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In object-oriented (OO) and functional programming, an immutable object (unchangeable [1] object) is an object whose state cannot be modified after it is created. [2] This is in contrast to a mutable object (changeable object), which can be modified after it is created. [ 3 ]
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.
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.
Similarly, the idea of immutable data from functional programming is often included in imperative programming languages, [108] for example the tuple in Python, which is an immutable array, and Object.freeze() in JavaScript. [109]
Objects can contain other objects in their instance variables; this is known as object composition. For example, an object in the Employee class might contain (either directly or through a pointer) an object in the Address class, in addition to its own instance variables like "first_name" and "position".
In a purely functional language, the only dependencies between computations are data dependencies, and computations are deterministic. Therefore, to program in parallel, the programmer need only specify the pieces that should be computed in parallel, and the runtime can handle all other details such as distributing tasks to processors, managing synchronization and communication, and collecting ...
Python supports most object oriented programming (OOP) techniques. It allows polymorphism, not only within a class hierarchy but also by duck typing. Any object can be used for any type, and it will work so long as it has the proper methods and attributes. And everything in Python is an object, including classes, functions, numbers and modules.