Observable Patterns

In this section

• AsyncSubject: Reactive Programming Pattern in Clojure
  The AsyncSubject design pattern in reactive programming is an abstraction over Observables, which allows it to emit only the last item of a sequence upon completion. This pattern is used often in scenarios where you want to ensure that only the final state is consumed after a series of asynchronous tasks have completed.
• BehaviorSubject: Emits the Most Recent Item to New Subscribers
  BehaviorSubject is a design pattern used in reactive programming that keeps track of the most recent item emitted by an observable and emits it to any new subscribers.
• CatchObservable: Handles Errors with Fallback Observables
  The CatchObservable design pattern provides a way to gracefully handle errors in reactive streams by substituting a fallback observable when an error occurs, ensuring the continued flow of data.
• Cold Observable: Reactive Programming Pattern
  Cold Observables are a type of observable in reactive programming that start emitting items only when an observer subscribes. This pattern is crucial in implementing lazy data streams which cater to individual subscribers independently.
• CombineLatestObservable: Combining the Latest Items from Multiple Observables
  CombineLatestObservable is a design pattern in reactive programming that allows for the combination of the latest items from multiple observables to create complex data streams. In this pattern, whenever any of the source observables emit a new item, the combineLatest operator combines each of the most recently emitted items from all observables into a new item and emits this to the subscribers.
• Completable: Represents a Deferred Computation Without Emitting Items
  The Completable design pattern is a specialized pattern in reactive programming that represents a deferred computation but is distinctively different in that it does not emit items. Instead, it signifies a computation that completes or fails.
• ConcatObservable: Sequentially Concatenates Observables
  The ConcatObservable pattern is a way to sequentially concatenate multiple observables, allowing them to execute in a well-defined order. This pattern is particularly useful in scenarios where operations must be performed one after the other, maintaining their sequential integrity.
• ConditionalObservable: Emits items based on specified conditions
  The ConditionalObservable pattern in Reactive Programming is a design pattern that allows for the emission of items from an observable source only when certain conditions are met. It provides a mechanism to filter and control data flow in reactive systems, allowing for efficient and condition-based event processing.
• ConnectableObservable: Shared Subscription in Reactive Programming
  ConnectableObservable is a design pattern in reactive programming that enables sharing a single subscription among multiple subscribers, akin to multicasting signals to various observers in a reactive stream.
• DeferredObservable: Creating Observable on Subscription
  The DeferredObservable pattern in Reactive Programming: creating observables at subscription time, ensuring observers receive fresh data.
• DistinctObservable: Filtering Out Duplicates in Reactive Streams
  The DistinctObservable pattern focuses on filtering out duplicate items in reactive streams, ensuring each item is unique before processing.
• Flowable: Managing Backpressure in Reactive Streams
  The Flowable design pattern supports backpressure, suitable for managing streams with varying demand in a reactive programming environment.
• ForkJoinObservable: Synchronizing Multiple Observables for Reactive Completion
  The ForkJoinObservable pattern synchronizes multiple observables, waiting for all to complete before emitting a final item, facilitating the handling of concurrent operations within reactive programming paradigms.
• Hot Observable: Eager Emission in Reactive Streams
  The Hot Observable pattern in functional reactive programming where an observable emits items regardless of current subscriptions.
• IntervalObservable: Emits items at specified intervals
  The IntervalObservable design pattern in reactive programming emits sequential items at specified intervals. It is essential for operations that rely on time-based events, providing a structured, non-blocking way to generate sequences for further processing.
• Maybe: Reactive Programming Pattern
  The Maybe pattern in reactive programming handles operations that may emit zero or one item and then completes, efficiently managing optional data interactions.
• MergeObservable: Merging Multiple Observables into One
  The MergeObservable pattern combines multiple observables into a single observable stream, facilitating the seamless integration of event streams in reactive programming.
• Observable: A Data Structure Emitting Sequence of Items Over Time
  Observable is a design pattern used in reactive programming to model data that changes over time. It emits a stream of events, allowing for asynchronous processing and functional handling of dynamic data streams.
• Observer: A Pattern That Reacts to Changes in the Observable
  The Observer design pattern is a behavioral pattern that defines a one-to-many dependency between objects so that when one object changes state, all its dependents are notified and updated automatically. This pattern is especially useful in applications where state changes need to be propagated to multiple objects, such as UI components reacting to data changes.
• ReplaySubject: Reactive Programming Design Pattern
  The ReplaySubject design pattern in Clojure replays emitted items to new subscribers, allowing them to receive previous values even after subscription has occurred.
• RetryObservable: Re-subscribing to Observables upon Error
  The RetryObservable pattern involves re-subscribing to an observable after it encounters an error, enhancing robustness in reactive programming.
• Single Design Pattern: Emits a Single Item or an Error
  The Single design pattern is fundamental in the world of reactive programming. It represents an operation that asynchronously produces a single value or an error. Unlike the Stream or Observer patterns, which represent sequences of values, the Single pattern simplifies the control flow by focusing on one-time events.
• StartWithObservable: Precedes Emissions with Specified Items
  The StartWithObservable pattern in reactive programming allows us to prepend a sequence of specified items to an existing observable stream, ensuring initial data is provided before existing emissions.
• Subject: Acts as Both an Observer and an Observable
  The Subject pattern serves as a dual-role design structure wherein a component functions concurrently as an observer and an observable, enabling it to propagate received changes to its own observers.
• Subscription: A Mechanism to Connect Observers to Observables
  The Subscription pattern is an integral part of reactive programming, allowing observers to subscribe to observables to react and respond to emitted data. This pattern facilitates a decoupled mechanism for distributing events or data across a system.
• SwitchableObservable: Switching Between Observables Based on Conditions
  The SwitchableObservable is a design pattern that focuses on switching between different observables based on dynamic conditions. This pattern is highly useful in reactive programming, especially when dealing with streams of data that need to change sources dynamically.
• TakeUntilObservable: Observable Pattern for Controlled Completion
  TakeUntilObservable is a design pattern used in reactive programming where the emission of items from a source observable is controlled and stopped by another observable. This pattern is particularly useful for implementing scenarios that require conditional completion of data streams.
• ThrottleFirstObservable: Emit First Item in a Timespan
  The ThrottleFirstObservable pattern allows developers to emit the first item emitted by an observable within a specified duration, suppressing subsequent items until the time window elapses.
• ThrottleLastObservable: Emit the Last Item in a Specified Timespan
  The ThrottleLastObservable pattern emits the last item of an observable sequence within a specified timespan, offering a way to limit the emissions of events based on time intervals.
• ThrottleTimeObservable: Rate Limiting in Reactive Streams
  ThrottleTimeObservable is a design pattern used in reactive programming to limit the rate of emissions from an observable source. By specifying a time window, this pattern helps manage the flow of events, reducing the risk of overwhelming subscribers with a burst of data.
• TimerObservable: Emits a Single Item After a Specified Delay
  The TimerObservable design pattern emits a single item after a specified delay, often used in reactive programming environments to manage timing operations and delayed actions.
• ZipObservable: Combining Multiple Observables
  The ZipObservable pattern combines items emitted by multiple observables into single observable pairs, applying a specified function.