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In computing, reactive programming is a declarative programming paradigm concerned with data streams and the propagation of change. With this paradigm, it is possible to express static (e.g., arrays) or dynamic (e.g., event emitters) data streams with ease, and also communicate that an inferred dependency within the associated execution model exists, which facilitates the automatic propagation ...
In 2007, F# added asynchronous workflows with version 2.0. [14] The asynchronous workflows are implemented as CE (computation expressions). They can be defined without specifying any special context (like async in C#). F# asynchronous workflows append a bang (!) to keywords to start asynchronous tasks. The following async function downloads ...
C#, since .NET Framework 4.5, [22] via the keywords async and await [23] Kotlin, however kotlin.native.concurrent.Future is only usually used when writing Kotlin that is intended to run natively [35] Nim; Oxygene; Oz version 3 [36] Python concurrent.futures, since 3.2, [37] as proposed by the PEP 3148, and Python 3.5 added async and await [38]
ReactiveX (Rx, also known as Reactive Extensions) is a software library originally created by Microsoft that allows imperative programming languages to operate on sequences of data regardless of whether the data is synchronous or asynchronous. It provides a set of sequence operators that operate on each item in the sequence.
Python — uses thread-based parallelism and process-based parallelism [17] Raku includes classes for threads, promises and channels by default [18] Reia—uses asynchronous message passing between shared-nothing objects; Red/System—for system programming, based on Rebol
Asynchrony, in computer programming, refers to the occurrence of events independent of the main program flow and ways to deal with such events. These may be "outside" events such as the arrival of signals, or actions instigated by a program that take place concurrently with program execution, without the program hanging to wait for results. [1]
Flow-based programming defines applications using the metaphor of a "data factory". It views an application not as a single, sequential process, which starts at a point in time, and then does one thing at a time until it is finished, but as a network of asynchronous processes communicating by means of streams of structured data chunks, called "information packets" (IPs).
Metaprogramming – writing programs that write or manipulate other programs (or themselves) as their data, or that do part of the work at compile time that would otherwise be done at runtime Template metaprogramming – metaprogramming methods in which a compiler uses templates to generate temporary source code, which is merged by the compiler ...