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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 ...
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.
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]
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 data from an URL using an asynchronous workflow:
Asynchronous message passing may be reliable or unreliable (sometimes referred to as "send and pray"). Message-passing concurrency tends to be far easier to reason about than shared-memory concurrency, and is typically considered a more robust form of concurrent programming.
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).
A synchronous programming language is a computer programming language optimized for programming reactive systems. Computer systems can be sorted in three main classes: Transformational systems take some inputs, process them, deliver their outputs, and terminate their execution. A typical example is a compiler.
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 ...