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The difference between const and immutable is what they apply to: const is a property of the variable: there might legally exist mutable references to referred value, i.e. the value can actually change.
Python sets are very much like mathematical sets, and support operations like set intersection and union. Python also features a frozenset class for immutable sets, see Collection types. Dictionaries (class dict) are mutable mappings tying keys and corresponding values. Python has special syntax to create dictionaries ({key: value})
Python makes a distinction between lists and tuples. 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 the tuple's elements are immutable.
In object-oriented programming, "immutable interface" is a pattern for designing an immutable object. [1] The immutable interface pattern involves defining a type which does not provide any methods which mutate state. Objects which are referenced by that type are not seen to have any mutable state, and appear immutable.
In D the type constructors are const, immutable, shared, and inout. immutable is a stronger variant of const, indicating data that can never change its value, while const indicates data that cannot be changed through this reference: it is a constant view on possibly mutable data.
Many languages have explicit pointers or references. Reference types differ from these in that the entities they refer to are always accessed via references; for example, whereas in C++ it's possible to have either a std:: string and a std:: string *, where the former is a mutable string and the latter is an explicit pointer to a mutable string (unless it's a null pointer), in Java it is only ...
The tail will not be duplicated, instead becoming shared between both the old list and the new list. So long as the contents of the tail are immutable, this sharing will be invisible to the program. Many common reference-based data structures, such as red–black trees, [7] stacks, [8] and treaps, [9] can easily be adapted to create a ...
Immutable objects are easily shared, but require creating new extrinsic objects whenever a change in state occurs. In contrast, mutable objects can share state. Mutability allows better object reuse via the caching and re-initialization of old, unused objects. Sharing is usually nonviable when state is highly variable.