ImmuTable

This is a Lua library that allows the creation of lightweight immutable tables.

Build

This code has been tested with Lua 5.1.5, Lua 5.2.3, Lua 5.3.5, and LuaJIT 2.0.5. To build, simply make or for LuaJIT: make LUA=luajit (you can also optionally specify LUA_INC=<path to the directory containing lua.h and lauxlib.h> or LUA_BIN=<path to the directory containing the lua binary>).

Or, with luarocks: luarocks make immutable-table-scm-1.rockspec

Usage

Here's a simple implementation of a 2-d vector using immutable tables:

immutable = require "immutable"
Vec = immutable({"x","y"}, {
    name='Vector',
    len2=function(self)
        return self.x*self.x + self.y*self.y
    end,
    class_variable = "classvar",
    __add=function(self, other)
        local cls = getmetatable(self)
        return cls(self.x+other.x, self.y+other.y)
    end,
})
v = Vec(2, 3)
assert(v.x == 2 and v.y == 3)
also_v = Vec(2, 3)
assert(v == also_v)
t = {[v]='yep'}
assert(t[also_v] == 'yep')
assert(v + Vec(0,1) == Vec(2,4))
assert(#v == 2)
assert(v:len2() == 13)
assert(v.class_variable == "classvar")
assert(tostring(v) == 'Vector(x=2, y=3)')
assert(Vec:is_instance(v) and not Vec:is_instance({x=2,y=3}))
for k, v in pairs(v) do
    assert((k == 'x' and v == 2) or (k == 'y' and v == 3))
end
for i, v in ipairs(v) do
    assert((i == 1 and v == 2) or (i == 2 and v == 3))
end
NotVec = immutable({"x","y"})
assert(NotVec(1,2) ~= Vec(1,2))

Singleton recipe

Singletons are pretty straightforward:

Singleton = immutable()
assert(Singleton() == Singleton())

Or if you want methods/class variables:

DogSingleton = immutable(0, {name="DogSingleton", bark=function(self) print("woof") end})
DogSingleton():bark()

Tuples

If no field names are passed in, immutable() defaults to creating immutable tables that behave like Python's tuples:

local Tuple = immutable()
local t0 = Tuple()
local t1 = Tuple(1,2)
local t2 = Tuple(1,2,3,4,5)
assert(t0 == Tuple())
assert(({[t1]='yep'})[Tuple(1,2)])
assert(tostring(Tuple(1,2)) == "(1, 2)")

New Metamethods

This library adds support for two new metamethods: __new and __missing. __new is called when an instance is created. It takes as arguments the immutable class and all arguments the user passed in, and whatever values it returns are used to create the instance. This is pretty handy for default or derived values.

local Foo = immutable({"x","y","xy"}, {
    __new = function(cls, x, y)
        y = y or 3
        return x, y, x*y
    end
})
assert(Foo(2).xy == 6)

__missing is similar to __index, except that it only gets called when accessing a key that is neither one of the immutable class's instance keys, nor one of the keys in the class table.

local Foo = immutable({"x","y"}, {
    classvar = 23,
    __missing = function(self, key)
        return "MISSING"
    end
})
local f = Foo(1, nil)
assert(f.x == 1 and f.y == nil and f.classvar == 23 and f.asdf == "MISSING")

General purpose immutable table recipe

Using tuples, you can make a function that returns an immutable version of a table with arbitrary keys, though it is a little bit hacky.

local Tuple = immutable()
local immutable_classes = {}
Immutable = function(t)
    local keys = {}
    for k,_ in pairs(t) do keys[#keys+1] = k end
    keys = Tuple(unpack(keys))
    if not immutable_classes[keys] then
        immutable_classes[keys] = immutable(keys, {name="Immutable"})
    end
    return immutable_classes[keys]:from_table(t)
end
assert(Immutable{x=1} == Immutable{x=1})
assert(Immutable{a=1,b=2,c=3} == Immutable{a=1,b=2,c=3})

Performance

This library is pretty dang fast, but it's still slower than native Lua tables. Based on my local testing, immutable tables add a couple nanoseconds to table operations in the worst case scenario. In LuaJIT, there is a bigger performance discrepancy because regular tables are more heavily optimized in LuaJIT. Your mileage may vary, but I'd say that immutable tables will probably never be a performance bottleneck for your program, especially if you use them in place of code that already used a constructor function and metatables. In some cases, immutable tables may also help reduce your program's memory footprint (if your program has many duplicate objects in memory) and may even improve speed (e.g. if your program uses a lot of deep equality checks). Don't trust this paragraph though! If in doubt, profile your code!

Implementation details

You can read more about the implementation details in the implementation documentation.