What does hash do in python

Question

I saw an example of code that where hash function is applied to a tuple  As a result it returns a negative integer  I wonder what does this function do  Google does not help  I found a page that explains how hash is calculated but it does not explain why we need this function

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The Python docs for hash   state      Hash values are integers  They are used to quickly compare dictionary keys during a dictionary lookup    Python dictionaries are implemented as hash tables  So any time you use a dictionary  hash   is called on the keys that you pass in for assignment  or look-up   Additionally  the docs for the dict type state      Values that are not hashable  that is  values containing lists  dictionaries or other mutable types  that are compared by value rather than by object identity  may not be used as keys

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TL DR   Please refer to the glossary  hash   is used as a shortcut to comparing objects  an object is deemed hashable if it can be compared to other objects  that is why we use hash    It s also used to access dict and set elements which are implemented as resizable hash tables in CPython   Technical considerations   usually comparing objects  which may involve several levels of recursion  is expensive  preferably  the hash   function is an order of magnitude  or several  less expensive  comparing two hashes is easier than comparing two objects  this is where the shortcut is    If you read about how dictionaries are implemented  they use hash tables  which means deriving a key from an object is a corner stone for retrieving objects in dictionaries in O 1   That s however very dependent on your hash function to be collision-resistant  The worst case for getting an item in a dictionary is actually O n    On that note  mutable objects are usually not hashable  The hashable property means you can use an object as a key  If the hash value is used as a key and the contents of that same object change  then what should the hash function return  Is it the same key or a different one  It depends on how you define your hash function   Learning by example   Imagine we have this class    gt  gt  gt  class Person object           def   init   self  name  ssn  address               self name   name             self ssn   ssn             self address   address         def   hash   self               return hash self ssn          def   eq   self  other               return self ssn    other ssn        Please note  this is all based on the assumption that the SSN never changes for an individual  don t even know where to actually verify that fact from authoritative source    And we have Bob    gt  gt  gt  bob   Person  bob    1111-222-333   None    Bob goes to see a judge to change his name    gt  gt  gt  jim   Person  jim bo    1111-222-333    sf bay area     This is what we know    gt  gt  gt  bob    jim True   But these are two different objects with different memory allocated  just like two different records of the same person    gt  gt  gt  bob is jim False   Now comes the part where hash   is handy    gt  gt  gt  dmv appointments       gt  gt  gt  dmv appointments bob     tomorrow    Guess what    gt  gt  gt  dmv appointments jim      tomorrow    From two different records you are able to access the same information  Now try this    gt  gt  gt  dmv appointments hash jim   Traceback  most recent call last     File   lt stdin gt    line 1  in  lt module gt    File   lt stdin gt    line 9  in   eq   AttributeError   int  object has no attribute  ssn   gt  gt  gt  hash jim     hash hash jim   True   What just happened  That s a collision  Because hash jim     hash hash jim   which are both integers btw  we need to compare the input of   getitem   with all items that collide  The builtin int does not have an ssn attribute so it trips    gt  gt  gt  del Person   eq    gt  gt  gt  dmv appointments bob   tomorrow   gt  gt  gt  dmv appointments jim  Traceback  most recent call last     File   lt stdin gt    line 1  in  lt module gt  KeyError   lt   main   Person object at 0x7f611bd37110 gt    In this last example  I show that even with a collision  the comparison is performed  the objects are no longer equal  which means it successfully raises a KeyError

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You can use the Dictionary data type in python  It s very very similar to the hash   and it also supports nesting  similar to the to nested hash   Example   dict     Name    Zara    Age   7   Class    First   dict  Age     8    update existing entry dict  School      DPS School    Add new entry  print   dict  Age       dict  Age    print   dict  School       dict  School      For more information  please reference this tutorial on the dictionary data type

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The hash is used by dictionaries and sets to quickly look up the object  A good starting point is Wikipedia s article on hash tables

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A hash is an fixed sized integer that identifies a particular value  Each value needs to have its own hash  so for the same value you will get the same hash even if it s not the same object    gt  gt  gt  hash  Look at me    4343814758193556824  gt  gt  gt  f    Look at me    gt  gt  gt  hash f  4343814758193556824   Hash values need to be created in such a way that the resulting values are evenly distributed to reduce the number of hash collisions you get  Hash collisions are when two different values have the same hash  Therefore  relatively small changes often result in very different hashes    gt  gt  gt  hash  Look at me     6941904779894686356   These numbers are very useful  as they enable quick look-up of values in a large collection of values  Two examples of their use are Python s set and dict  In a list  if you want to check if a value is in the list  with if x in values   Python needs to go through the whole list and compare x with each value in the list values  This can take a long time for a long list  In a set  Python keeps track of each hash  and when you type if x in values   Python will get the hash-value for x  look that up in an internal structure and then only compare x with the values that have the same hash as x   The same methodology is used for dictionary lookup  This makes lookup in set and dict very fast  while lookup in list is slow  It also means you can have non-hashable objects in a list  but not in a set or as keys in a dict  The typical example of non-hashable objects is any object that is mutable  meaning that you can change its value  If you have a mutable object it should not be hashable  as its hash then will change over its life-time  which would cause a lot of confusion  as an object could end up under the wrong hash value in a dictionary   Note that the hash of a value only needs to be the same for one run of Python  In Python 3 3 they will in fact change for every new run of Python      opt python33 bin python3 Python 3 3 2  default  Jun 17 2013  17 49 21    GCC 4 6 3  on linux Type  help    copyright    credits  or  license  for more information   gt  gt  gt  hash  foo   1849024199686380661  gt  gt  gt      opt python33 bin python3 Python 3 3 2  default  Jun 17 2013  17 49 21    GCC 4 6 3  on linux Type  help    copyright    credits  or  license  for more information   gt  gt  gt  hash  foo   -7416743951976404299   This is to make is harder to guess what hash value a certain string will have  which is an important security feature for web applications etc   Hash values should therefore not be stored permanently  If you need to use hash values in a permanent way you can take a look at the more  serious  types of hashes  cryptographic hash functions  that can be used for making verifiable checksums of files etc

[python] What does hash do in python?

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