Reductor


Source link: https://github.com/Yarikx/reductor

Reductor: Redux for Android

Redux inspired predictable state container library for Java/Android.

Reductor can help you make your state mutations easier to read, write and reason about. It leverages annotation processing to validate correctness and generate boilerplate code at compile time, allowing you to express state reducers in a concise way as pure java functions. As Redux it's based on three principles (from Redux documentation):

  • Single source of truth
  • State is read-only
  • Changes are made with pure functions

Key point of this implementation was to keep the original concept of Redux to reuse most of existing approaches but provide nice Java API and preserve types as much as possible.

Reductor advantages:

  • Lightweight
  • Do not use reflection
  • Follow implementation of Redux
  • Allow to compose a state with @CombinedState
  • Allow to define Reducers in typesafe way with @AutoReducer

Note: This version is still under development, API may change till version 1.0

Blog posts

Installation

repositories {

  jcenter() 
}
  dependencies {

  compile 'com.yheriatovych:reductor:x.x.x'
  apt
  'com.yheriatovych:reductor-processor:x.x.x' 
}

Apt dependency on reductor-processor is only necessary if you want to use features as @CombinedState and @AutoReducer

Getting started

First example: Simple counter

//state will be just integer //define actions @ActionCreator interface CounterActions {

  String INCREMENT = "INCREMENT";
  String ADD = "ADD";

@ActionCreator.Action(INCREMENT)
  Action increment();

 @ActionCreator.Action(ADD)
  Action add(int value);
 
}

 //Define reducer

   @AutoReducer abstract class CounterReducer implements Reducer<Integer> {

  @AutoReducer.InitialState
  int initialState() {

return 0;
  
}

@AutoReducer.Action(

 value = CounterActions.INCREMENT,

 from = CounterActions.class)
  int increment(int state) {

return state + 1;
  
}

@AutoReducer.Action(

 value = CounterActions.ADD,

 from = CounterActions.class)
  int add(int state, int value) {

return state + value;
  
}

public static CounterReducer create() {

return new CounterReducerImpl();
 //Note: usage of generated class
  
}
 
}
  //Now you can create store and dispatch some actions public static void main(String[] args) {

  //Now you can create store and dispatch some actions
  Store<Integer> counterStore = Store.create(CounterReducer.create());

//you can access state anytime with Store.getState()
  System.out.println(counterStore.getState());

 //print 0  

 //no need to implement CounterActions, we can do it for you
  CounterActions actions = Actions.from(CounterActions.class);

//you can subscribe to state changes 
  counterStore.subscribe(state -> System.out.println(state));

counterStore.dispatch(actions.increment());
 //print 1  

counterStore.dispatch(actions.increment());
 //print 2  

counterStore.dispatch(actions.add(5));

//print 7 
}

API

Main point of interaction with state is Store object. Store is actually container for your state.

There are two ways of accessing the state inside the Store:

  • Call store.getState() to get the state Store holds at the moment
  • Call store.subscribe(state -> doSomething(state)). Calling subscribe will notify provided listener every time state changes

And only one way how to change the state:

  • Call store.dispatch(action) to deliver and process it by corresponding Reducer.

Advanced use

Combine Reducers

For one store you need one Reducer, however usually state is complex and it's good practice to separate logic to separate it into multiple reducers.

You can do it manually by creating Reducer which delegate reducing logic to 'smaller' reducers

 //Complex state  class Todo {

List<String> items;

String searchQuery;

 public Todo(List<String> items, String searchQuery) {

 this.items = items;

 this.searchQuery = searchQuery;

}
  
}

 //define reducer per sub-states  class ItemsReducer implements Reducer<List<String>> {

@Override

public List<String> reduce(List<String> strings, Action action) {
...
}

}

 class QueryReducer implements Reducer<String> {

@Override

public String reduce(String filter, Action action) {
...
}
  
}

 //define combined reducer  class TodoReducer implements Reducer<Todo> {

private ItemsReducer itemsReducer = new ItemsReducer();

private QueryReducer queryReducer = new QueryReducer();

@Override

public Todo reduce(Todo todo, Action action) {

 //composing new state based on sub-reducers

 return new Todo(

itemsReducer.reduce(todo.items, action),

queryReducer.reduce(todo.searchQuery, action)

 );

}
  
}

This approach works but requires developer to write a bit of boilerplate of dispatching sub-states to sub-reducers. That's why Reductor can do boring work for you. Just use @CombinedState to generate corresponding Reducer

//Complex state @CombinedState interface Todo {

  List<String> items();

  String searchQuery();
 
}
  //define reducer per sub-states class ItemsReducer implements Reducer<List<String>> {

  @Override
  public List<String> reduce(List<String> strings, Action action) {
return null;
}
 
}
  class QueryReducer implements Reducer<String> {

  @Override
  public String reduce(String filter, Action action) {
return null;
}
 
}
  public static void main(String[] args) {

  //Using generated TodoReducer
  Reducer<Todo> todoReducer = TodoReducer.builder()

 .itemsReducer(new ItemsReducer())

 .searchQueryReducer(new QueryReducer())

 .build();
 
}

Note that @CombinedState annotated class needs to be interface or AutoValue abstract class.

AutoReducer

Consider following Reducer which manages List<String>.

Note: PCollections library is used as implementation of persistent collections.

//  class ItemsReducer implements Reducer<List<String>> {

  @Override
  public List<String> reduce(List<String> items, Action action) {

switch (action.type) {

 case "ADD_ITEM": {

  String value = (String) action.value;

  return TreePVector.from(items)

 .plus(value);

 
}

 case "REMOVE_ITEM": {

  String value = (String) action.value;

  return TreePVector.from(items)

 .minus(value);

 
}

 case "REMOVE_BY_INDEX": {

  int index = (int) action.value;

  return TreePVector.from(items)

 .minus(index);

 
}

 default:

  return items;

}

  
}
 
}

This way of writing reducers is canonical but have some disadvantages:

  • Boilerplate code for switch statement
  • Unsafe casting action.value to expected type

That's why Reductor has @AutoReducer to help developer by generating reduce method

//AutoReducer annotated class should be abstract class which implement Reducer interface @AutoReducer abstract class ItemsReducer implements Reducer<List<String>> {

 //Each 'handler' should be annotated with @AutoReducer.Action
  @AutoReducer.Action("ADD_ITEM")
  List<String> add(List<String> state, String value) {

return TreePVector.from(state)

  .plus(value);

  
}

@AutoReducer.Action("REMOVE_ITEM")
  List<String> remove(List<String> state, String value) {

return TreePVector.from(state)

  .minus(value);

  
}

@AutoReducer.Action("REMOVE_BY_INDEX")
  List<String> removeByIndex(List<String> state, int index) {

return TreePVector.from(state)

  .minus(index);

  
}

static ItemsReducer create() {

//Note: ItemsReducerImpl is generated class

return new ItemsReducerImpl();

  
}
 
}

@AutoReducer.Action annotation supports declaring action creator. That will check at compile time if there is such action creator with the same parameters. Example: interface, usage.

Defining action creators

In Reductor, an action is represented with class Action. It contains two fields:

  • type: defines action id or name.
  • values: arrays of arbitrary objects that can be added as payload.

You can create this Actions ad-hoc, just before dispatching. However usually it's more natural and readable way to encapsulate it into "Action creator" function, like:

Action addItemToCart(int itemId, String name, int price) {

  return Action.create("CART_ADD_ITEM", itemId, name, price);
 
}

But that's not fun to write code for just bundling arguments inside. That's why Reductor lets you define all your action creators as just interface functions.

@ActionCreator interface CartActions{

  @ActionCreator.Action("CART_ADD_ITEM")
  Action addItem(int itemId, String name, int price);

@ActionCreator.Action("CART_REMOVE_ITEM")
  Action removeItem(int itemId);
 
}

Reductor will generate implementation. To get the instance just call Actions.from(class):

CartActions cartActions = Actions.from(CartActions.class);
 store.dispatch(cartActions.addItem(42, "Phone", 350));

The information about actions structure is also used to check if @AutoReducer reducer actions have the same structure and name.

Roadmap

  • Support Kotlin data classes to use with @CombinedState
  • Better documentation
  • Minimize usage of generated code from a source code
  • Add more example:
    • Async actions
    • Time-traveling
    • Dispatching custom actions with Middleware
    • Using Rx with store

Resources

This example project is an attempt at a simple implementation of sectioned, expandable, grid RecyclerView.

Makes your data classes Parcelable. Just add AutoParceable to the class declaration. That's all. No methods need to be implemented.

Rosie is an Android framework to create applications following the Clean Architecture.

Rosie divides your application in three layers, view, domain and repository. For each layer, Rosie provides plenty of classes that will make defining and separating these concerns much easier.

This is an Android library allowing to add Header and/or Footer in your RecyclerView in the simplest way possible.

Implementation of Android Marshmallow Boot Animation.

Simple library that helps developers to create awesome sliding android app tutorial.

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