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Reactive state container for Android & Kotlin
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Concise reactive state container library for Android applications.


Knot helps managing application state by reacting on events and performing asynchronous actions in a structured way. There are five core concepts Knot defines: State, Change, Action, Reducer and Effect.

State represents an immutable partial state of an application. It can be a state of a screen or a state of an internal headless component, like a repository.

Change is an immutable data object with an optional payload intended for changing the State. A Change can be produced from an external source or be a result of execution of an Action.

Action is a synchronous or an asynchronous operation which, when completed, can – but doesn't have to – emit a new Change.

Reducer is a function that takes the previous State and a Change as arguments and returns the new State and an optional Action wrapped by the Effect class. Reducer in Knot is designed to stay side-effects free because each side-effect can be turned into an Action and returned from the reducer function together with a new state in a pure way.

Effect is a convenient wrapper class containing the new State and an optional Action. If Action is present, Knot will perform it and provide resulting Change (if any) back to the Reducer.

Unique Features

  • DSL. Knot provides a concise and easy to understand DLS for writing state container logic.
  • External events. Knot can mix external events like "user location updates", "database table changes", "network state" etc. into the loop by design. All events go through the reducer first, to be processed in accordance with the current state. Thus the state handling is well synchronized and is localized at a single place - in the reducer.
  • Actions as side-effects. Common unanswered question of many state containers is how to handle side-effects in reducer, when the state does not reflect the change but the app, for instance, has to show a message to the user instead. Knot answers this by allowing to issue an Action from the reducer, which then can be processed outside. This keeps reducer a pure function and provides a structured way of handling side-effects.
  • Decomposition. Knot offers a convenient and structured way of splitting code into multiple parts when the code becomes complex.

Getting Started

The example below declares a Knot capable of loading data, handling Success and Failure loading results and reloading data automatically when an external "data changed" signal gets received. It also logs all State mutations as well as all processed Changes and Actions in console.

sealed class State {
   object Empty : State()
   object Loading : State()
   data class Content(val data: String) : State()
   data class Failed(val error: Throwable) : State()

sealed class Change {
   object Load : Change() {
      data class Success(val data: String) : Change()
      data class Failure(val error: Throwable) : Change()

sealed class Action {
   object Load : Action()

val knot = knot<State, Change, Action> {
    state { 
        initial = State.Empty 
        watchAll { println("state: $it") }
    changes {
        reduce { change ->
            when (change) {
                is Change.Load -> State.Loading + Action.Load
                is Change.Load.Success -> State.Content(data).only
                is Change.Load.Failure -> State.Failed(error).only
        watchAll { println("change: $it") }
    actions {
        perform<Action.Load> {
            switchMapSingle<String> { api.load() }
                .map<Change> { Change.Load.Success(it) }
                .onErrorReturn { Change.Load.Failure(it) }
        watchAll { println("action: $it") }
    events {
        source {
   { Change.Load }

val states = knot.state.test()


Notice how inside the reduce function a new State can be combined with an Action using + operator. If only the State value should be returned from the reducer, the .only suffix is added to the State.


If your knot becomes complex and you want to improve its redability and maintainability, you may consider to decompose it. You start decomposition by grouping related functionality into, in a certain sense, indecomposable pieces called Primes.

Each Prime is isolated from the other Primes. It defines its own set of Changes, Actions and Reducers. It's only the State, what is shared between the Primes. In that respect each Prime can be seen as a separate Knot working on a shared State. Once all Primes are defined, they can be composed together and provided to CompositeKnot which implements standard Knot interface. For more information check out PrimeTest class.

Why Knot?

  • Predictable - state is the single source of truth.
  • Side-effect free reducer - by design.
  • Scalable - single knots can be combined together to build more complex application logic.
  • Decomposable - complex knots can be decomposed into primes by related functionality.
  • Structured - easy to read and write DSL for writing better structured and less buggy code.
  • Concise - it has minimalistic API and compact implementation.
  • Testable - reducers and transformers are easy to test.
  • Production ready - Knot is used in production.
  • Why not?


repositories {
dependencies {
    implementation 'de.halfbit:knot:<version>'


Knot was inspired by two awesome projects


Copyright 2019 Sergej Shafarenka,

Licensed under the Apache License, Version 2.0 (the "License");
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