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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]
The syntax of JavaScript is the set of rules that define a correctly structured JavaScript program. The examples below make use of the log function of the console object present in most browsers for standard text output .
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.
The immutable keyword denotes data that cannot be modified through any reference. The const keyword denotes a non-mutable view of mutable data. Unlike C++ const, D const and immutable are "deep" or transitive, and anything reachable through a const or immutable object is const or immutable respectively. Example of const vs. immutable in D
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]
This JavaScript example implementation provides the toJSON method used by the JSON.stringify() [9] function to serialize the class into a simple string instead of a composite data type. It calls Object.freeze() to make the instance immutable. [10] It overrides the built-in toString() method [11] and the valueOf() method. [12]
Turkey Cheese Ball. Even if you're not serving turkey this Thanksgiving doesn't mean you can't get in on the theme. Enter: this adorable cheeseball.We used carrots, pecans, pretzels, and bell ...
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 ...