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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 ...
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:
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.
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] R (promises for lazy evaluation, still single threaded) Racket [39] Raku [40]
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]
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.
Rule-based programming – a network of rules of thumb that comprise a knowledge base and can be used for expert systems and problem deduction & resolution; Visual programming – manipulating program elements graphically rather than by specifying them textually (e.g. Simulink); also termed diagrammatic programming [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).