Reactive programming
Reactive programming is a programming paradigm in which computations and outputs respond to asynchronous events or changing data by propagating changes through dependent operations.
Functional Programming in JavaScript
A programming paradigm centered on data flows and propagation of change, especially for responding to asynchronous or event-driven updates.
- How it is used
- Unifies asynchronous and event-based data providers into observable streams that can be transformed and subscribed to.
- How deep it goes
- Explains observable streams and pipelines with map, filter, subscription, errors, completion, and asynchronous flattening without detailing implementation internals.
- Examples
- Uses number ranges, generated squares, SSN input validation, and filtering U.S. students returned from a JSON request.
- What you can do after
- Apply it via RxJS to transform event, promise, collection, and service-call values through observable pipelines.
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Quarkus in Action
Reactive programming is a programming paradigm centered on asynchronous data streams and the propagation of changes over time.
- How it is used
- Uses asynchronous, nonblocking execution to keep I/O-heavy Quarkus applications responsive under load.
- How deep it goes
- Explains continuations and event-loop request handling, then connects them to reactive database access and pipeline types.
- Examples
- Contrasts blocking and nonblocking I/O handling and uses Hibernate Reactive database access to illustrate asynchronous results.
- What you can do after
- Apply it via Quarkus and SmallRye Mutiny to build nonblocking pipelines while keeping blocking work off event-loop threads.
Spring in Action, Sixth Edition
Reactive programming is a programming approach based on asynchronous processing of data streams and the propagation of change over time.
- How it is used
- Frames data processing as a pipeline and provides context for Project Reactor and Spring WebFlux.
- How deep it goes
- Explains the imperative contrast and introduces pipelines, Mono, Flux, and basic operations without detailing execution internals.
- Examples
- Uses newspaper delivery and two Java greeting implementations to contrast batch-like steps with a Reactor pipeline.
- What you can do after
- Apply it via Project Reactor to express a simple transformation as a Mono pipeline.
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Modern Angular
Reactive programming is a programming technique that expresses computation in terms of asynchronous data streams and the propagation of changes.
- How it is used
- Frames Angular frontend behavior as state changes propagated from asynchronous events into rendered UI.
- How deep it goes
- Defines state, UI, events, and pull-versus-event-driven behavior, then points toward RxJS without detailing operator internals.
- Examples
- Uses a counter component, a synchronous data pull, and a click-event listener to contrast state-driven and event-driven behavior.
- What you can do after
- Apply reactive programming in Angular with RxJS, including observable cleanup and dependency-aware custom operators.
Spring Security in Action, Second Edition
Reactive programming is a programming paradigm based on asynchronous processing of streams of data and events, typically to support nonblocking and concurrent execution.
- How it is used
- Supports Spring Security application development when asynchronous, fragmented processing changes how authentication and authorization operate.
- How deep it goes
- Defines incremental processing and demonstrates a Mono endpoint, while deferring detailed reactive application study.
- Examples
- Uses incremental file uploads, a milk-factory analogy, a Mono-based HelloController, and publisher-subscriber streams.
- What you can do after
- Build a simple Spring WebFlux endpoint and recognize when reactive processing may improve delivery of fragmented results.
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Functional Design and Architecture: Examples in Haskell
Reactive programming is a programming technique for expressing computations that respond to continuously arriving events or changing data.
- How it is used
- Organizes formulas and stateful applications around continuously arriving data and changing environmental conditions.
- How deep it goes
- Defines the motivating principle and surveys actors, streams, event models, protocols, MVars, STM, and message queues without detailed implementation.
- Examples
- Uses spacecraft motion, fuel, and interconnected-system formulas as the central domain example.
- What you can do after
- Evaluate reactive designs by comparing actors, streams, event models, MVars, STM, and message queues.
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Related concepts
- imperative programmingalternative to · Imperative programming is a programming paradigm that expresses computation as an ordered sequence of instructions specifying operations, control flow, or changes to state.
- imperative approachcontrasts with · An imperative approach processes a bulk of available data as a whole rather than incrementally as data arrives.
- Project Reactorused by · Project Reactor is a JVM reactive programming library providing asynchronous, nonblocking types and operators for composing data sequences with backpressure.
- Quarkus platformused by · Quarkus is a Java framework for building cloud-native applications, optimized for containerized environments, fast startup, and low memory use.
- signalhas part · A signal is an observable value, event, or pattern that conveys information about a condition, state, or phenomenon.
- push modeluses · A push model is a communication pattern in which a producer or system proactively sends data, work, or updates to recipients rather than waiting for each to request them.
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