@alloc/quick-lru

@alloc/quick-lru

Simple “Least Recently Used” (LRU) cache

This is a CommonJS-only fork of quick-lru.

Useful when you need to cache something and limit memory usage.

See the algorithm section for implementation details.

Install

$ npm install @alloc/quick-lru

Usage

const QuickLRU = require('@alloc/quick-lru');

const lru = new QuickLRU({maxSize: 1000});

lru.set('🦄', '🌈');

lru.has('🦄');
//=> true

lru.get('🦄');
//=> '🌈'

API

new QuickLRU(options?)

Returns a new instance.

options

Type: object

maxSize

Required
Type: number

The target maximum number of items before evicting the least recently used items.

Note: The dual-cache algorithm may physically retain up to twice maxSize entries for performance reasons, even though the reported cache size does not exceed maxSize.

maxAge

Type: number
Default: Infinity

The maximum number of milliseconds an item should remain in cache. By default maxAge will be Infinity, which means that items will never expire.

Lazy expiration happens upon the next write or read call.

Individual expiration of an item can be specified by the set(key, value, options) method.

onEviction

Optional
Type: (key, value) => void

Called right before an item is evicted from the cache due to capacity pressure or TTL expiration.

Useful for side effects or for items like object URLs that need explicit cleanup (revokeObjectURL).

This callback is not called for manual removals via delete() or clear().

Instance

The instance is iterable so you can use it directly in a for…of loop.

Both key and value can be of any type.

.set(key, value, options?)

Set an item. Returns the instance.

Individual expiration of an item can be specified with the maxAge option. If not specified, the global maxAge value will be used in case it is specified on the constructor, otherwise the item will never expire.

.get(key)

Get an item.

.has(key)

Check if an item exists.

.peek(key)

Get an item without marking it as recently used.

.expiresIn(key)

Get the remaining time to live (in milliseconds) for the given item, or undefined if the item is not in the cache.

• Does not mark the item as recently used.
• Does not trigger lazy expiration or remove the entry when it is expired.
• Returns Infinity if the item has no expiration.
• May return a negative number if the item has already expired but has not yet been lazily removed.

.delete(key)

Delete an item.

Returns true if the item is removed or false if the item doesn't exist.

.clear()

Delete all items.

.resize(maxSize)

Update the maxSize, discarding items as necessary. Insertion order is mostly preserved, though this is not a strong guarantee.

Useful for on-the-fly tuning of cache sizes in live systems.

.keys()

Iterable for all the keys.

.values()

Iterable for all the values.

.entriesAscending()

Iterable for all entries, starting with the oldest (ascending in recency).

.entriesDescending()

Iterable for all entries, starting with the newest (descending in recency).

.size

The stored item count.

Algorithm

This library implements a variant of the hashlru algorithm using two Map objects. One map holds recently added or accessed entries, while the other holds older entries. When the recent map reaches maxSize, it replaces the older map and a new recent map is created.

This avoids the frequent delete operations required by a traditional linked-list LRU and supports keys of any type and undefined values. The tradeoff is that the two maps may physically retain up to twice the target maxSize between rotations. Use a strict-size cache when that temporary memory overhead is unacceptable.

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Similar packages

Other packages similar to @alloc/quick-lru

lru-cache

lru-cache is another popular LRU cache implementation. It offers a rich set of features like item expiration, cache resizing, and a more extensive API for cache manipulation. Compared to @alloc/quick-lru, it might be more suitable for applications requiring these advanced features, but it could also be heavier in terms of performance and resource usage.

tiny-lru

tiny-lru is a minimalistic LRU cache implementation focused on performance and a small footprint. It provides basic LRU cache functionality similar to @alloc/quick-lru but with fewer features. It's an excellent choice for projects where simplicity and efficiency are paramount.