This library is an attempt to make the fastest possible memoization library in JavaScript that supports N arguments. The fastest cache is used for the running environment, but it is possible to pass a custom cache to be used.
memoization jsA memoization library that only caches the result of the most recent arguments. There are only two hard things in Computer Science: cache invalidation and naming things.
memoize performance memoization cacheA collection of the most useful property decorators.
decorators debounce throttle-calls memoize memoizationReact server-side rendering optimization with component memoization and templatization
react-server server-optimization rendering-optimizations component-memoization html-markup isomorphic universal-react optimization react-server-render react-rendering react server-side memoization templatization cache cachingmoize is a consistently blazing fast memoization library for JavaScript. It handles multiple parameters (including default values) without any additional configuration, and offers a large number of options to satisfy any number of potential use-cases. All parameter types are supported, including circular objects, functions, etc. There are also a number of shortcut methods to memoize for unique use-cases.
memoization performance cache expire lru memoize optimize promise ttlMemoize functions - An optimization used to speed up consecutive function calls by caching the result of calls with identical input
memoize function mem memoization cache caching optimize performance ttl expire promiseUseful for speeding up consecutive function calls by caching the result of calls with identical input.See the mem docs.
promise memoize mem memoization function cache caching optimize performance ttl expire async await promises time out cancel bluebirdSimple disk memoization and in memory LRU cache for speeding up frequently accessed high latency IO resources. Queues up concurrent requests for the same resource before it has been cached to avoid fetching it multiple times in parallel.
cache ssd disk memoize memoization network performance latency caching ioClever memoization helper that uses Ruby internals instead of meta-programming.
memoize memoizationWhilst not new by any means, memoization is a useful optimization technique for caching the results of function calls such that lengthy lookups or expensive recursive computations can be minimized where possible. The basic idea is that if you can detect an operation has already been previously completed for a specific set of input values, the stored result can instead be returned instead of repeating the operation again.
memoize memoization cacheSophisticated function memoization
asynchronous async function call memoization backend storageThis decorator applies memoization to a method of a class. Apply the decorator to a method of a class. The cache is local for the method but shared among all instances of the class. Strongly recommend you to use this decorator only on pure methods.
memoization decoratorA caching library for Python.
caching memoization lru mru lfu fifo lifo rr python3Fast (see benchmarks), small (1k min/gzip), efficient, JavaScript memoization lib to memoize JS functions. Uses JavaScript's Map() object for instant lookups, or a performant polyfill if Map is not available - does not do expensive serialization or string manipulation.
memoize memoizer memoization memoized js lru cache fastFull-featured, testable OOP
oop class inheritance testing mocks memoizationAutomagically enhances, even enchants redux connect, to be more concrete - mapStateToProps, wrapping it with memoize-state to sky-rocket your application. Just import beautiful-react-redux and forget about reselect and any other selector memoization. Now your application will runs like it has MobX underneath.
redux react reselect optimization memoization memoize mapstatetoprops selector redrawReselect? Memoize-one? Most of memoization libraries remembers the parameters you provided, not what you did inside. Sometimes is not easy to achive high cache hit ratio. Sometimes you have to think about how to properly dissolve computation into the memoizable parts. Memoize-state is built to memoize more complex situations, even the ones which are faster to recomoute, than to deside that recalculation is not needed. Just because one cheap computation can cause a redraw/reflow/recomputation cascade for a whole application.
memoization proxy memoization-library selector memoize performance mapstatetoprops mobx stateWhy did you update is a function that monkey patches Redux and notifies you in the console when potentially unnecessary re-renders occur due to a unnecessary update from mapStateToProps. This library is available on npm, install it with: npm install --save why-did-you-update-redux or yarn add why-did-you-update-redux.
redux optimization reselect memoizationPersistent incremental computations, for repeatable tests and benchmarks.
ocaml caching merkle-dag memoization persistent
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