Reactive programming is a programming paradigm that focuses on constructing responsive and robust software applications that can handle asynchronous data streams and change propagation. This paradigm enables developers to create scalable and more easily maintainable applications that can adapt to a dynamic environment[4].
In reactive programming, the core concept revolves around data streams, which are time-ordered sequences of events. These streams can begin with an observer, such as a section of code within an application that monitors for conditions, or a device like an IoT sensor that generates events. The streams flow through various handlers that process the events and can branch into derivative streams as necessary[1].
The fundamental principles of reactive programming include responsiveness, resilience, elasticity, and message-driven architecture. Responsiveness refers to the system's ability to respond in a timely manner, which is crucial for user experience and system functionality. Resilience is the system's ability to stay responsive even in the face of failure, which is achieved through strategies like replication and isolation. Elasticity allows the system to handle varying workloads by scaling resources up or down as needed. Finally, a message-driven architecture underpins scalable, resilient, and responsive systems by enabling components to communicate through asynchronous message passing[2][5].
Reactive programming uses declarative code to create asynchronous processing pipelines, which can efficiently handle real-time adjustments to data. This approach is particularly useful in modern applications that require quick and dynamic responses to events, such as user interactions, sensor outputs, or messages from other systems[1][3].
Several libraries and frameworks facilitate reactive programming across different programming languages, including RxJS for JavaScript, RxJava f...
