("hello sl4a")
1532079858
&gt;&gt;&gt; hash(101)
101
</code></pre>

Mobile Python Interpreter (Python 2.6.2)

<pre><code>&gt;&gt;&gt; hash(int)
-2146549248
&gt;&gt;&gt; hash("hello sl4a")
1532079858
&gt;&gt;&gt; hash(101)
101
</code></pre>

Can any one tell me is it a bug or I misunderstood something.

Why doesn't Python hash function give the same values when run on Android implementation?

解释器

Android

Python

我相信hash()函数在所有python解释器中都是一样的。但是当我使用在我的手机上运行它时，它就不同了。对于散列字符串和数字，我得到了相同的散列值，但是当我散列内置数据类型时，散列值就不同了。PC Python解释器(Python2.7.3)>>> hash(int)31585118>>> hash("hello s...

问为什么Python哈希函数在Android实现上运行时没有给出相同的值？
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