lru_cache

    1.0.2 • Public • Published

    Least Recently Used (LRU) cache algorithm

    A finite key-value cache using the Least Recently Used (LRU) cache algorithm where the most recently used objects are keept in cache while less recently used items are purged.

    This implementation is compatible with most JavaScript environments (including ye olde browser) and is very efficient.

    Terminology & design

    • Based on a doubly-linked list for low complexity random shuffling of entries.

    • The cache object iself has a "head" (least recently used entry) and a "tail" (most recently used entry).

    • The "head" and "tail" are "entries" -- an entry might have a "newer" and an "older" entry (doubly-linked, "older" being close to "head" and "newer" being closer to "tail").

    • Key lookup is done through a key-entry mapping native object, which on most platforms mean O(1) complexity. This comes at a very low memory cost (for storing two extra pointers for each entry).

    Fancy ASCII art illustration of the general design:

        entry             entry             entry             entry        
        ______            ______            ______            ______       
       | head |.newer => |      |.newer => |      |.newer => | tail |      
       |  A   |          |  B   |          |  C   |          |  D   |      
       |______| <= older.|______| <= older.|______| <= older.|______|      
    
    removed  <--  <--  <--  <--  <--  <--  <--  <--  <--  <--  <--  added
    

    Example

    var c = new LRUCache(3);
    c.put('adam', 29);
    c.put('john', 26);
    c.put('angela', 24);
    c.toString();        // -> "adam:29 < john:26 < angela:24"
    c.get('john');       // -> 26
    // Now 'john' is the most recently used entry, since we just requested it
    c.toString();        // -> "adam:29 < angela:24 < john:26"
    c.put('zorro', 141); // -> {key:adam, value:29}
    // Because we only have room for 3 entries, put-ing 'zorro' purged 'adam'
    c.toString();        // -> "angela:24 < john:26 < zorro:141"
    

    API

    An entry is a simple Object with at least two members: {key:Object, value:Object}. An entry might also have a newer member which points to a newer entry, and/or a older member pointing to an older entry.

    Included in lru_cache and lru_cache/core:

    new LRUCache(Number limit) -> LRUCache instance

    Creates a new cache object which will hold up to limit entries.

    LRUCache.prototype.size -> Number

    Current number of entries. Read-only.

    LRUCache.prototype.limit <-> Number

    Maximum number of items this cache will keep.

    LRUCache.prototype.put (Object key, Object value) -> Object entry

    Put value into the cache associated with key.

    Returns an entry which was removed (to make room for the new entry) or undefined if there was enough space for the new entry.

    Note: The returned entry does not include any (strong) references to other entries (i.e. there is no older or newer members). This design makes garbage collection predictable.

    LRUCache.prototype.get (Object key) -> Object value

    Retrieve value for, and register recent use of, key. Returns the value associated with key or undefined if not in the cache.

    LRUCache.prototype.shift () -> Object entry

    Remove the least recently used (oldest) entry. Returns the removed entry, or undefined if the cache was empty.

    If you need to perform any form of finalization of purged items, this is a good place to do it. Simply override/replace this function:

    var c = new LRUCache(123);
    c.shift = function() {
      var entry = LRUCache.prototype.shift.call(this);
      doSomethingWith(entry);
      return entry;
    }
    

    The returned entry must not include any strong references to other entries. See note in the documentation of LRUCache.prototype.put (Object key, Object value) -> Object entry.

    Included in lru_cache only

    LRUCache.prototype.find (Object key) -> Object entry

    Check if key is in the cache without registering recent use. Feasible if you do not want to chage the state of the cache, but only "peek" at it. Returns the entry associated with key if found, otherwise undefined is returned.

    Note: The entry returned is managed by the cache (until purged) and thus contains members with strong references which might be altered at any time by the cache object. You should look at the returned entry as being immutable.

    LRUCache.prototype.set (key, value) -> Object oldValue

    Update the value of entry with key or put a new entry. Returns the old value, or undefined if the cache was empty.

    LRUCache.prototype.remove (key) -> Object value

    Remove entry key from cache and return its value. Returns undefined if key is not found.

    LRUCache.prototype.removeAll () -> LRUCache instance

    Removes all entries and return itself.

    LRUCache.prototype.keys () -> Array keys

    Return an array containing all keys of entries in arbitrary order.

    LRUCache.prototype.forEach (fun, [Object context, Boolean desc | true])

    Call fun for each entry. Starting with the newest entry if desc is a true value, otherwise starts with the oldest (head) enrty and moves towards the tail.

    Returns nothing (undefined).

    fun is called with 3 arguments in the context context:

    fun.call(context, Object key, Object value, LRUCache self)
    

    Example which prints "key: value" starting with the most recent entry:

    cache.forEach(function(key, value) {
      puts(key+': '+value);
    }, true);
    

    LRUCache.prototype.toJSON () -> Array representation

    Returns an array of object (for use by JSON.stringify) of the form:

    [
      {key:"key1", value:"value1"},
      {key:"key2", value:"value2"},
      {key:"key3", value:"value3"}
    ]
    

    LRUCache.prototype.toString () -> String representation

    Returns a string representation in the format:

    key1:value1 < key2:value2 < key3:value3
    

    Oldest (head) on the left hand side and newer entries to the right hand side.

    Factorising a minimal implementation

    As this code is most suitable for embedding, here is a shortlist of the essential parts (prototype functions) needed for a minimal implementation. All other functions, not mentioned here, are simply ancillary.

    • LRUCache -- the constructor is naturally a good thing to keep ;)
    • LRUCache.prototype.put -- handles appending and chaining.
    • LRUCache.prototype.shift -- used by put to "purge" an old entry.
    • LRUCache.prototype.get -- fetches a cached entry and registers that entry as being recently used.

    To include only the minimal code above, require lru_cache/core instead of lru_cache

    MIT license

    Copyright (c) 2016 Rasmus Andersson http://hunch.se/, Ben Woosley

    Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

    The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

    THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

    Install

    npm i lru_cache

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    4

    Version

    1.0.2

    License

    MIT

    Last publish

    Collaborators

    • empact