I believed that hash()
function works the same in all python interpreters. But it differs when I run it on my mobile using python for android. 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)
>>> hash(int) 31585118 >>> hash("hello sl4a") 1532079858 >>> hash(101) 101
Mobile Python Interpreter (Python 2.6.2)
>>> hash(int) -2146549248 >>> hash("hello sl4a") 1532079858 >>> hash(101) 101
Can any one tell me is it a bug or I misunderstood something.
Yes, if you hash the same input with the same function, you will always get the same result.
As noted by many, Python's hash is not consistent anymore (as of version 3.3), as a random PYTHONHASHSEED is now used by default (to address security concerns, as explained in this excellent answer).
Python uses hash tables for dictionaries and sets. A hash table is an unordered collection of key-value pairs, where each key is unique.
The hash() method returns the hash value of an object if it has one. Hash values are just integers that are used to compare dictionary keys during a dictionary look quickly.
hash()
is randomised by default each time you start a new instance of recent versions (Python3.3+) to prevent dictionary insertion DOS attacks
Prior to that, hash()
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
>>> import hashlib >>> hashlib.algorithms ('md5', 'sha1', 'sha224', 'sha256', 'sha384', 'sha512')
for old python (at least, my Python 2.7), it seems that
hash(<some type>) = id(<type>) / 16
and for CPython id()
is the address in memory - http://docs.python.org/2/library/functions.html#id
>>> id(int) / hash(int) 16 >>> id(int) % hash(int) 0
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:
>>> for i in range(-1000,1000): ... if hash(i) != i: print(i) ... -1
there's an answer here somewhere explaining that one...
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