MnemoniK

Simple memoization extension function for Kotlin

Rationale

Suppose you have a performance-intensive function that you must call repeatedly. A common solution is to build an internal cache (...) Memoization is a feature built into a programming language that enables automatic caching of recurring function-return values.

Functional Thinking - Neal Ford

Kotlin doesn't have yet any similar feature in it's tools. Although it might have it at some point I wanted to experiment a bit with this technique so that's why I created the lib.

Important

Functions must be pure for the caching technique to work.

A pure function is one that has no side effects: it references no other mutable class fields, doesn't set any values other than the return value, and relies only on the parameters for input.

In other words, you can reuse cached results successfully only if the function reliably returns the same values for a given set of parameters.

Also, when passing or returning Objects, make sure to implement both equals and hashcode for the cache to work properly.

Usage

Having a function like:

fun anExpensiveFun(someArg: Int, someOtherArg: Boolean): String = { /*...*/ }

You can create a memoized version of it by just calling an extension function over its reference like this:

val memoized = ::anExpensiveFun.memoize()

Now memoized is the same function as anExpensiveFun but is wrapped in a lambda that contains an internal cache, meaning that the first call to:

memoized(5, true)

Will just execute the function and return the value. But a second call with the same arguments will retrieve the previous value from cache.

Note that we're storing values in a memory cache, so try to have that in consideration when doing a relatively big amount of calls to your memoized function or if you use big objects as parameters or return type.

If you want to specify how big the cache has to be you can do it like the following:

val memoized = ::anExpensiveFun.memoize(50)

By default the cache size is initialized with 256.

By default HashMap and ConcurrentHashMap are used as caches but you can also pass any MutableMap and ConcurrentMap instances which allows custom control of the cache.

val map = ConcurrentHashMap<Int, Boolean>(50)
val memoized = ::anExpensiveFun.memoize(cache = map)

// clear the cache at the end
map.clear

Note: The same approach also works for suspend functions.

Limitations

Currently this library only supports up to 5 function parameters.

Note that the memoization might not be thread safe for the first call, subsequent calls are safe as they will simply retrieve from cache.

Distribution

Add as a dependency to your build.gradle with Jitpack

License

MIT License

Copyright (c) 2022 aballano

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