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In OCaml, the library function Oo.copy performs shallow copying of an object. In Python, the library's copy module provides shallow copy and deep copy of objects through the copy() and deepcopy() functions, respectively. [13] Programmers may define special methods __copy__() and __deepcopy__() in an object to provide custom copying implementation.
A technique that blends the advantages of mutable and immutable objects, and is supported directly in almost all modern hardware, is copy-on-write (COW). Using this technique, when a user asks the system to copy an object, it instead merely creates a new reference that still points to the same object.
Mojo def functions use value semantics by default (functions receive a copy of all arguments and any modifications are not visible outside the function), while Python functions use reference semantics (functions receive a reference on their arguments and any modification of a mutable argument inside the function is visible outside). [35]
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 ...
One example is mutability: whether the objects storing extrinsic flyweight state can change. 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 ...
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 computing, a persistent data structure or not ephemeral data structure is a data structure that always preserves the previous version of itself when it is modified. Such data structures are effectively immutable, as their operations do not (visibly) update the structure in-place, but instead always yield a new updated structure.
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.)