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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.
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 ...
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]
F# added asynchronous workflows with await points in version 2.0 in 2007. [5] This influenced the async/await mechanism added to C#. [6] Microsoft first released a version of C# with async/await in the Async CTP (2011). It was later officially released in C# 5 (2012). [7] [1]: 10 Haskell lead developer Simon Marlow created the async package in ...
By way of illustration, the following code fragments demonstrate detection of patterns within event streams. The first is an example of processing a data stream using a continuous SQL query (a query that executes forever processing arriving data based on timestamps and window duration).
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
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).
The original formulation of functional reactive programming can be found in the ICFP 97 paper Functional Reactive Animation by Conal Elliott and Paul Hudak. [1] FRP has taken many forms since its introduction in 1997. One axis of diversity is discrete vs. continuous semantics. Another axis is how FRP systems can be changed dynamically. [2]