package ringo

A mutable structure that holds at most a fixed number of values of a same type. Values are not removed by hand, instead, once the limit is reached, adding a value replaces the oldest one in the buffer.

Ring is a potentially useful module that is used internally to manage bounded, FIFO collections of items. The documentation is available in UNBOXED_COLLECTION.

Dll is a potentially useful module that is used internally to manage bounded, LRU collections of items. The documentation is available in UNBOXED_COLLECTION.

A Mutable structure akin to a hash-table, but with a size bound. Note that, different caches have different policies towards the size bounds: some uphold the bound strictly, some treat the bound as a suggestion. In addition, some caches count their elements somewhat sloppily.

A Mutable structure akin to a set, but with a size bound. Note that, different caches have different policies towards the size bounds: some uphold the bound strictly, some treat the bound as a suggestion. In addition, some caches count their elements somewhat sloppily.

replacement is for defining the replacement policy of a cache. LRU is for "Least Recently Used", meaning that when a supernumerary item is inserted in the cache, the least recently used item is removed to make room. FIFO is for "First-In, First-Out" meaning that when a supernumerary item is inserted in the cache, the oldest inserted element is removed to make room.

overflow is for defining the overflow policy of a cache. Strong means that the cache never holds more element than is specified when calling create (see MAP_MAKER and SET_MAKER below and CACHE_MAP and CACHE_SET). Weak means that the cache may hold more elements than specified when calling create but that supernumerary elements may be collected by the Garbage Collector.

accounting is for defining the accounting policy of a cache.

Precise means that the cache counts its number of elements precisely: when an element is added, the count increases, when an element is removed, the count decreases, when an already present element is re-inserted the count is unchanged.

Sloppy means that the cache may count some elements that are not in the cache as still being held by the cache. As a result, adding a new element into the cache may lead to another element being removed even though the size limit was not actually reached.

The element-count of a Sloppy cache may become offset by one when an element is removed or when an element that is already present in the cache is re-added. This effect is cumulative and the element count can be off by more than one if multiple, say, removals happen.

The element-count eventually restores itself if enough new elements are added.

Additional details of the accounting in Sloppy caches are implementation dependent. Use Precise only if you use remove a lot, if you might insert the same key multiple times often, or if you need strong guarantees on the number of elements.

Note that when requesting a Sloppy cache, the library might give you a Precise cache if there is no additional runtime cost. In general, Sloppy caches are more efficient, but depending on the other parameters they might be only as-efficient-as (not strictly more efficient than) Precise caches.

A MAP_MAKER is a functor that instantiates CACHE_MAPs based on a given type and its associated hash function.

map_maker ~replacement ~overflow ~accounting is a first-class MAP_MAKER that instantiates caches with the policies specified by replacement, overflow, and accounting.

EmptyMap(H) is a map module but it only supports the empty map: a map with zero elements.

SingletonMap(H) is a map module but it only supports singleton maps: maps with at most one element.

A SET_MAKER is a functor that instantiates CACHE_SETs based on a given type and its associated hash function.

set_maker ~replacement ~overflow ~accounting is a first-class SET_MAKER that instantiates caches with the policies specified by replacement, overflow, and accounting.

EmptySet(H) is a set module but it only supports the empty set: a set with zero elements.

SingletonSey(H) is a set module but it only supports singleton sets: sets with at most one element.