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Create the next immutable state by mutating the current one

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Immer

Your personally assistance for creating your next immutable state


Immer (German for: always) is a tiny package that allows you to work with immutable state in a more convenient way. It is based on copy-on-write mechanism.

The basic idea is that you will apply all your changes to a draftState. Which is a proxy of the currentState, and once all your mutations are completed, immer will produce the nextState based on the mutations to the draft state. This means that you can interact with your data by simply modifying it, while keeping all the benefits of immutable data.

immer.png

Using immer is like having a personal assistant; he takes a letter (the current state), and gives you a copy (draft) to jod changes onto. Once you are done the assistant will take your draft and produce the real immutable, final letter for you (the next state).

API

The immer package exposes a single function:

immer(currentState, fn: (draftState) => void): nextState

Example

const baseState = [
    {
        todo: "Learn typescript",
        done: true
    },
    {
        todo: "Try immer",
        done: false
    }
]

const nextState = immer(baseState, draftState => {
    draftState.push({ todo: "Tweet about it" })
    draftState[1].done = true
})

The interesting thing about immer is that baseState will be untouched, but that nextState will reflect all changes made to draftState.

// the new item is only added to the next state,
// base state is unmodified
expect(baseState.length).toBe(2)
expect(nextState.length).toBe(3)

// same for the changed 'done' prop
expect(baseState[1].done).toBe(false)
expect(nextState[1].done).toBe(true)

// unchanged data is structurally shared
expect(nextState[0]).toBe(baseState[0])
// changed data not (dûh)
expect(nextState[1]).not.toBe(baseState[1])

Benefits

  • Use the language© to construct create your next state
  • Strongly typed, no string based paths etc
  • Deep updates are trivial
  • Small, dependency free library with minimal api surface
  • No accidental mutations of current state, but intentional mutations of a draft state

Reducer Example

A lot of words; here is a simple example of what difference that could make in practice. The todo reducers from the official Redux todos-with-undo example

Note, this is just a sample application of the immer package. Immer is design to just simply Redux reducers. It can be used in any context where you have an immutable data tree that you want to clone and modify (with structural sharing)

const todo = (state, action) => {
  switch (action.type) {
    case 'ADD_TODO':
      return {
        id: action.id,
        text: action.text,
        completed: false
      }
    case 'TOGGLE_TODO':
      if (state.id !== action.id) {
        return state
      }

      return {
        ...state,
        completed: !state.completed
      }
    default:
      return state
  }
}

const todos = (state = [], action) => {
  switch (action.type) {
    case 'ADD_TODO':
      return [
        ...state,
        todo(undefined, action)
      ]
    case 'TOGGLE_TODO':
      return state.map(t =>
        todo(t, action)
      )
    default:
      return state
  }
}

After using immer, that simply becomes:

import immer from 'immer'

const todos = (state = [], action) =>
  // immer produces nextState from draftState and returns it
  immer(state, draftState => {
    switch (action.type) {
      case 'ADD_TODO':
        draftState.push({
          id: action.id,
          text: action.text,
          completed: false
        })
        return
      case 'TOGGLE_TODO':
        const todo = draftState.find(todo => todo.id === action.id)
        todo.completed = !todo.completed
        return
    }
  })

Creating middleware or reducer wrapper that applies immer automatically is left as exercise to the reader :-).

Limitations

  • This package requires Proxies, so Safari > 10, no Internet Explorer
  • Currently only tree shaped states are supported. Cycles could potentially be supported as well (PR's welcome)
  • Currently only supports plain objects and arrays. Non-plain data structures (like Map, Set) not (yet). (PR's welcome)

Pitfalls:

  • Make sure to modify the state you get passed in in the callback function, not the original base state that was passed as first argument to immer!
  • Since immer uses proxies, reading huge amounts of data from state comes with an overhead. If this ever becomes an issue (measure before optimize!), do the current state analysis before entering the immer block or read form the currentState rather than the draftState

Changelog

0.0.4 (31-12-2017)

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