# cancellation Published articles for cancellation. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Report: FuturLab lays off devs without informing team leads or managers DevFeed: [Report: FuturLab lays off devs without informing team leads or managers]() Original publisher: [Read original article]() Author: Chris Kerr Published: 2026-09-08T13:23:06Z Content type: news Language: en Sources: [gamedeveloper]() Topics: [Development]() Tags: [cancellation](), [company](), [developer](), [news](), [project](), [report](), [statement](), [work]() ### AI overview FuturLab laid off seven employees after cancelling a non-PowerWash-related project that had been in development for two to three years. Sources alleged that affected workers were left without assignments and that managers and team leads were not informed about the layoffs. The company later described the situation as part of a restructuring process. ### Source excerpt Sources have also accused the Powerwash Simulator developer of obfuscating the truth by asking staff to refer to those laid off as 'the leavers.' ## Coroutine Essentials DevFeed: [Coroutine Essentials]() Original publisher: [Read original article]() Author: author@typealias.com (Dave Leeds) Published: 2026-08-21T00:00:00Z Content type: tutorial Language: en Sources: [Dave Leeds on Kotlin - typealias.com]() Topics: [Coroutines](), [Kotlin](), [coding](), [Software]() Tags: [async](), [cancellation](), [coding](), [concurrency](), [coroutine](), [coroutines](), [deferred](), [dispatcher](), [exception-handling](), [introduction](), [job](), [kotlin](), [launch](), [learn-to-program](), [parallelism](), [programming](), [runblocking](), [software](), [structured-concurrency](), [suspend-function](), [withcontext](), [yield]() ### AI overview This tutorial introduces essential Kotlin coroutine concepts for performing multiple tasks concurrently, such as making network calls while updating a screen. It aims to provide a foundation for day-to-day coding and more advanced coroutine concepts. ### Source excerpt When you're on hold during a phone call, you might also check your email. While brewing coffee, you might also cook breakfast. And while driving a car, you might listen to a podcast. In the same way, sometimes it's helpful for the software that we write to do more than one thing at a time. For example, it could make two or three network calls at one time--all while updating the screen to show the progress of each call. ## Stripe Recurring Payments: How to Set Them Up in 2026 DevFeed: [Stripe Recurring Payments: How to Set Them Up in 2026]() Original publisher: [Read original article]() Author: Aarthi Poonia Published: 2026-06-26T00:00:00Z Content type: tutorial Language: en Sources: [Dodo Payments Blog]() Topics: [stripe](), [API](), [configuration]() Tags: [2026](), [billing](), [cancellation](), [checkout](), [customer](), [guide](), [how-to](), [lifecycle](), [merchant-of-record](), [payment](), [stripe](), [subscriptions](), [tax](), [webhooks]() ### AI overview A practical guide to Stripe recurring payments covering subscription setup, payment-method collection, billing lifecycles, failed payments and dunning, tax responsibility, and when a merchant of record may be a better fit. ### Source excerpt A practical 2026 guide to Stripe recurring payments: how to set up subscriptions, handle failed payments and dunning, manage tax, and when an MoR fits better. ## Subscription Payment Gateway: How to Pick One for Your SaaS DevFeed: [Subscription Payment Gateway: How to Pick One for Your SaaS]() Original publisher: [Read original article]() Author: Ayush Agarwal Published: 2026-06-09T00:00:00Z Content type: comparison Language: en Sources: [Dodo Payments Blog]() Topics: [Software as a service](), [stripe]() Tags: [buyers-guide](), [cancellation](), [features](), [geography](), [guide](), [merchant-of-record](), [payment-gateway](), [payments](), [retry](), [saas](), [set](), [stripe](), [subscription](), [subscriptions](), [webhooks]() ### AI overview A buyer's guide to subscription payment gateways for SaaS. It explains the minimum capabilities gateways need, including recurring charges, secure credential storage, retry logic, credential updates, and webhooks, then compares pure gateways, PSPs with native subscription billing, and merchant-of-record platforms. ### Source excerpt Subscription payment gateway buyers guide for SaaS founders. What features matter, how PSPs differ from MoRs, and how to evaluate by stage and geography. ## Kotlin Coroutines Cancellation and Exception Handling DevFeed: [Kotlin Coroutines Cancellation and Exception Handling]() Original publisher: [Read original article]() Published: 2026-01-11T00:00:00Z Content type: tutorial Language: en Sources: [Vasya Drobushkov]() Topics: [kotlin-coroutines](), [cancellation](), [Exception handling](), [Kotlin](), [Concurrency]() Tags: [cancellation](), [concurrency](), [coroutines](), [exception-handling](), [kotlin](), [kotlin-coroutines]() ### AI overview This article explains why cancellation and exception handling in Kotlin coroutines are difficult, emphasizing that the concepts are distinct but coupled. It discusses the flexibility and hidden complexity of the coroutine API and introduces explanations and best practices for learning and using these mechanisms. ### Source excerpt Cancellation and exception handling in coroutines is by far the most complex thing I've faced during my entire career. These two things are so complicated that I sometimes ask myself how people are using such a difficult-to-use framework. I read all the possible docs that I found, many different articles, video courses, and even tried to look at the code - and still, I feel that my understanding of this topic is quite bad. When reading articles, I often thought that their structure was not good and that things were not clarified in a reasonable way. Usually, articles are just a collection of examples that show how certain combinations of suspending functions or coroutine builders will work. Learning by examples is good, but they should help with understanding core concepts so that all other situations are easy to relate to what was learned. ## Temporal Ruby SDK Reaches General Availability with Rust Core and Deterministic Fiber Scheduler DevFeed: [Temporal Ruby SDK Reaches General Availability with Rust Core and Deterministic Fiber Scheduler]() Original publisher: [Read original article]() Author: Chad Retz Published: 2025-10-16T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Ruby](), [SDKs](), [Rust](), [Programming](), [cancellation](), [Code](), [Open Source]() Tags: [announcements](), [asynchronous](), [cancellation](), [fiber](), [guardrails](), [open-source](), [ruby](), [rust](), [scheduler](), [sdk](), [workflows]() ### AI overview Temporal Ruby is now generally available, providing Ruby developers with a native-feeling SDK for building durable software and Workflows. The article introduces its programming model and demonstrates Activities, deterministic fibers, durable timers, cancellation, and updates, while also discussing the Rust-powered implementation and execution guardrails. ### Source excerpt Temporal Ruby SDK is GA. Build durable Ruby Workflows with native APIs, a Rust-powered core, a deterministic fiber scheduler, and guardrails for safe execution. ## Kotlin Coroutines and Swift DevFeed: [Kotlin Coroutines and Swift]() Original publisher: [Read original article]() Published: 2025-09-15T00:00:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [kotlin-coroutines](), [Swift](), [Kotlin Multiplatform](), [Structured concurrency](), [async/await](), [kotlin-flow](), [kotlin-native](), [iOS]() Tags: [async](), [cancellation](), [coroutines](), [how-to](), [kotlin](), [kotlin-flow](), [kotlin-multiplatform](), [kotlin-native](), [structured-concurrency](), [swift](), [workshop-learning-programming]() ### AI overview This tutorial explains how to bridge Kotlin Coroutines and Swift's async/await and structured concurrency in Kotlin Multiplatform iOS projects. It covers suspending functions, exception conversion, Kotlin Flow to AsyncSequence, and calling Swift async functions from Kotlin. ### Source excerpt How to use Kotlin Coroutines in Swift projects, or Swift libraries from Kotlin Coroutines. ## How to turn callback functions into suspend functions or Flow DevFeed: [How to turn callback functions into suspend functions or Flow]() Original publisher: [Read original article]() Published: 2025-07-14T00:00:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [Kotlin](), [kotlin-coroutines](), [callback](), [functions](), [Continuation](), [API]() Tags: [callback](), [cancellation](), [continuation](), [coroutines](), [exceptions](), [functions](), [guide](), [how-to](), [interoperability](), [kotlin](), [kotlin-coroutines](), [suspend](), [workshop-learning-programming]() ### AI overview A guide to adapting callback-based APIs for Kotlin Coroutines. It explains how to convert callbacks that return one value into suspending functions and how to adapt callbacks that emit multiple values into Flows, including handling cancellation and exceptions. ### Source excerpt A guide on how to correctly convert callback-based functions into suspending functions or Flows in Kotlin Coroutines. ## Context Package Semantics In Go DevFeed: [Context Package Semantics In Go]() Original publisher: [Read original article]() Published: 2025-02-10T00:00:00Z Content type: tutorial Language: en Sources: [William Kennedy]() Topics: [Go Language](), [context](), [Programming](), [Software]() Tags: [api](), [ardan-labs](), [blog](), [cancellation](), [go](), [go-programming](), [golang](), [goroutines](), [latency](), [pitfalls](), [programming]() ### AI overview This tutorial explains the semantics of Go's Context package, including request-scoped data, deadlines, cancellation signals, and how to introduce contexts early when designing APIs. It also discusses managing goroutine lifetime and latency in services. ### Source excerpt Although first introduced in 2014, the Context package remains a crucial component of Go programming, enabling efficient management of request-scoped data, deadlines, and cancellation signals. As the Go ecosystem continues to evolve, understanding the Context package's semantics is vital for developing reliable and maintainable software. This blogpost provides an in-depth exploration of the Context package's semantics, highlighting best practices and common pitfalls to help developers effectively leverage this powerful tool. ## Job and children awaiting in Kotlin Coroutines DevFeed: [Job and children awaiting in Kotlin Coroutines]() Original publisher: [Read original article]() Published: 2024-07-15T00:00:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [Job](), [kotlin-coroutines](), [Structured concurrency](), [cancellation]() Tags: [cancellation](), [job](), [kotlin-coroutines](), [structured-concurrency](), [workshop-learning-programming]() ### AI overview This tutorial explains the Kotlin Coroutines Job context. It describes how each coroutine has its own Job, how parent-child Job relationships support structured concurrency, and how Jobs enable cancellation, completion waiting, and exception handling within a coroutine scope. ### Source excerpt What Job is and how it is the most important context responsible for structured concurrency. ## Key advantages of Kotlin Coroutines DevFeed: [Key advantages of Kotlin Coroutines]() Original publisher: [Read original article]() Published: 2024-06-10T00:00:00Z Content type: article Language: en Sources: [Kt. Academy]() Topics: [Coroutines](), [Kotlin](), [kotlin-coroutines](), [Structured concurrency](), [Concurrency](), [cancellation](), [Testing](), [async/await](), [Ktor](), [Back end](), [Android](), [WebSocket]() Tags: [cancellation](), [concurrency](), [coroutines](), [http](), [kotlin](), [kotlin-coroutines](), [ktor](), [structured-concurrency](), [testing](), [workshop-learning-programming]() ### AI overview This article explains the main advantages of Kotlin Coroutines: simpler imperative-style asynchronous code, structured concurrency, lighter execution than threads, cancellation, synchronization, and precise virtual-time testing. It discusses applications in Android and backend development, including Ktor. ### Source excerpt Where Kotlin Coroutines shine and why you should use them. ## Cancellation in Kotlin Coroutines DevFeed: [Cancellation in Kotlin Coroutines]() Original publisher: [Read original article]() Published: 2024-06-10T00:00:00Z Content type: tutorial Language: en Sources: [Kt. Academy]() Topics: [cancellation](), [Kotlin](), [kotlin-coroutines](), [Coroutines]() Tags: [android](), [application](), [backend](), [cancellation](), [coroutines](), [kotlin](), [kotlin-coroutines](), [thread](), [websockets](), [workshop-learning-programming]() ### AI overview A tutorial on cancellation in Kotlin Coroutines, explaining how cancellation propagates through coroutine hierarchies, changes coroutine state, raises cancellation exceptions at suspension points, and helps release resources in Android and backend applications. ### Source excerpt Everything you need to know about the cancellation mechanism in Kotlin Coroutines. ## Learn how to interact with Workflows with free hands-on training DevFeed: [Learn how to interact with Workflows with free hands-on training]() Original publisher: [Read original article]() Author: Angela Zhou Published: 2024-05-21T06:00:00Z Content type: tutorial Language: en Sources: [Temporal Blog]() Topics: [Learning](), [SDKs](), [Command-line interface](), [monitor]() Tags: [asynchronous](), [cancellation](), [command-line](), [courses](), [free](), [how-to](), [learn](), [sdks](), [training](), [web]() ### AI overview Temporal announces four free hands-on training courses about interacting with Workflows through specific SDKs. The courses cover Signals and Queries, Custom Search Attributes, Asynchronous Activity Completion, and Workflow cancellation. ### Source excerpt Explore four new hands-on training courses from Temporal to learn how to interact with workflows using different SDKs. Start learning today! ## Introducing Temporal .NET - deterministic Workflow authoring in .NET DevFeed: [Introducing Temporal .NET - deterministic Workflow authoring in .NET]() Original publisher: [Read original article]() Author: Chad Retz Published: 2023-12-05T13:00:00Z Content type: release Language: en Sources: [Temporal Blog]() Topics: [.NET](), [SDKs](), [C#](), [Development]() Tags: [c-sharp](), [cancellation](), [code](), [http](), [net](), [product-news](), [sdk]() ### AI overview Temporal introduces a .NET SDK for writing durable, reliable, and scalable workflows in .NET languages. The article provides a high-level overview of the SDK, discusses development challenges, and demonstrates a simplified C# workflow involving activities, cancellation, HTTP access, and durable timers. ### Source excerpt A high-level overview of Temporal's new .NET runtime, and some interesting challenges encountered during its development. ## Coroutines on Android DevFeed: [Coroutines on Android]() Original publisher: [Read original article]() Author: Stevan Milovanovic Published: 2022-05-20T12:36:23Z Content type: tutorial Language: en Sources: [Homegate Engineering Blog - Medium]() Topics: [Coroutines](), [Android](), [async](), [Concurrent Programming](), [context]() Tags: [android](), [android-app-development](), [android-apps](), [article](), [async](), [asynchronous](), [cancellation](), [coroutine](), [coroutine-testing](), [coroutines](), [dispatcher](), [kotlin-coroutines](), [lifecycle](), [programming](), [thread](), [threads]() ### AI overview This tutorial explains why Kotlin coroutines can be preferable to threads for asynchronous and background processing on Android. It introduces coroutine scopes, contexts, suspending functions, jobs, and dispatchers, and describes using coroutines for networking and background processing. ### Source excerpt Coroutines on Android In this article I'll try to explain why coroutines are useful and why would you want to use them in your project. After we go through the most important concepts of coroutines, I'll show you how I used coroutines to implement networking and background processing in the example project. First of all, you might ask yourself, why we want to use coroutines over threads? Main problem with threads is that they are resource intensive, meaning it takes a lot of resources to start a thread, stop a thread. Meanwhile, coroutines are lightweight threads, since they use thread pools. Another benefit of coroutines is that they greatly simplify asynchronous code. Callbacks and synchronisation are very easy to use. In fact, they make parallel programming look very much like sequential programming. Coroutines can be paused and resumed at any time, on a number of threads. And lastly, since coroutines are based on a few fairly easy to grasp concepts, their syntax is simple and easy to use. Here are the main concepts we need to explain about coroutines: Scope Coroutine scope, as its name says, defines a scope for new coroutines. Every coroutine builder (like launch and async) is an extension on CoroutineScope and inherits its coroutineContext to automatically propagate all its elements and cancellation. Context Coroutine context represents the context of its scope. Context is encapsulated by the scope and used for implementation of coroutine builders that are extensions on the scope. Scope provides a context in which the coroutine runs (state of the coroutine which provides variables, functionality of the coroutine etc.). Suspending functions Suspending functions are functions that can be run in a coroutine. They make callbacks seamless. They can be run in a coroutine (can be suspended) and that is why they can provide functionalities which have to be run in parallel. Job Job is a handle on that coroutine (on the piece of code which runs in the background). A laun ## Converting LiveData to Flow: More lessons learned DevFeed: [Converting LiveData to Flow: More lessons learned]() Original publisher: [Read original article]() Author: Chao Zhang Published: 2021-06-23T06:52:18Z Content type: tutorial Language: en Sources: [Stories by Chao Zhang on Medium]() Topics: [kotlin-coroutines](), [Kotlin](), [Android](), [test]() Tags: [android](), [android-app-development](), [androiddev](), [cancellation](), [coroutine](), [coroutines](), [flow](), [kotlin](), [kotlin-coroutines](), [livedata](), [sharedflow](), [stateflow](), [unit-tests]() ### AI overview This continuation explains lessons from converting between Kotlin Flow and LiveData in Android. It covers unfinished hot-flow coroutines during unit tests, why asLiveData cancellation occurs after a timeout on Dispatchers.Main, and how values are replayed when LiveData becomes active again. ### Source excerpt Photo: Buzz Andersen from Unsplash Android KTX provides opinionated methods facilitating using Kotlin Coroutines in Android Architecture Components. For instance, Flow.asLiveData() is quite helpful to migrate your apps using LiveData towards coroutine. Make sure to understand their behaviors underneath before using them! This story is a continuation of the previous one. Lesson III: Unfinished coroutines during unit testshttps://medium.com/media/41979239402051494c1002bb4d9e57dc/href When converting from Flow to LiveData, the source stream might be a hot StateFlow like above. Running the test will actually end up with the following error: kotlinx.coroutines.test.UncompletedCoroutinesError: Unfinished coroutines during teardown. Ensure all coroutines are completed or cancelled by your test. We know a hot Flow like SharedFlow never completes, so this error appears reasonable. A common way to test hot flow is to cancel the coroutine that the hot flow is executed on. In this case, we may want to pass a custom coroutineContext to asLiveData(context = ...)and cancel the job when the assertions are done: https://medium.com/media/129968c37bf50ac019a25755e3c56411/href However, it does not work! Let's take a step back and consult the documentation of Flow.asLiveData : If the LiveData becomes inactive (LiveData.onInactive) while the flow has not completed, the flow collection will be cancelled after timeoutInMs milliseconds unless the LiveData becomes active again before that timeout (to gracefully handle cases like Activity rotation). Since we are converting a hot flow to LiveData, we will always meet the condition. The flow collection will be canceled after timeoutInMs (default is 5 seconds). After digging it a bit more into the source code, we find that the cancellation is implemented as a delay() call on Dispatchers.Main : https://medium.com/media/154954407331c372f002028c8353a843/href The reason why cancel()runs on Dispatchers.Main is because it is invoked byLiveData.onI ## Coroutine Cancellation 101 DevFeed: [Coroutine Cancellation 101]() Original publisher: [Read original article]() Author: Márton Braun Published: 2020-03-04T19:00:00Z Content type: tutorial Language: en Sources: [zsmb.co]() Topics: [Coroutines](), [Code]() Tags: [android](), [blocking](), [cancellation](), [coroutine](), [coroutines](), [execution](), [function](), [kotlin](), [lambda](), [marton-braun](), [run](), [running](), [time](), [zsmb](), [zsmb-co](), [zsmb13](), [zsmbco]() ### AI overview A tutorial on coroutine cancellation explains coroutine builders, asynchronous execution, cancellable lifecycle tracking, and cooperative cancellation. It shows why cancellation does not work during continuously blocking code and why forcibly stopping such code can be dangerous. ### Source excerpt A brief introduction to the basics of coroutine cancellation. ## Retrofit meets coroutines DevFeed: [Retrofit meets coroutines]() Original publisher: [Read original article]() Author: Márton Braun Published: 2019-02-15T22:00:00Z Content type: tutorial Language: en Sources: [zsmb.co]() Topics: [Coroutines](), [kotlin-coroutines](), [REST API](), [API]() Tags: [android](), [cancellation](), [coroutines](), [demo](), [exception](), [gson](), [implementation](), [kotlin](), [kotlin-coroutines](), [marton-braun](), [networking](), [rest-api](), [retrofit](), [serialization](), [zsmb](), [zsmb-co](), [zsmb13](), [zsmbco]() ### AI overview This tutorial explains how to use Retrofit 2.6.0 or later with Kotlin coroutines. It demonstrates coroutine-based API calls, Gson serialization, exception propagation, cancellation, and response-handling variants using the SpaceX REST API. ### Source excerpt Retrofit's coroutine support has been a long time coming, and it's finally coming to completion. Take a look at how you can use it to neatly integrate networking into an application built with coroutines. ## Java 9 Flow API: Multicasting via a Processor DevFeed: [Java 9 Flow API: Multicasting via a Processor]() Original publisher: [Read original article]() Author: David Karnok (noreply@blogger.com) Published: 2017-12-14T13:20:00Z Content type: tutorial Language: en Sources: [Akarnokd - Advanced RxJava]() Topics: [Java](), [Java 9](), [reactive](), [Streams](), [implementation](), [API]() Tags: [backpressure](), [cancellation](), [concurrency](), [flow](), [flow-api](), [java](), [java-9](), [jdk](), [multicast](), [processor](), [reactive](), [reactive-streams](), [streams](), [subscriber](), [subscription](), [tck]() ### AI overview This tutorial explains how Java 9 Flow API processors can multicast elements from a single upstream source to multiple consumers. It focuses on coordinating subscriber demand, backpressure, dynamic subscription, and cancellation, and introduces MulticastProcessor as the intermediate solution. ### Source excerpt Introduction There are situations when the same elements of a source should be dispatched to multiple consumers. Certainly, if the source supports multiple subscribers and is deterministic (such as our previous async range), one can just instantiate the flow multiple times. However, if the source doesn't support multiple subscribers or each subscription ends up being unique and/or non-deterministic, that simple approach doesn't work anymore. We need a way to have a single realization of the (upstream) source yet allow multiple consumers. Since we are dealing with Flow.Publishers that require backpressure management, such intermediate solution has to coordinate requests from its Flow.Subscribers in addition to handling the dynamic subscription and unsubscription (cancellation) of said Flow.Subscribers while the flow is active. Enter, MulticastProcessor. Flow.Processor recap What is a Processor? By definition, it is a combination of a Flow.Publisher and a Flow.Subscriber, i.e., it can act as a source and can be subscribed to via subscribe() as well as the processor itself can be used with somebody else's Flow.Publisher.subscribe(). It has a mixed history as the idea comes from the original Observer pattern (i.e., java.util.Observable) and Rx.NET's Subject that allows dispatching signals to multiple Observers in an imperative (and synchronous) fashion. The Flow.Processor in Java 9 defines two type arguments, one for its input side (Flow.Subscriber) and one for its output side (Flow.Publisher). The idea behind it was that a Flow.Processor can act as a transformation step between an upstream and a downstream. However, such transformation often mandates the Flow.Processor implementation only accepts a single Flow.Subscriber during its entire lifetime. Since the implementation has to follow the Reactive Streams specification nonetheless, this adds a lot of overhead to the flow. As demonstrated in previous posts, when a flow is realized, there are only one subscriber per st ## Android LiveData API: a quick look DevFeed: [Android LiveData API: a quick look]() Original publisher: [Read original article]() Author: David Karnok (noreply@blogger.com) Published: 2017-10-19T13:45:00Z Content type: tutorial Language: en Sources: [Akarnokd - Advanced RxJava]() Topics: [Android](), [API](), [reactive](), [Library](), [Streams]() Tags: [android](), [api](), [backpressure](), [cancellation](), [concurrency](), [flow](), [flowable](), [google](), [lifecycle](), [lifecycle-components](), [livedata](), [reactive](), [release](), [rxjava](), [subscription](), [thread](), [threading](), [ui]() ### AI overview This article provides a quick technical overview of Android LiveData, explaining its main-thread requirements, lifecycle-aware observer behavior, observer removal, and interoperability with Reactive Streams. It notes that LiveData was considered beta and could change before release. ### Source excerpt Introduction Threading and lifecycle are one of the top concerns when developing applications for the Android platform. UI has to be interacted with on a dedicated thread (main thread) but in order to keep the UI responsible to user input and rendering, blocking or CPU intensive calculations should be kept off it. In addition, views can get destroyed and recreated in a way that is outside of a given application's control unlike a desktop Swing application. This means background tasks must be stopped and listeners removed to prevent leaking references to now logically dead objects. RxJava and RxAndroid can help with threading concerns and there are other libraries that tap into the various lifecycle events; in general, this means someone will call dispose() on a particular flow or clear() on a CompositeDisposable to mass-cancel multiples of them. Having a rich set of transformative and coordinating operators along with support for normal values, errors and finite sequences may be overwhelming compared to a classical Listener-based API. Google's LiveData is one of such classical Listener style APIs but unlike Swing's ActionListener for example, there are explicit requirements that interaction with the LiveData object itself happens on the main thread and signals will be dispatched from the main thread to Observers to it. LiveData API Unfortunately, I wasn't able to locate a public repository for the LiveData sources and had to rely on the sources downloaded from Google's Maven repository: compile "android.arch.lifecycle:reactivestreams:1+" There is an interoperation library associated with LiveData that allows presenting and consuming events from any Reactive-Streams Publisher. This will transitively import the actual LiveData library. Note that LiveData is currently considered beta and may change arbitrarily before release. That said, I don't think the core structure and premise will actually change. The main consumer type is the android.arch.lifecycle.Observer with ## Rewriting RxJava with Kotlin Coroutines? DevFeed: [Rewriting RxJava with Kotlin Coroutines?]() Original publisher: [Read original article]() Author: David Karnok (noreply@blogger.com) Published: 2017-09-09T15:16:00Z Content type: opinion Language: en Sources: [Akarnokd - Advanced RxJava]() Topics: [Coroutines](), [Kotlin](), [kotlin-coroutines](), [reactive](), [Streams]() Tags: [callback](), [cancellation](), [coroutine](), [coroutines](), [kotlin](), [kotlin-coroutines](), [library](), [reactive](), [reactive-streams](), [rxjava](), [scrabble]() ### AI overview The article explores whether a declarative-reactive library can be implemented with Kotlin coroutines as an alternative to RxJava. It examines coroutine abstractions, operator design, cancellation, lazy versus eager execution, and the potential trade-offs for library developers and users. ### Source excerpt Introduction Someone influential stated that RxJava should be rewritten with Kotlin Coroutines. I haven't seen any attempt of it as of now and declaring such a thing to be (not) worth without actually trying is irresponsive. As we saw in the earlier post and the response in the comment section, following up on the imperative-reactive promise leads to some boilerplate and questionable cancellation management, and the idiomatic Kotlin/Coroutine enhancement suggested is to ... factor out the imperative control structures into common routines and have the user specify lambda callback(s); thus it can become declarative-reactive, just like RxJava interpreted from a higher level viewpoint. Kind of defeats one of the premises in my understanding. This doesn't diminish the power of coroutine-based abstraction but certainly implies a relevant question: who is supposed to write these abstract operators? One possible answer is, of course, library writers who not only have experience with abstracting away control structures but perhaps wield deeper knowledge about how the coroutine infrastructure can be utilized in certain complicated situations. If this assumption of mine is true, that somewhat defeats another premise of coroutines: the end user will likely have to stick to writing suspendable functionals and discover operators provided by a library most of the time. So what's mainly left is to see if implementing a declarative-reactive library on top of coroutines gives benefits to the library developer (i.e., ease of writing) over hand crafted state-machines and (reasonable) performance to the user of the library itself. The library implementation Perhaps one of the more attractive properties of RxJava is the deferred lazy execution of a reactive flow (cold). One sets up a template of transformations and issues a subscribe() call to begin execution. In contrast, CompletableFuture and imperative Coroutines can be thought as eager executions - in order to retry them one has to ## Implementing Non-Renewable Subscriptions with In-App Purchase DevFeed: [Implementing Non-Renewable Subscriptions with In-App Purchase]() Original publisher: [Read original article]() Author: Steve Hannah Published: 2016-12-19T00:00:00Z Content type: tutorial Language: en Sources: [CodeName One]() Topics: [App](), [API](), [Server](), [Android](), [iOS]() Tags: [android](), [api](), [app](), [app-store](), [apple](), [cancellation](), [code](), [component](), [data](), [devices](), [ios](), [management](), [series](), [server](), [subscriptions]() ### AI overview This tutorial explains how Codename One handles non-renewable and auto-renewable subscriptions through in-app purchases. It introduces the Receipts API, explains the need for a server-side receipt store, and describes receipt synchronization and subscription-status checks. ### Source excerpt __ This is the second post in a three-part series on In-App purchase. Please check out Part I: Introduction to In-App Purchase and Part 3: Auto-renewing Subscriptions in iOS and Android. In my last post we looked at one-off in-app purchases. In this post we'll look at subscriptions. As we discussed before, there are two types of subscriptions: Non-renewable Auto-renewable Non-renewable subscriptions are really the same as consumable products, except that they are shareable across all of a user's devices. Auto-renewable subscriptions, on the other hand, will continue as long as the user doesn't cancel it. They will be re-billed automatically by the appropriate app-store when the chosen period expires, and all management of the subscription is handled by the app-store itself. ## SubscribeOn and ObserveOn DevFeed: [SubscribeOn and ObserveOn]() Original publisher: [Read original article]() Author: David Karnok (noreply@blogger.com) Published: 2016-03-31T12:55:00Z Content type: tutorial Language: en Sources: [Akarnokd - Advanced RxJava]() Topics: [Programming](), [reactive](), [User Experience](), [Android](), [GUI]() Tags: [backpressure](), [blocking](), [cancellation](), [executorservice](), [main-thread](), [observeon](), [reactive](), [rxjava](), [subscribeon](), [thread]() ### AI overview A tutorial explaining why RxJava's subscribeOn and observeOn operators are often confused. It distinguishes their effects by tracing subscription and method-call flow, and discusses moving subscription side effects such as network, database, or blocking work away from the current thread. ### Source excerpt Introduction One of the most confused operator pair of the reactive ecosystem is the subscribeOn and observeOn operators. The source of confusion may be rooted in a few causes: they sound alike, they sometimes show similar behavior when looked at from downstream and they are duals in some sense. It appears the name-confusion isn't local to RxJava. Project Reactor faces a similar issue with their publishOn and dispatchOn operators. Apparently, it doesn't matter what they are called and people will confuse them anyhow. When I started learning about Rx.NET back in 2010, I never experienced this confusion; subscribeOn affects subscribe() and observeOn affects onXXX(). (Remark: I've searched Channel 9 for the early videos but couldn't really find the talk where they build up these operators just like I'm about to do. The closest thing was this.) My "thesis" is that the confusion may be resolved by walking through how one can implement these operators and thus showing the internal method-call flow. SubscribeOn The purpose of subscribeOn() is to make sure side-effects from calling subscribe() happens on some other thread. However, almost no standard RxJava source does side-effects on its own; you can have side-effects with custom Observables, wrapped subscription-actions via create() or as of lately, the with the SyncOnSubscribe and fromCallable() APIs. Why would one move the side-effects? The main use cases are doing network calls or database access on the current thread or anything that involves blocking wait. Holding off a Tomcat worker thread hasn't been much of a programming problem (that doesn't mean we can't improve the stack with reactive) but holding off the Event Dispatch Thread in a Swing application or the Main thread in an Android application has adverse effect on the user experience. (Sidenote: it's a funny thing that blocking the EDT is basically a convenience backpressure strategy in the GUI world to prevent the user from changing the application state whil ## Building advanced MVVM commands, Part 1 DevFeed: [Building advanced MVVM commands, Part 1]() Original publisher: [Read original article]() Author: Andrew Khmylov Published: 2010-11-24T00:00:00Z Content type: tutorial Language: en Sources: [Despite the odds]() Topics: [MVVM](), [WPF](), [async](), [cancellation](), [Exception](), [Code]() Tags: [applications](), [async](), [asynchronous](), [cancellation](), [exception-handling](), [mvvm](), [thread](), [ui]() ### AI overview This tutorial presents an advanced DelegateCommand implementation for WPF and Silverlight applications using the MVVM pattern. It covers asynchronous execution, command states, cancellation, progress tracking, exception handling, UI updates through Dispatcher, and helper support for property-change notifications. ### Source excerpt If you follow the MVVM pattern while developing your WPF/Silverlight applications, then you are probably familiar with DelegateCommand (or RelayCommand, as it is called sometimes) model. In brief: it is an implementation of WPF/Silverlight ICommand that allows you to specify what the command should do by passing some delegate that performs execution logic (instead of using CommandBindings). Pretty simple, but powerful pattern. Dealing with MVVM a lot, I've build my own implementation of this pattern that lets you simplify its usage. Here are some common features, that you have to handle on your own by using classic DelegateCommand: Support for asynchronous execution (usually solved by generating additional code in ViewModel that handles async calls and free/busy indicator). Different command states (Free/Busy/Failed with exception) + UI reactions for those states. Support for execution cancellation and progress tracking (required for asynchronous commands) Before we start, I offer you to imagine a common command execution timeline. In my opinion it looks like: Initialize some data (generally, UI settings - clear collections, set some indicators,...) Perform main execution logic (can be synchronous or asynchronous) Perform some actions after execution (update UI based on execution result) And don't forget about exception handling and correct cross-thread calls for asynchronous commands (all UI changes have to be performed through Dispatcher). Let's start with a little helper class, that I called PropertyChangedNotifier. It's just a wrapper around IPropertyChangedNotifier that has OnPropertyChanged(string propertyName) method. This method raises underlying IPropertyChangedNotifier.PropertyChanged event. Also this class has VerifyPropertyName method that verifies if specified string corresponds to the actual property (this method is marked with [Conditional("DEBUG")] attribute and is only used while debugging your applications to find out possible bugs with invalid prope