A WeakMap based memoization library for a better and safer caching

Memoization

Memoization is cool technique. But is it reliable and safe?

What is the difference between lodash.memoize, memoize-one, and React.useMemo?

• lodash.memoize is a cool thing. But by default it has endless cache size.
• memoize-one only remembers the latest arguments and result. No need to worry about cache busting mechanisms such as maxAge, maxSize, exclusions and so on which can be prone to memory leaks.
• react.useMemo is the greatest of all. Still memoize only one call, but doing it on per-component level. The downside of useMemo is React. You cannot use it outside of Functional Component.

What about reselect, a tool powering up all the redux ecosystem? Still - single cache item.

• Is it server-side friendly? Nope, server handles many requests from many clients, and memoized value is constantly got wiped.
• Is it server-side safe? Oh no! Cross request memoization could be a killer! What if memoized value not got rejected??
• Is it test friendly? Nope, tests should always work the same, while memoization will make it... less predictable.

So - it's time to fix all the problems above. Wanna know more - read the article

In short - to better REMEMBER something, you have to better FORGET it

API

• kashe/weakKashe - memoization
• box - prefixed memoization
• inbox - nested prefixed memoization
• fork - nested memoization

TLDR: kashe uses passed arguments as a key to an internal WeakMap to store a result. It does not store anything anywhere - it's always weak. Once argument is gone - data is gone.

kashe

• kashe(function: T):T - transparent weak memoization. Requires first argument to be an object or array or function. The first argument would be used to store a result.

import {kashe} from 'kashe';

const selector = state => [state.a, state.b];
const memoizedSelector = kashe(selector);
memoizedSelector(state) === memoizedSelector(state);

const complexSelector = (state, field) => ({ field: state[field]});
const memoizedComplexSelector = kashe(complexSelector);
memoizedComplexSelector(state, 'a') === memoizedComplexSelector(state, 'a');

weakKashe

For the cases like selectors and mappers some times it's easier to use not strict cache.

const {weakKashe} from 'kashe';

const weakMap = weakKashe((data, iterator, ...deps) => data.map(iterator)); 

const derived = weakMap(data, line => ({...line, somethingElse}), localVariable1);

In this case:

• cache would be stored in the data
• arguments would be matched not by "strict" equality, but by the "toString" equality.
• as a result, the second kashe argument, always the new function, would not destroy cache
• keep in mind - this is not 100% safe operation. Consider adding local scope variables to control cache precision.

boxed

• boxed(function(...args)=>T):(_, ...args)=>T - "prefixes" a call to function with "weakmappable" argument. All arguments shall be equal to return a cached result. Use boxed to make any function kashe-memoizable, buy adding a leading argument.

import {boxed} from 'kashe';

const addTwo = (a,b) => a+b; // could not be "kashe" memoized
const bAddTwo = boxed(addTwo);
const cacheKey = {}; // any object

bAddTwo(cacheKey, 1, 2) === bAddTwo(cacheKey, 1, 2) === 3
bAddTwo(otherCacheKey, 1, 2) // -> a new call

bAddTwo(cacheKey, 10, 20) // -> a new call - arguments dont match
bAddTwo(cacheKey, 1, 2) // -> a new call - original result replaced by 10+20

inboxed

• inboxed(function(...args)=>T):(_, ...args)=>T - "nest" a call to a function with "weakmappable" argument. Use inboxed to make any function kashe-memoizable, buy adding a leading argument.

Diffence from boxed - inboxed "nests" all the cache below it.

import {inboxed} from 'kashe';

const selector = (state) => ({state}) // could be "kashe"-memoized
const memoizedSelector = kashe(selector);

const bSelector = boxed(memoizedSelector);
const ibSelector = inboxed(memoizedSelector);
const cacheKey = {}; // any object

ibSelector(cacheKey, state) === ibSelector(cacheKey, state)
ibSelector(otherCacheKey, state) // a new call. Other key used for inbox, and other cache would be used for memoizedSelector  
ibSelector(cacheKey, otherState) // a new call
ibSelector(cacheKey, state) // cacheKey has cache for `state`

// but!
bSelector(cacheKey, state) === bSelector(otherCacheKey, state)

// bSelector is not "sharing" it's own result (key is different), but underlaying
// `memoizedSelector` shares, and `state` argument is the same.

The difference between inboxed and boxed

• boxed could increase probability to cache a value
• inboxed could decrease probability to cache a value

inboxed is scoping all the nested caches behind a first argument. It if changes - cache changes.

Yet again - first argument is WHERE cache is stored.

boxed is just storing result in a first argument. If cache is not found it is still possible to discover it in a nested cache.

const memoizedSelector = kashe(selector);

const inboxedSelector = inboxed(memoizedSelector);
const boxedSelector = boxed(memoizedSelector);

// state1 !== state2. selectors would use different caches, memoizedSelector included
inboxedSelector(state1, data) !== inboxedSelector(state2, data)

// state1 !== state2. memoization would fail, but memoizedSelector would return the same values
  boxedSelector(state1, data) ===   boxedSelector(state2, data)

inboxedSelector is more memory safe, but CPU intensive. It guratines all selectors would be clean for a session(first argument). boxedSelector is useful as long as everything here is still holds only ONE result. It may be wiped from nested selector, but still exists in a boxed

memoizedSelector(data1);
boxedSelector(state, data1); // they are the same
boxedSelector(state, data2); // updating cache for both selectors
memoizedSelector(data2); // they are the same
memoizedSelector(data1); // cache is updated
boxedSelector(state, data2); // !!!! result is still stored in `state`

fork

• fork(function: T):T - create a copy of a selector, with overiden internal cache. fork has the same effect inbox has, but not adding a leading argument. First argument still expected to be an object, array, or a function.

const selector = (state) => ({state});

const memoized = kashe(selector);
memoized(state) === memoized(state);

const forked = fork(memoized);
memoized(state) !== memoized(state);

Size

1.01 kb

Cook-book

Per-instance one argument memoization

Let's imagine a simple HOC

const hoc = WrappedComponent => <SomeStuff><WrappedComponent/></SomeStuff>;

You want to call this function 10 times, and always get the same result

hoc(ComponentA);
hoc(ComponentA); // !!! a new call === a new result, a new component, so remount! We dont need it.

const memoizedHoc = memoizeOne(hoc);

memoizedHoc(ComponentA);
memoizedHoc(ComponentA); // YES! It works as expected!
memoizedHoc(ComponentB); // BAM! Previous result got wiped
memoizedHoc(ComponentA); // A new result, and BAM! Previous result got wiped 

const kasheHoc = kashe(hoc);

kasheHoc(ComponentA);
kasheHoc(ComponentA); // YES! It works as expected!
kasheHoc(ComponentB); // YES! It works as expected! Result is stored in a first argument.
kasheHoc(ComponentA); // YES! It works as expected! Result is still inside ComponentA 

But what about concurrent execution, where scope may matter, and where you dont want to leave any traces?

// first client
kasheHoc(ComponentA);
// second client
kasheHoc(ComponentA); // We got cached result :(

// lets fix, and "prefix" selector
// using `box` for memoized `kasheHoc` would nullify the effect.

const boxedKasheHoc = inbox(kasheHoc);
// first client
boxedKasheHoc(client1Key, ComponentA);
// second client
boxedKasheHoc(client2Key, ComponentA); // another client key - another memoization! 
boxedKasheHoc(client2Key, ComponentB); // another argument key - another memoization!
boxedKasheHoc(client2Key, ComponentA); // result is cached

Reselect API

A Reselect-compatible API

TLDR: it just replaces default memoization for reselect - createSelectorCreator(strongMemoize);. strongMemoize - is not public API yet.

Reselect is a great library, but it has one limitation - stores only one result. There are a few attempts to "fix" it

• re-reselect, to let you store result in a "buckets". All that data would be kept in a memory.
• memoize-state, to use only data pieces, which matters. Still no problem to miss a cache.
• constructing selectors in mapStateToProps factory function, to create per-instance memoization. That requires a different code structure.

Magically - kashe is ideally compatible with reselect API

import {createSelector} from 'kashe/reselect'

const getDataSlice = (state, props) => state[props.sliceId]
const dataSelector = createSelector(getDataSlice, slice => ({slice})) // lets make it harder

const slice1Value = dataSelector(state, { sliceId: 1 });
const slice2Value = dataSelector(state, { sliceId: 2 });
// the real `reselect` would replace stored value by a new one

const unknownValue = dataSelector(state, { sliceId: 1 });
// the real `reselect` would return a new object here


// `kashe/reselect` - would return `slice1Value`

Troubleshoting

solving Error: No weak-mappable object found to read a cache from.

If all selectors returned a non "weak-mappable" object (like array, object, function, symbol) - kashe would throw. This is intentional, as long as it stores cache inside such objects, and without them it could not work. However, if you think that it should work that way - just give it that "cache"

const cache = {};
const selector = createSelector(
  someSelector, 
  () => cache,  // <---- cache for a selector
  selectedData => {/*...*/}
);

Memoize-one

kashe could not replace memoize-one as long as it requires at least one argument to be a object or array. But if at least one is in list - go for it.

React.useMemo

You may use React.useRef/useState/Context to create and propagate a per-instance, or per-tree variable, you may use for kashe

const KasheContext = React.createContext();
// create a "value provider". useRef would give you an object you may use
const CacheKeyProvider = ({children}) => (
  <KasheContext.Provider value={useRef(null)}>{children}</KasheContext.Provider>
);

const memoizedFunction = kashe(aFunction);

const OtherComponent = () => {
  const kasheKey = useContext(KasheContext);
  const localKasheKey = useRef();
  // use per-render key to store data
  const memoizedData1 = memoizedFunction(kasheKey, firstArgument, secondArgument);
  // use per-instance key to store data
  const memoizedData2 = memoizedFunction(localKasheKey, firstArgument, secondArgument);
}

So - almost the same as React.useMemo, but you might use it in Class Components and mapStateToProps.

Usage in class components

See Don’t Stop the Data Flow in Rendering for details about memoization in react.

// wrap slowlyCalculateTextColor with leading "state" argument 
const generateTextColor = boxed(slowlyCalculateTextColor);

class MyComponent extends React.Component {
  // ...
  render () {
    // use `this` as `state`
    const textColor = generateTextColor(this, this.props.color);
    return (
        <button className={'Button-' + color + ' Button-text-' + textColor}>
          {children}
        </button>
    );
  }
}

mapStateToProps

const mapStateToProps = () => {
  const selector1 = fork(selectors.selector1);
  return state => ({
    value1: selector1(state), // "per-instance" selector
    value2: selectors.selector2(box, state), // normal selector
    value3: memoizedFunction(selector1, state.data), // use "selector1" as a cache-key for another function
  })
};

See also

The nearest analog of kashe is weak-memoize, but it does accept only one argument.

Speed

// a simple one argument function
memoize-one one argument  x 58,277,071 ops/sec ±1.60% (87 runs sampled)
kashe       one argument  x 19,724,367 ops/sec ±0.76% (91 runs sampled)

// a simple two arguments function
memoize-one two arguments x 42,526,871 ops/sec ±0.77% (90 runs sampled)
kashe       two arguments x 16,929,449 ops/sec ±0.84% (89 runs sampled)

// using more than one object to call - memoize-one is failing, while kashe still works
// PS: multiply results by 2 
memoize-one    two states x   308,917 ops/sec ±0.56% (92 runs sampled)
kashe          two states x 8,992,170 ops/sec ±0.96% (83 runs sampled)

Kashe-y?

When I first time I heard my nickname - kashey pronounces as cache - I decides to create a caching library one day. Here we go.

License

MIT