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For example, one could define a dictionary having a string "toast" mapped to the integer 42 or vice versa. The keys in a dictionary must be of an immutable Python type, such as an integer or a string, because under the hood they are implemented via a hash function. This makes for much faster lookup times, but requires keys not change.
The relatively new System.Collections.Immutable package, available in .NET Framework versions 4.5 and above, and in all versions of .NET Core, also includes the System.Collections.Immutable.Dictionary<TKey, TValue> type, which is implemented using an AVL tree. The methods that would normally mutate the object in-place instead return a new ...
Lists are written as [1, 2, 3], are mutable, and cannot be used as the keys of dictionaries (dictionary keys must be immutable in Python). Tuples, written as (1, 2, 3), are immutable and thus can be used as keys of dictionaries, provided all of
Duck typing is similar to, but distinct from, structural typing.Structural typing is a static typing system that determines type compatibility and equivalence by a type's structure, whereas duck typing is dynamic and determines type compatibility by only that part of a type's structure that is accessed during runtime.
The immutable pointer and length are being copied and the copies are mutable. The referred data has not been copied and keeps its qualifier, in the example immutable. It can be stripped by making a depper copy, e.g. using the dup function.
A hash table uses a hash function to compute an index, also called a hash code, into an array of buckets or slots, from which the desired value can be found. During lookup, the key is hashed and the resulting hash indicates where the corresponding value is stored. A map implemented by a hash table is called a hash map.
Mutable (non-const) operations can then be implemented in such a way that they create new objects instead of modifying the existing ones. This approach is characteristic of functional programming and is also used by the string implementations in Java, C#, and Python. (See Immutable object.)
The main difference between an arbitrary data structure and a purely functional one is that the latter is (strongly) immutable. This restriction ensures the data structure possesses the advantages of immutable objects: (full) persistency, quick copy of objects, and thread safety.