Prerequisites For this answer I’m going to assume you know how to use pointers, structs, and have a basic understanding of the C language. Also if you don’t know. When talking about the speed of algorithms and data structures you should know the terms: O() = (it’s pronounced “Big-oh”) Big-oh or O() refers to the … Read more
If you are working with classes and not structs, you can use the ObjectIdentifier struct. Note that you also have to define == for your class in order to conform to Equatable (Hashable requires it). It would look something like this: class MyClass: Hashable { } func ==(lhs: MyClass, rhs: MyClass) -> Bool { return … Read more
Hash-tables could not claim “amortized constant time insertion” if, for instance, the resizing was by a constant increment. In that case the cost of resizing (which grows with the size of the hash-table) would make the cost of one insertion linear in the total number of elements to insert. Because resizing becomes more and more … Read more
This should be enough: parameterList.Remove(key);
Well, think of it this way. If you use an array, a simple index-based data structure, and fill it up with random stuff, finding a particular entry gets to be a more and more expensive operation as you fill it with data, since you basically have to start searching from one end toward the other, … Read more
It’s impossible to know in advance how many collisions you will get with your hash function, as well as things like needing to resize. This can add an element of unpredictability to the performance of a hash table, making it not true O(1). However, virtually all hash table implementations offer O(1) on the vast, vast, … Read more
The map has to work out which internal table index to use for any given key, mapping any int value (could be negative) to a value in the range [0, table.length). When table.length is a power of two, that can be done really cheaply – and is, in indexFor: static int indexFor(int h, int length) … Read more
In Python 3 you can use this dictionary comprehension syntax: def foo(somelist): return {x[0]:x for x in somelist}
You can find a good (and fast) hash function, and an interesting read, at http://www.azillionmonkeys.com/qed/hash.html The only time you should not check for collisions, is if you use a perfect hash — a good old fashioned lookup table, like gperf.
Update Martin R writes: As of Swift 4.1, the compiler can synthesize Equatable and Hashable for types conformance automatically, if all members conform to Equatable/Hashable (SE0185). And as of Swift 4.2, a high-quality hash combiner is built-in into the Swift standard library (SE-0206). Therefore there is no need anymore to define your own hashing function, … Read more