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  • Good Hash Function for Strings

    - by Leif Andersen
    I'm trying to think up a good hash function for strings. And I was thinking it might be a good idea to sum up the unicode values for the first five characters in the string (assuming it has five, otherwise stop where it ends). Would that be a good idea, or is it a bad one? I am doing this in Java, but I wouldn't imagine that would make much of a difference.

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  • Use hash or case-statement [Ruby]

    - by user94154
    Generally which is better to use?: case n when 'foo' result = 'bar' when 'peanut butter' result = 'jelly' when 'stack' result = 'overflow' return result or map = {'foo' => 'bar', 'peanut butter' => 'jelly', 'stack' => 'overflow'} return map[n] More specifically, when should I use case-statements and when should I simply use a hash?

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  • hash password in mssql (asp.net)

    - by ile
    Is this how hashed password stored in mssql should look like? This is function I use to hash password (I found it in some tutorial) public string EncryptPassword(string password) { //we use codepage 1252 because that is what sql server uses byte[] pwdBytes = Encoding.GetEncoding(1252).GetBytes(password); byte[] hashBytes = System.Security.Cryptography.MD5.Create().ComputeHash(pwdBytes); return Encoding.GetEncoding(1252).GetString(hashBytes); } Thanks, Ile

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  • Perl, convert hash to array

    - by Mike
    If I have a hash in Perl that contains complete and sequential integer mappings (ie, all keys from from 0 to n are mapped to something), is there a means of converting this to an Array? I know I could iterate over the key/value pairs and place them into a new array, but something tells me there should be a built-in means of doing this.

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  • djb2 Hash Function

    - by Jainish
    I am using the djb2 algorithm to generate the hash key for a string which is as follows hash(unsigned char *str) { unsigned long hash = 5381; int c; while (c = *str++) hash = ((hash << 5) + hash) + c; /* hash * 33 + c */ return hash; } Now with every loop there is a multiplication with two big numbers, After some time with the 4th of 5th character of the string there is a overflow as the hash value becomes huge What is the correct way to refactor so that the hash value does not overflow and the hashing also happens correctly

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  • Salt and hash a password in .NET

    - by Jon Canning
    I endeavoured to follow the CrackStation rules: Salted Password Hashing - Doing it Right    public class SaltedHash     {         public string Hash { get; private set; }         public string Salt { get; private set; }         public SaltedHash(string password)         {             var saltBytes = new byte[32];             new RNGCryptoServiceProvider().GetNonZeroBytes(saltBytes);             Salt = ConvertToBase64String(saltBytes);             var passwordAndSaltBytes = Concat(password, saltBytes);             Hash = ComputeHash(passwordAndSaltBytes);         }         static string ConvertToBase64String(byte[] bytes)         {             return Convert.ToBase64String(bytes);         }         static string ComputeHash(byte[] bytes)         {             return ConvertToBase64String(SHA256.Create().ComputeHash(bytes));         }         static byte[] Concat(string password, byte[] saltBytes)         {             var passwordBytes = Encoding.UTF8.GetBytes(password);             return passwordBytes.Concat(saltBytes).ToArray();         }         public static bool Verify(string salt, string hash, string password)         {             var saltBytes = Convert.FromBase64String(salt);             var passwordAndSaltBytes = Concat(password, saltBytes);             var hashAttempt = ComputeHash(passwordAndSaltBytes);             return hash == hashAttempt;         }     }

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  • Tracking unique versions of files with hashes

    - by rwmnau
    I'm going to be tracking different versions of potentially millions of different files, and my intent is to hash them to determine I've already seen that particular version of the file. Currently, I'm only using MD5 (the product is still in development, so it's never dealt with millions of files yet), which is clearly not long enough to avoid collisions. However, here's my question - Am I more likely to avoid collisions if I hash the file using two different methods and store both hashes (say, SHA1 and MD5), or if I pick a single, longer hash (like SHA256) and rely on that alone? I know option 1 has 288 hash bits and option 2 has only 256, but assume my two choices are the same total hash length. Since I'm dealing with potentially millions of files (and multiple versions of those files over time), I'd like to do what I can to avoid collisions. However, CPU time isn't (completely) free, so I'm interested in how the community feels about the tradeoff - is adding more bits to my hash proportionally more expensive to compute, and are there any advantages to multiple different hashes as opposed to a single, longer hash, given an equal number of bits in both solutions?

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  • Hash 32bit int to 16bit int?

    - by dkamins
    What are some simple ways to hash a 32-bit integer (e.g. IP address, e.g. Unix time_t, etc.) down to a 16-bit integer? E.g. hash_32b_to_16b(0x12345678) might return 0xABCD. Let's start with this as a horrible but functional example solution: function hash_32b_to_16b(val32b) { return val32b % 0xffff; } Question is specifically about JavaScript, but feel free to add any language-neutral solutions, preferably without using library functions. Simple = good. Wacky+obfuscated = amusing.

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  • Ruby: change each value in a hash with something like #collect for arrays?

    - by Adam Nonymous
    Hi! I'd like to replace each value in a hash with value.some_method. For example in a simple hash {"a" = "b", "c" = "d"} every value should be .upcase-d so it looks like {"a" = "B", "c" = "D"}. I tried #collect and #map but always just get arrays back. Is there an 'elegant' way to do this? Thanks in advance, Adam Nonymous UPDATE: Damn, I forgot: The hash is in an instance variable which should not be changed. I need a new hash with the changed values, but would prefer not to define that variable explicitly and then loop over the hash filling it. Something like new_hash = hash.magic {...} ;)

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  • Mapping multiple keys to the same value in a Javascript hash

    - by Bears will eat you
    I use a Javascript hash object to store a set of numerical counters, set up like this [this is greatly simplified]: var myHash = { A: 0, B: 0, C: 0 }; Is there a way to make other keys, ones not explicitly in myHash, map to keys that are? For instance, I'd like [again, this is simplified]: myHash['A_prime']++; // or myHash.A_prime++; to be exactly equivalent to myHash['A']++; // or myHash.A++; e.g. incrementing the value found at the key A, not A_prime.

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  • Perfect hash in Scala.

    - by Lukasz Lew
    I have some class C: class C (...) { ... } I want to use it to index an efficient map. The most efficient map is an Array. So I add a "global" "static" counter in companion object to give each object unique id: object C { var id_counter = 0 } In primary constructor of C, with each creation of C I want to remember global counter value and increase it. Question 1: How to do it? Now I can use id in C objects as perfect hash to index array. But array does not preserve type information like map would, that a given array is indexed by C's id. Question 2: Is it possible to have it with type safety?

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  • Summarize object area with a Hash in Ruby

    - by Arto Uusikangas
    require 'sketchup' entities = Sketchup.active_model.entities summa = Hash.new for face in entities next unless face.kind_of? Sketchup::Face if (face.material) summa[face.material.display_name] += face.area end end Im trying to get the structure in the array as such: summa { "Bricks" = 500, "Planks" = 4000 } Making a ruby script for Google Sketchup btw But if I run this code i only get Error: #+' for nil:NilClass> C:\Program Files (x86)\Google\Google SketchUp 7\Plugins\test.rb:17 C:\Program Files (x86)\Google\Google SketchUp 7\Plugins\test.rb:14:ineach' C:\Program Files (x86)\Google\Google SketchUp 7\Plugins\test.rb:14 C:\Program Files (x86)\Google\Google SketchUp 7\Plugins\test.rb:8:in `call' As im used to using PHP and just doing $array['myownassoc'] += bignumber; But i guess this isnt the right approach when using Ruby? So any help in how i need to go would be nice.

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  • hash password in SQL Server (asp.net)

    - by ile
    Is this how hashed password stored in SQL Server should look like? This is function I use to hash password (I found it in some tutorial) public string EncryptPassword(string password) { //we use codepage 1252 because that is what sql server uses byte[] pwdBytes = Encoding.GetEncoding(1252).GetBytes(password); byte[] hashBytes = System.Security.Cryptography.MD5.Create().ComputeHash(pwdBytes); return Encoding.GetEncoding(1252).GetString(hashBytes); } EDIT I tried to use sha-1 and now strings seem to look like as they are suppose to: public string EncryptPassword(string password) { return FormsAuthentication.HashPasswordForStoringInConfigFile(password, "sha1"); } // example output: 39A43BDB7827112409EFED3473F804E9E01DB4A8 Result from the image above looks like broken string, but this sha-1 looks normal.... Will this be secure enough?

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  • Merge a hash with the key/values of a string in ruby

    - by LazyJason
    Hi there, I'm trying to merge a hash with the key/values of string in ruby. i.e. h = {:day => 4, :month => 8, :year => 2010} s = "/my/crazy/url/:day/:month/:year" puts s.interpolate(h) All I've found is to iterate the keys and replace the values. But I'm not sure if there's a better way doing this? :) class String  def interpolate(e)    self if e.each{|k, v| self.gsub!(":#{k}", "#{v}")}  end end Thanks

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  • Lists Hash function

    - by John Retallack
    I'm trying to make a hash function so I can tell if too lists with same sizes contain the same elements. For exemple this is what I want: f((1 2 3))=f((1 3 2))=f((2 1 3))=f((2 3 1))=f((3 1 2))=f((3 2 1)). Any ideea how can I approch this problem ? I've tried doing the sum of squares of all elements but it turned out that there are collisions,for exemple f((2 2 5))=33=f((1 4 4)) which is wrong as the lists are not the same. I'm looking for a simple approach it there are any.

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  • Hash Function Added To The PredicateEqualityComparer

    - by Paulo Morgado
    Sometime ago I wrote a predicate equality comparer to be used with LINQ’s Distinct operator. The Distinct operator uses an instance of an internal Set class to maintain the collection of distinct elements in the source collection which in turn checks the hash code of each element (by calling the GetHashCode method of the equality comparer) and only if there’s already an element with the same hash code in the collection calls the Equals method of the comparer to disambiguate. At the time I provided only the possibility to specify the comparison predicate, but, in some cases, comparing a hash code instead of calling the provided comparer predicate can be a significant performance improvement, I’ve added the possibility to had a hash function to the predicate equality comparer. You can get the updated code from the PauloMorgado.Linq project on CodePlex,

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  • Stack and Hash joint

    - by Alexandru
    I'm trying to write a data structure which is a combination of Stack and HashSet with fast push/pop/membership (I'm looking for constant time operations). Think of Python's OrderedDict. I tried a few things and I came up with the following code: HashInt and SetInt. I need to add some documentation to the source, but basically I use a hash with linear probing to store indices in a vector of the keys. Since linear probing always puts the last element at the end of a continuous range of already filled cells, pop() can be implemented very easy without a sophisticated remove operation. I have the following problems: the data structure consumes a lot of memory (some improvement is obvious: stackKeys is larger than needed). some operations are slower than if I have used fastutil (eg: pop(), even push() in some scenarios). I tried rewriting the classes using fastutil and trove4j, but the overall speed of my application halved. What performance improvements would you suggest for my code? What open-source library/code do you know that I can try?

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  • whats wrong with this ruby hash?

    - by yaya3
    I'm pretty new to ruby, I keep getting the following error: in gem_original_require': ./helpers/navigation.rb:28: odd number list for Hash (SyntaxError) Any help appreciated... module Sinatra::Navigation def navigation @navigation nav = { primary[0] = { :title => "cheddar", :active => false, :children => { { :title => "cheese", :active => false }, { :title => "ham", :active => false } } }, primary[1] = { :title => "gorgonzola", :active => false, :children => { { :title => "What is the cheese?", :active => false }, { :title => "What cheese", :active => false }, { :title => "What does the cheese tell us?", :active => false, :children => { { :title => "Cheessus", :active => false }, { :title => "The impact of different cheeses / characteristics for cheese in relation to CHSE outcomes", :active => false } } } } } }

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  • hash fragments and collisions cont.

    - by Mark
    For this application I've mine I feel like I can get away with a 40 bit hash key, which seems awfully low, but see if you can confirm my reasoning (I want a small key because I want a small filename and the key will be converted to a filename): (Note: only accidental collisions a concern - no security issues.) A key point here is that the population in question is divided into groups, and a collision is only relevant if it occurs within the same group. A "group" is a directory on a user's system (the contents of files are hashed and a collision is only relevant if it occurs for files within the same directory). So with speculating roughly 100,000 potential users, say 2^17, that corresponds to 2^18 "groups" assuming 2 directories per user on average. So with a 40 bit key I can expect 2^(20+9) files created (among all users) before a collision occurs for some user somewhere. (Or IOW 2^((40+18)/2), due to the "birthday effect".) That's an average 4096 unique files created per user, for 2^17 users, before a single collision occurs for some user somewhere. And then that long again before another collision occurs somewhere (right?)

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  • Plan Caching and Query Memory Part II (Hash Match) – When not to use stored procedure - Most common performance mistake SQL Server developers make.

    - by sqlworkshops
    SQL Server estimates Memory requirement at compile time, when stored procedure or other plan caching mechanisms like sp_executesql or prepared statement are used, the memory requirement is estimated based on first set of execution parameters. This is a common reason for spill over tempdb and hence poor performance. Common memory allocating queries are that perform Sort and do Hash Match operations like Hash Join or Hash Aggregation or Hash Union. This article covers Hash Match operations with examples. It is recommended to read Plan Caching and Query Memory Part I before this article which covers an introduction and Query memory for Sort. In most cases it is cheaper to pay for the compilation cost of dynamic queries than huge cost for spill over tempdb, unless memory requirement for a query does not change significantly based on predicates.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   To read additional articles I wrote click here.   The best way to learn is to practice. To create the below tables and reproduce the behavior, join the mailing list by using this link: www.sqlworkshops.com/ml and I will send you the table creation script. Most of these concepts are also covered in our webcasts: www.sqlworkshops.com/webcasts  Let’s create a Customer’s State table that has 99% of customers in NY and the rest 1% in WA.Customers table used in Part I of this article is also used here.To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'. --Example provided by www.sqlworkshops.com drop table CustomersState go create table CustomersState (CustomerID int primary key, Address char(200), State char(2)) go insert into CustomersState (CustomerID, Address) select CustomerID, 'Address' from Customers update CustomersState set State = 'NY' where CustomerID % 100 != 1 update CustomersState set State = 'WA' where CustomerID % 100 = 1 go update statistics CustomersState with fullscan go   Let’s create a stored procedure that joins customers with CustomersState table with a predicate on State. --Example provided by www.sqlworkshops.com create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1) end go  Let’s execute the stored procedure first with parameter value ‘WA’ – which will select 1% of data. set statistics time on go --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' goThe stored procedure took 294 ms to complete.  The stored procedure was granted 6704 KB based on 8000 rows being estimated.  The estimated number of rows, 8000 is similar to actual number of rows 8000 and hence the memory estimation should be ok.  There was no Hash Warning in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Now let’s execute the stored procedure with parameter value ‘NY’ – which will select 99% of data. -Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  The stored procedure took 2922 ms to complete.   The stored procedure was granted 6704 KB based on 8000 rows being estimated.    The estimated number of rows, 8000 is way different from the actual number of rows 792000 because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘WA’ in our case. This underestimation will lead to spill over tempdb, resulting in poor performance.   There was Hash Warning (Recursion) in SQL Profiler. To observe Hash Warning, enable 'Hash Warning' in SQL Profiler under Events 'Errors and Warnings'.   Let’s recompile the stored procedure and then let’s first execute the stored procedure with parameter value ‘NY’.  In a production instance it is not advisable to use sp_recompile instead one should use DBCC FREEPROCCACHE (plan_handle). This is due to locking issues involved with sp_recompile, refer to our webcasts, www.sqlworkshops.com/webcasts for further details.   exec sp_recompile CustomersByState go --Example provided by www.sqlworkshops.com exec CustomersByState 'NY' go  Now the stored procedure took only 1046 ms instead of 2922 ms.   The stored procedure was granted 146752 KB of memory. The estimated number of rows, 792000 is similar to actual number of rows of 792000. Better performance of this stored procedure execution is due to better estimation of memory and avoiding spill over tempdb.   There was no Hash Warning in SQL Profiler.   Now let’s execute the stored procedure with parameter value ‘WA’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go  The stored procedure took 351 ms to complete, higher than the previous execution time of 294 ms.    This stored procedure was granted more memory (146752 KB) than necessary (6704 KB) based on parameter value ‘NY’ for estimation (792000 rows) instead of parameter value ‘WA’ for estimation (8000 rows). This is because the estimation is based on the first set of parameter value supplied to the stored procedure which is ‘NY’ in this case. This overestimation leads to poor performance of this Hash Match operation, it might also affect the performance of other concurrently executing queries requiring memory and hence overestimation is not recommended.     The estimated number of rows, 792000 is much more than the actual number of rows of 8000.  Intermediate Summary: This issue can be avoided by not caching the plan for memory allocating queries. Other possibility is to use recompile hint or optimize for hint to allocate memory for predefined data range.Let’s recreate the stored procedure with recompile hint. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, recompile) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 297 ms and 1102 ms in line with previous optimal execution times.   The stored procedure with parameter value ‘WA’ has good estimation like before.   Estimated number of rows of 8000 is similar to actual number of rows of 8000.   The stored procedure with parameter value ‘NY’ also has good estimation and memory grant like before because the stored procedure was recompiled with current set of parameter values.  Estimated number of rows of 792000 is similar to actual number of rows of 792000.    The compilation time and compilation CPU of 1 ms is not expensive in this case compared to the performance benefit.   There was no Hash Warning in SQL Profiler.   Let’s recreate the stored procedure with optimize for hint of ‘NY’. --Example provided by www.sqlworkshops.com drop proc CustomersByState go create proc CustomersByState @State char(2) as begin declare @CustomerID int select @CustomerID = e.CustomerID from Customers e inner join CustomersState es on (e.CustomerID = es.CustomerID) where es.State = @State option (maxdop 1, optimize for (@State = 'NY')) end go  Let’s execute the stored procedure initially with parameter value ‘WA’ and then with parameter value ‘NY’. --Example provided by www.sqlworkshops.com exec CustomersByState 'WA' go exec CustomersByState 'NY' go  The stored procedure took 353 ms with parameter value ‘WA’, this is much slower than the optimal execution time of 294 ms we observed previously. This is because of overestimation of memory. The stored procedure with parameter value ‘NY’ has optimal execution time like before.   The stored procedure with parameter value ‘WA’ has overestimation of rows because of optimize for hint value of ‘NY’.   Unlike before, more memory was estimated to this stored procedure based on optimize for hint value ‘NY’.    The stored procedure with parameter value ‘NY’ has good estimation because of optimize for hint value of ‘NY’. Estimated number of rows of 792000 is similar to actual number of rows of 792000.   Optimal amount memory was estimated to this stored procedure based on optimize for hint value ‘NY’.   There was no Hash Warning in SQL Profiler.   This article covers underestimation / overestimation of memory for Hash Match operation. Plan Caching and Query Memory Part I covers underestimation / overestimation for Sort. It is important to note that underestimation of memory for Sort and Hash Match operations lead to spill over tempdb and hence negatively impact performance. Overestimation of memory affects the memory needs of other concurrently executing queries. In addition, it is important to note, with Hash Match operations, overestimation of memory can actually lead to poor performance.   Summary: Cached plan might lead to underestimation or overestimation of memory because the memory is estimated based on first set of execution parameters. It is recommended not to cache the plan if the amount of memory required to execute the stored procedure has a wide range of possibilities. One can mitigate this by using recompile hint, but that will lead to compilation overhead. However, in most cases it might be ok to pay for compilation rather than spilling sort over tempdb which could be very expensive compared to compilation cost. The other possibility is to use optimize for hint, but in case one sorts more data than hinted by optimize for hint, this will still lead to spill. On the other side there is also the possibility of overestimation leading to unnecessary memory issues for other concurrently executing queries. In case of Hash Match operations, this overestimation of memory might lead to poor performance. When the values used in optimize for hint are archived from the database, the estimation will be wrong leading to worst performance, so one has to exercise caution before using optimize for hint, recompile hint is better in this case.   I explain these concepts with detailed examples in my webcasts (www.sqlworkshops.com/webcasts), I recommend you to watch them. The best way to learn is to practice. To create the above tables and reproduce the behavior, join the mailing list at www.sqlworkshops.com/ml and I will send you the relevant SQL Scripts.  Register for the upcoming 3 Day Level 400 Microsoft SQL Server 2008 and SQL Server 2005 Performance Monitoring & Tuning Hands-on Workshop in London, United Kingdom during March 15-17, 2011, click here to register / Microsoft UK TechNet.These are hands-on workshops with a maximum of 12 participants and not lectures. For consulting engagements click here.   Disclaimer and copyright information:This article refers to organizations and products that may be the trademarks or registered trademarks of their various owners. Copyright of this article belongs to R Meyyappan / www.sqlworkshops.com. You may freely use the ideas and concepts discussed in this article with acknowledgement (www.sqlworkshops.com), but you may not claim any of it as your own work. This article is for informational purposes only; you use any of the suggestions given here entirely at your own risk.   R Meyyappan [email protected] LinkedIn: http://at.linkedin.com/in/rmeyyappan

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  • Hash Code for a group of three fields

    - by Gauranga
    I have three fields namely Number1 Number2 Time I am trying to write a function in java that returns a unique hash value (long needs to be the return type of hash) for the above fields. This hash would then be used to store database rows corresponding to the above mentioned fields in a HashSet. I am new to writing a hash code function, can someone please review what I have. Any help would be appreciated. public class HashCode { private long Number1; private long Number2; String Time; public HashCode(long Number1, long Number2, String Time){ this.Number1 = Number1; this.Number2 = Number2; this.Time = Time; } public long getHashCode() { long hash = 3; hash = 47 * hash + (long) (this.Number1 ^ (this.Number1 >>> 32)); hash = 47 * hash + (long) (this.Number2 ^ (this.Number2 >>> 32)); hash = 47 * hash + (this.Time != null ? this.Time.hashCode() : 0); return hash; } }

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  • Contrary to Python 3.1 Docs, hash(obj) != id(obj). So which is correct?

    - by Don O'Donnell
    The following is from the Python v3.1.2 documentation: From The Python Language Reference Section 3.3.1 Basic Customization: object.__hash__(self) ... User-defined classes have __eq__() and __hash__() methods by default; with them, all objects compare unequal (except with themselves) and x.__hash__() returns id(x). From The Glossary: hashable ... Objects which are instances of user-defined classes are hashable by default; they all compare unequal, and their hash value is their id(). This is true up through version 2.6.5: Python 2.6.5 (r265:79096, Mar 19 2010 21:48:26) ... ... >>> class C(object): pass ... >>> c = C() >>> id(c) 11335856 >>> hash(c) 11335856 But in version 3.1.2: Python 3.1.2 (r312:79149, Mar 21 2010, 00:41:52) ... ... >>> class C: pass ... >>> c = C() >>> id(c) 11893680 >>> hash(c) 743355 So which is it? Should I report a documentation bug or a program bug? And if it's a documentation bug, and the default hash() value for a user class instance is no longer the same as the id() value, then it would be interesting to know what it is or how it is calculated, and why it was changed in version 3.

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