lru-cache
A cache object that deletes the least-recently-used items.
Specify a max number of the most recently used items that you want to keep, and this cache will keep that many of the most recently accessed items.
This is not primarily a TTL cache, and does not make strong TTL
guarantees. There is no preemptive pruning of expired items by
default, but you may set a TTL on the cache or on a single
set
. If you do so, it will treat expired items as missing, and
delete them when fetched. If you are more interested in TTL
caching than LRU caching, check out
@isaacs/ttlcache.
As of version 7, this is one of the most performant LRU implementations available in JavaScript, and supports a wide diversity of use cases. However, note that using some of the features will necessarily impact performance, by causing the cache to have to do more work. See the “Performance” section below.
Installation
npm install lru-cache --save
Usage
const LRU = require('lru-cache')
// At least one of 'max', 'ttl', or 'maxSize' is required, to prevent
// unsafe unbounded storage.
//
// In most cases, it's best to specify a max for performance, so all
// the required memory allocation is done up-front.
//
// All the other options are optional, see the sections below for
// documentation on what each one does. Most of them can be
// overridden for specific items in get()/set()
const options = {
max: 500,
// for use with tracking overall storage size
maxSize: 5000,
sizeCalculation: (value, key) => {
return 1
},
// for use when you need to clean up something when objects
// are evicted from the cache
dispose: (value, key) => {
freeFromMemoryOrWhatever(value)
},
// how long to live in ms
ttl: 1000 * 60 * 5,
// return stale items before removing from cache?
allowStale: false,
updateAgeOnGet: false,
updateAgeOnHas: false,
// async method to use for cache.fetch(), for
// stale-while-revalidate type of behavior
fetch: async (key, staleValue, { options, signal }) => {}
}
const cache = new LRU(options)
cache.set("key", "value")
cache.get("key") // "value"
// non-string keys ARE fully supported
// but note that it must be THE SAME object, not
// just a JSON-equivalent object.
var someObject = { a: 1 }
cache.set(someObject, 'a value')
// Object keys are not toString()-ed
cache.set('[object Object]', 'a different value')
assert.equal(cache.get(someObject), 'a value')
// A similar object with same keys/values won't work,
// because it's a different object identity
assert.equal(cache.get({ a: 1 }), undefined)
cache.clear() // empty the cache
If you put more stuff in it, then items will fall out.
Options
max
The maximum number (or size) of items that remain in the cache
(assuming no TTL pruning or explicit deletions). Note that fewer
items may be stored if size calculation is used, and maxSize
is
exceeded. This must be a positive finite intger.
At least one of max
, maxSize
, or TTL
is required. This
must be a positive integer if set.
It is strongly recommended to set a max
to prevent unbounded
growth of the cache. See “Storage Bounds Safety” below.
maxSize
Set to a positive integer to track the sizes of items added to
the cache, and automatically evict items in order to stay below
this size. Note that this may result in fewer than max
items
being stored.
Optional, must be a positive integer if provided. Required if other size tracking features are used.
At least one of max
, maxSize
, or TTL
is required. This
must be a positive integer if set.
Even if size tracking is enabled, it is strongly recommended to
set a max
to prevent unbounded growth of the cache. See
“Storage Bounds Safety” below.
sizeCalculation
Function used to calculate the size of stored items. If you’re
storing strings or buffers, then you probably want to do
something like n => n.length
. The item is passed as the first
argument, and the key is passed as the second argument.
This may be overridden by passing an options object to
cache.set()
.
Requires maxSize
to be set.
Deprecated alias: length
fetchMethod
Function that is used to make background asynchronous fetches.
Called with fetchMethod(key, staleValue, { signal, options })
.
May return a Promise.
If fetchMethod
is not provided, then cache.fetch(key)
is
equivalent to Promise.resolve(cache.get(key))
.
The signal
object is an AbortSignal
if that’s available in
the global object, otherwise it’s a pretty close polyfill.
If at any time, signal.aborted
is set to true
, or if the
signal.onabort
method is called, or if it emits an 'abort'
event which you can listen to with addEventListener
, then that
means that the fetch should be abandoned. This may be passed
along to async functions aware of AbortController/AbortSignal
behavior.
The options
object is a union of the options that may be
provided to set()
and get()
. If they are modified, then that
will result in modifying the settings to cache.set()
when the
value is resolved. For example, a DNS cache may update the TTL
based on the value returned from a remote DNS server by changing
options.ttl
in the fetchMethod
.
noDeleteOnFetchRejection
If a fetchMethod
throws an error or returns a rejected promise,
then by default, any existing stale value will be removed from
the cache.
If noDeleteOnFetchRejection
is set to true
, then this
behavior is suppressed, and the stale value remains in the cache
in the case of a rejected fetchMethod
.
This is important in cases where a fetchMethod
is only called
as a background update while the stale value is returned, when
allowStale
is used.
This may be set in calls to fetch()
, or defaulted on the
constructor.
dispose
Function that is called on items when they are dropped from the
cache, as this.dispose(value, key, reason)
.
This can be handy if you want to close file descriptors or do other cleanup tasks when items are no longer stored in the cache.
NOTE: It is called before the item has been fully removed
from the cache, so if you want to put it right back in, you need
to wait until the next tick. If you try to add it back in during
the dispose()
function call, it will break things in subtle and
weird ways.
Unlike several other options, this may not be overridden by
passing an option to set()
, for performance reasons. If
disposal functions may vary between cache entries, then the
entire list must be scanned on every cache swap, even if no
disposal function is in use.
The reason
will be one of the following strings, corresponding
to the reason for the item’s deletion:
evict
Item was evicted to make space for a new additionset
Item was overwritten by a new valuedelete
Item was removed by explicitcache.delete(key)
or by callingcache.clear()
, which deletes everything.
The dispose()
method is not called for canceled calls to
fetchMethod()
. If you wish to handle evictions, overwrites,
and deletes of in-flight asynchronous fetches, you must use the
AbortSignal
provided.
Optional, must be a function.
disposeAfter
The same as dispose
, but called after the entry is completely
removed and the cache is once again in a clean state.
It is safe to add an item right back into the cache at this point. However, note that it is very easy to inadvertently create infinite recursion in this way.
The disposeAfter()
method is not called for canceled calls to
fetchMethod()
. If you wish to handle evictions, overwrites,
and deletes of in-flight asynchronous fetches, you must use the
AbortSignal
provided.
noDisposeOnSet
Set to true
to suppress calling the dispose()
function if the
entry key is still accessible within the cache.
This may be overridden by passing an options object to
cache.set()
.
Boolean, default false
. Only relevant if dispose
or
disposeAfter
options are set.
ttl
Max time to live for items before they are considered stale. Note that stale items are NOT preemptively removed by default, and MAY live in the cache, contributing to its LRU max, long after they have expired.
Also, as this cache is optimized for LRU/MRU operations, some of the staleness/TTL checks will reduce performance, as they will incur overhead by deleting from Map objects rather than simply throwing old Map objects away.
This is not primarily a TTL cache, and does not make strong TTL guarantees. There is no pre-emptive pruning of expired items, but you may set a TTL on the cache, and it will treat expired items as missing when they are fetched, and delete them.
Optional, but must be a positive integer in ms if specified.
This may be overridden by passing an options object to
cache.set()
.
At least one of max
, maxSize
, or TTL
is required. This
must be a positive integer if set.
Even if ttl tracking is enabled, it is strongly recommended to
set a max
to prevent unbounded growth of the cache. See
“Storage Bounds Safety” below.
If ttl tracking is enabled, and max
and maxSize
are not set,
and ttlAutopurge
is not set, then a warning will be emitted
cautioning about the potential for unbounded memory consumption.
Deprecated alias: maxAge
noUpdateTTL
Boolean flag to tell the cache to not update the TTL when setting a new value for an existing key (ie, when updating a value rather than inserting a new value). Note that the TTL value is always set (if provided) when adding a new entry into the cache.
This may be passed as an option to cache.set()
.
Boolean, default false.
ttlResolution
Minimum amount of time in ms in which to check for staleness.
Defaults to 1
, which means that the current time is checked at
most once per millisecond.
Set to 0
to check the current time every time staleness is
tested.
Note that setting this to a higher value will improve performance somewhat while using ttl tracking, albeit at the expense of keeping stale items around a bit longer than intended.
ttlAutopurge
Preemptively remove stale items from the cache.
Note that this may significantly degrade performance, especially if the cache is storing a large number of items. It is almost always best to just leave the stale items in the cache, and let them fall out as new items are added.
Note that this means that allowStale
is a bit pointless, as
stale items will be deleted almost as soon as they expire.
Use with caution!
Boolean, default false
allowStale
By default, if you set ttl
, it’ll only delete stale items from
the cache when you get(key)
. That is, it’s not preemptively
pruning items.
If you set allowStale:true
, it’ll return the stale value as
well as deleting it. If you don’t set this, then it’ll return
undefined
when you try to get a stale entry.
Note that when a stale entry is fetched, even if it is returned
due to allowStale
being set, it is removed from the cache
immediately. You can immediately put it back in the cache if you
wish, thus resetting the TTL.
This may be overridden by passing an options object to
cache.get()
. The cache.has()
method will always return
false
for stale items.
Boolean, default false, only relevant if ttl
is set.
Deprecated alias: stale
updateAgeOnGet
When using time-expiring entries with ttl
, setting this to
true
will make each item’s age reset to 0 whenever it is
retrieved from cache with get()
, causing it to not expire. (It
can still fall out of cache based on recency of use, of course.)
This may be overridden by passing an options object to
cache.get()
.
Boolean, default false, only relevant if ttl
is set.
updateAgeOnHas
When using time-expiring entries with ttl
, setting this to
true
will make each item’s age reset to 0 whenever its presence
in the cache is checked with has()
, causing it to not expire.
(It can still fall out of cache based on recency of use, of
course.)
This may be overridden by passing an options object to
cache.has()
.
Boolean, default false, only relevant if ttl
is set.
API
new LRUCache(options)
Create a new LRUCache. All options are documented above, and are on the cache as public members.
cache.max
, cache.maxSize
, cache.allowStale
,
cache.noDisposeOnSet
, cache.sizeCalculation
, cache.dispose
,
cache.maxSize
, cache.ttl
, cache.updateAgeOnGet
,
cache.updateAgeOnHas
All option names are exposed as public members on the cache object.
These are intended for read access only. Changing them during program operation can cause undefined behavior.
cache.size
The total number of items held in the cache at the current moment.
cache.calculatedSize
The total size of items in cache when using size tracking.
`set(key, value, [{ size, sizeCalculation, ttl,
noDisposeOnSet }])`
Add a value to the cache.
Optional options object may contain ttl
and sizeCalculation
as described above, which default to the settings on the cache
object.
Options object my also include size
, which will prevent calling
the sizeCalculation
function and just use the specified number
if it is a positive integer, and noDisposeOnSet
which will
prevent calling a dispose
function in the case of overwrites.
Will update the recency of the entry.
Returns the cache object.
get(key, { updateAgeOnGet, allowStale } = {}) => value
Return a value from the cache.
Will update the recency of the cache entry found.
If the key is not found, get()
will return undefined
. This
can be confusing when setting values specifically to undefined
,
as in cache.set(key, undefined)
. Use cache.has()
to
determine whether a key is present in the cache at all.
`async fetch(key, { updateAgeOnGet, allowStale, size,
sizeCalculation, ttl, noDisposeOnSet } = {}) => Promise`
If the value is in the cache and not stale, then the returned Promise resolves to the value.
If not in the cache, or beyond its TTL staleness, then
fetchMethod(key, staleValue, options)
is called, and the value
returned will be added to the cache once resolved.
If called with allowStale
, and an asynchronous fetch is
currently in progress to reload a stale value, then the former
stale value will be returned.
Multiple fetches for the same key
will only call fetchMethod
a single time, and all will be resolved when the value is
resolved, even if different options are used.
If fetchMethod
is not specified, then this is effectively an
alias for Promise.resolve(cache.get(key))
.
When the fetch method resolves to a value, if the fetch has not been aborted due to deletion, eviction, or being overwritten, then it is added to the cache using the options provided.
peek(key, { allowStale } = {}) => value
Like get()
but doesn’t update recency or delete stale items.
Returns undefined
if the item is stale, unless allowStale
is
set either on the cache or in the options object.
has(key, { updateAgeOnHas } = {}) => Boolean
Check if a key is in the cache, without updating the recency of
use. Age is updated if updateAgeOnHas
is set to true
in
either the options or the constructor.
Will return false
if the item is stale, even though it is
technically in the cache.
delete(key)
Deletes a key out of the cache.
Returns true
if the key was deleted, false
otherwise.
clear()
Clear the cache entirely, throwing away all values.
Deprecated alias: reset()
keys()
Return a generator yielding the keys in the cache, in order from most recently used to least recently used.
rkeys()
Return a generator yielding the keys in the cache, in order from least recently used to most recently used.
values()
Return a generator yielding the values in the cache, in order from most recently used to least recently used.
rvalues()
Return a generator yielding the values in the cache, in order from least recently used to most recently used.
entries()
Return a generator yielding [key, value]
pairs, in order from
most recently used to least recently used.
rentries()
Return a generator yielding [key, value]
pairs, in order from
least recently used to most recently used.
find(fn, [getOptions])
Find a value for which the supplied fn
method returns a truthy
value, similar to Array.find()
.
fn
is called as fn(value, key, cache)
.
The optional getOptions
are applied to the resulting get()
of
the item found.
dump()
Return an array of [key, entry]
objects which can be passed to
cache.load()
Note: this returns an actual array, not a generator, so it can be more easily passed around.
load(entries)
Reset the cache and load in the items in entries
in the order
listed. Note that the shape of the resulting cache may be
different if the same options are not used in both caches.
purgeStale()
Delete any stale entries. Returns true
if anything was
removed, false
otherwise.
Deprecated alias: prune
getRemainingTTL(key)
Return the number of ms left in the item’s TTL. If item is not
in cache, returns 0
. Returns Infinity
if item is in cache
without a defined TTL.
forEach(fn, [thisp])
Call the fn
function with each set of fn(value, key, cache)
in the LRU cache, from most recent to least recently used.
Does not affect recency of use.
If thisp
is provided, function will be called in the
this
-context of the provided object.
rforEach(fn, [thisp])
Same as cache.forEach(fn, thisp)
, but in order from least
recently used to most recently used.
pop()
Evict the least recently used item, returning its value.
Returns undefined
if cache is empty.
Internal Methods and Properties
In order to optimize performance as much as possible, “private” members and methods are exposed on the object as normal properties, rather than being accessed via Symbols, private members, or closure variables.
Do not use or rely on these. They will change or be removed without notice. They will cause undefined behavior if used inappropriately. There is no need or reason to ever call them directly.
This documentation is here so that it is especially clear that this not “undocumented” because someone forgot; it is documented, and the documentation is telling you not to do it.
Do not report bugs that stem from using these properties. They will be ignored.
initializeTTLTracking()
Set up the cache for tracking TTLsupdateItemAge(index)
Called when an item age is updated, by internal IDsetItemTTL(index)
Called when an item ttl is updated, by internal IDisStale(index)
Called to check an item’s staleness, by internal IDinitializeSizeTracking()
Set up the cache for tracking item size. Called automatically when a size is specified.removeItemSize(index)
Updates the internal size calculation when an item is removed or modified, by internal IDaddItemSize(index)
Updates the internal size calculation when an item is added or modified, by internal IDindexes()
An iterator over the non-stale internal IDs, from most recently to least recently used.rindexes()
An iterator over the non-stale internal IDs, from least recently to most recently used.newIndex()
Create a new internal ID, either reusing a deleted ID, evicting the least recently used ID, or walking to the end of the allotted space.evict()
Evict the least recently used internal ID, returning its ID. Does not do any bounds checking.connect(p, n)
Connect thep
andn
internal IDs in the linked list.moveToTail(index)
Move the specified internal ID to the most recently used position.keyMap
Map of keys to internal IDskeyList
List of keys by internal IDvalList
List of values by internal IDsizes
List of calculated sizes by internal IDttls
List of TTL values by internal IDstarts
List of start time values by internal IDnext
Array of “next” pointers by internal IDprev
Array of “previous” pointers by internal IDhead
Internal ID of least recently used itemtail
Internal ID of most recently used itemfree
Stack of deleted internal IDs
Storage Bounds Safety
This implementation aims to be as flexible as possible, within the limits of safe memory consumption and optimal performance.
At initial object creation, storage is allocated for max
items.
If max
is set to zero, then some performance is lost, and item
count is unbounded. Either maxSize
or ttl
must be set if
max
is not specified.
If maxSize
is set, then this creates a safe limit on the
maximum storage consumed, but without the performance benefits of
pre-allocation. When maxSize
is set, every item must provide
a size, either via the sizeCalculation
method provided to the
constructor, or via a size
or sizeCalculation
option provided
to cache.set()
. The size of every item must be a positive
integer.
If neither max
nor maxSize
are set, then ttl
tracking must
be enabled. Note that, even when tracking item ttl
, items are
not preemptively deleted when they become stale, unless
ttlAutopurge
is enabled. Instead, they are only purged the
next time the key is requested. Thus, if ttlAutopurge
, max
,
and maxSize
are all not set, then the cache will potentially
grow unbounded.
In this case, a warning is printed to standard error. Future
versions may require the use of ttlAutopurge
if max
and
maxSize
are not specified.
If you truly wish to use a cache that is bound only by TTL
expiration, consider using a Map
object, and calling
setTimeout
to delete entries when they expire. It will perform
much better than an LRU cache.
Here is an implementation you may use, under the same license as this package:
// a storage-unbounded ttl cache that is not an lru-cache
const cache = {
data: new Map(),
timers: new Map(),
set: (k, v, ttl) => {
if (cache.timers.has(k)) {
clearTimeout(cache.timers.get(k))
}
cache.timers.set(k, setTimeout(() => cache.del(k), ttl))
cache.data.set(k, v)
},
get: k => cache.data.get(k),
has: k => cache.data.has(k),
delete: k => {
if (cache.timers.has(k)) {
clearTimeout(cache.timers.get(k))
}
cache.timers.delete(k)
return cache.data.delete(k)
},
clear: () => {
cache.data.clear()
for (const v of cache.timers.values()) {
clearTimeout(v)
}
cache.timers.clear()
}
}
If that isn’t to your liking, check out @isaacs/ttlcache.
Performance
As of January 2022, version 7 of this library is one of the most performant LRU cache implementations in JavaScript.
Benchmarks can be extremely difficult to get right. In particular, the performance of set/get/delete operations on objects will vary wildly depending on the type of key used. V8 is highly optimized for objects with keys that are short strings, especially integer numeric strings. Thus any benchmark which tests solely using numbers as keys will tend to find that an object-based approach performs the best.
Note that coercing anything to strings to use as object keys is unsafe, unless you can be 100% certain that no other type of value will be used. For example:
const myCache = {}
const set = (k, v) => myCache[k] = v
const get = (k) => myCache[k]
set({}, 'please hang onto this for me')
set('[object Object]', 'oopsie')
Also beware of “Just So” stories regarding performance. Garbage collection of large (especially: deep) object graphs can be incredibly costly, with several “tipping points” where it increases exponentially. As a result, putting that off until later can make it much worse, and less predictable. If a library performs well, but only in a scenario where the object graph is kept shallow, then that won’t help you if you are using large objects as keys.
In general, when attempting to use a library to improve performance (such as a cache like this one), it’s best to choose an option that will perform well in the sorts of scenarios where you’ll actually use it.
This library is optimized for repeated gets and minimizing eviction time, since that is the expected need of a LRU. Set operations are somewhat slower on average than a few other options, in part because of that optimization. It is assumed that you’ll be caching some costly operation, ideally as rarely as possible, so optimizing set over get would be unwise.
If performance matters to you:
- If it’s at all possible to use small integer values as keys, and you can guarantee that no other types of values will be used as keys, then do that, and use a cache such as lru-fast, or mnemonist’s LRUCache which uses an Object as its data store.
- Failing that, if at all possible, use short non-numeric strings (ie, less than 256 characters) as your keys, and use mnemonist’s LRUCache.
- If the types of your keys will be long strings, strings that
look like floats,
null
, objects, or some mix of types, or if you aren’t sure, then this library will work well for you. - Do not use a
dispose
function, size tracking, or especially ttl behavior, unless absolutely needed. These features are convenient, and necessary in some use cases, and every attempt has been made to make the performance impact minimal, but it isn’t nothing.
Breaking Changes in Version 7
This library changed to a different algorithm and internal data structure in version 7, yielding significantly better performance, albeit with some subtle changes as a result.
If you were relying on the internals of LRUCache in version 6 or before, it probably will not work in version 7 and above.
For more info, see the change log.