I am experimenting with using JNLua's javavm module to connect with and extend a Java library (JAR). So far I am super impressed with how easy it is to pass Java objects back and forth between Lua and Java- seemlessness.
Now I am interested to extend these Java objects in LUA. In my naive approach I've wrapped the Java object in a Lua class with the intent of extending that objects API i.e. adding methods to it. But I don't want to have to recreate, within the wrapper, all of the Java objects methods. It seems like I should be able to inherit from the Java object so that when a method is missing from my wrapper Lua will look for it in the Java object which is a member of the wrapped class. I've tried adapting the examples shown in Inheritance but this is a slightly trickier thing to set up, given that I'm dealing with a Java object. Thoughts?
I found my answer in the below SO question
Add members dynamically to a class using Lua + SWIG
I needed to realize I was dealing with a UserData object, not a table- no way to add members
I needed some metatable kung-fu
The below code has the effect of allowing me to extend (add methods) a Java object.
function Model:new (model)
o = {}
WrapObject(Model, o, model)
self.__index = self
self.model = model or nil
return o
end
function WrapObject(class, object, userData)
local wrapper_metatable = {}
function wrapper_metatable.__index(self, key)
local ret = rawget(class, key)
if(not ret) then
ret = userData[key]
if(type(ret) == "function") then
return function(self, ...)
return ret(userData, ...)
end
else
return ret
end
else
return ret
end
end
setmetatable(object, wrapper_metatable)
return object
end
function Model:Test ()
name = self:GetFullName()
fileName = self:GetFileName()
ret = name .. fileName
print("It's a test!!")
return ret
end
Related
Suppose if I had the following Employee struct:
mutable struct Employee
_id::Int64
_first_name::String
_last_name::String
function Employee(_id::Int64,_first_name::String,_last_name::String)
# validation left out.
new(_id,_first_name,_last_name)
end
end
If I wanted to implement my own setproperty!() I can do:
function setproperty!(value::Employee,name::Symbol,x)
if name == :_id
if !isa(x,Int64)
throw(ErrorException("ID type is invalid"))
end
setfield!(value,:_id,x)
end
if name == :_first_name
if is_white_space(x)
throw(ErrorException("First Name cannot be blank!"))
end
setfield!(value,:_first_name,x)
end
if name == :_last_name
if is_white_space(x)
throw(ErrorException("Last Name cannot be blank!"))
end
setfield!(value,:_last_name,x)
end
end
Have I implemented setproperty!() correctly?
The reason why I use setfield!() for _first_name and _last_name, is because if I do:
if name == :_first_name
setproperty!(value,:_first_name,x) # or value._first_name = x
end
it causes a StackOverflowError because it's recursively using setproperty!().
I don't really like the use of setproperty!(), because as the number of parameters grows, so would setproperty!().
It also brings to mind using Enum and if statements (only we've switched Enum with Symbol).
One workaround I like, is to document that the fields are meant to be private and use the provided setter to set the field:
function set_first_name(obj::Employee,first_name::AbstractString)
# Validate first_name before assigning it.
obj._first_name = first_name
end
The function is smaller and has a single purpose.
Of course this doesn't prevent someone from using setproperty!(), setfield!() or value._field_name = x, but if you're going to circumvent the provided setter then you'll have the handle the consequences for doing it.
Of course this doesn't prevent someone from using setproperty!(), setfield!() or value._field_name = x, but if you're going to circumvent the provided setter then you'll have the handle the consequences for doing it.
I would recommend you to do this, defining getter,setter functions, instead of overloading getproperty/setproperty!. on the wild, the main use i saw on overloading getproperty/setproperty! is when fields can be calculated from the data. for a getter/setter pattern, i recommend you to use the ! convention:
getter:
function first_name(value::Employee)
return value._first_name
end
setter:
function first_name!(value::Employee,text::String)
#validate here
value._first_name = text
return value._first_name
end
if your struct is mutable, it could be that some fields are uninitialized. you could add a getter with default, by adding a method:
function first_name(value::Employee,default::String)
value_stored = value._first_name
if is_initialized(value_stored) #define is_initialized function
return value_stored
else
return default
end
end
with a setter/getter with default, the only difference between first_name(val,text) and first_name!(val,text) would be the mutability of val, but the result is the same. useful if you are doing mutable vs immutable functions. as you said it, the getproperty/setproperty! is cumbersome in comparison. If you want to disallow accessing the fields, you could do:
Base.getproperty(val::Employee,key::Symbol) = throw(error("use the getter functions instead!")
Base.setproperty!(val::Employee,key::Symbol,x) = throw(error("use the setter functions instead!")
Disallowing the syntax sugar of val.key and val.key = x. (if someone really want raw access, there is still getfield/setfield!, but they were warned.)
Finally, i found this recomendation in the julia docs, that recommends getter/setter methods over direct field access
https://docs.julialang.org/en/v1/manual/style-guide/#Prefer-exported-methods-over-direct-field-access
I am seeing that Julia explicitly does NOT do classes... and I should instead embrace mutable structs.. am I going down the correct path here?? I diffed my trivial example against an official flux library but cannot gather how do I reference self like a python object.. is the cleanest way to simply pass the type as a parameter in the function??
Python
# Dense Layer
class Layer_Dense
def __init__(self, n_inputs, n_neurons):
self.weights = 0.01 * np.random.randn(n_inputs, n_neurons)
self.biases = np.zeros((1, n_neurons))
def forward(self, inputs):
pass
My JuliaLang version so far
mutable struct LayerDense
num_inputs::Int64
num_neurons::Int64
weights
biases
end
function forward(layer::LayerDense, inputs)
layer.weights = 0.01 * randn(layer.num_inputs, layer.num_neurons)
layer.biases = zeros((1, layer.num_neurons))
end
The flux libraries version of a dense layer... which looks very different to me.. and I do not know what they're doing or why.. like where is the forward pass call, is it here in flux just named after the layer Dense???
source : https://github.com/FluxML/Flux.jl/blob/b78a27b01c9629099adb059a98657b995760b617/src/layers/basic.jl#L71-L111
struct Dense{F, M<:AbstractMatrix, B}
weight::M
bias::B
σ::F
function Dense(W::M, bias = true, σ::F = identity) where {M<:AbstractMatrix, F}
b = create_bias(W, bias, size(W,1))
new{F,M,typeof(b)}(W, b, σ)
end
end
function Dense(in::Integer, out::Integer, σ = identity;
initW = nothing, initb = nothing,
init = glorot_uniform, bias=true)
W = if initW !== nothing
Base.depwarn("keyword initW is deprecated, please use init (which similarly accepts a funtion like randn)", :Dense)
initW(out, in)
else
init(out, in)
end
b = if bias === true && initb !== nothing
Base.depwarn("keyword initb is deprecated, please simply supply the bias vector, bias=initb(out)", :Dense)
initb(out)
else
bias
end
return Dense(W, b, σ)
end
This is an equivalent of your Python code in Julia:
mutable struct Layer_Dense
weights::Matrix{Float64}
biases::Matrix{Float64}
Layer_Dense(n_inputs::Integer, n_neurons::Integer) =
new(0.01 * randn(n_inputs, n_neurons),
zeros((1, n_neurons)))
end
forward(ld::Layer_Dense, inputs) = nothing
What is important here:
here I create an inner constructor only, as outer constructor is not needed; as opposed in the Flux.jl code you have linked the Dense type defines both inner and outer constructors
in python forward function does not do anything, so I copied it in Julia (your Julia code worked a bit differently); note that instead of self one should pass an instance of the object to the function as the first argument (and add ::Layer_Dense type signature so that Julia knows how to correctly dispatch it)
similarly in Python you store only weights and biases in the class, I have reflected this in the Julia code; note, however, that for performance reasons it is better to provide an explicit type of these two fields of Layer_Dense struct
like where is the forward pass call
In the code you have shared only constructors of Dense object are defined. However, in the lines below here and here the Dense type is defined to be a functor.
Functors are explained here (in general) and in here (more specifically for your use case)
I have a script written in Lua 5.1 that imports third-party module and calls some functions from it. I would like to get a list of function calls from a module with their arguments (when they are known before execution).
So, I need to write another script which takes the source code of my first script, parses it, and extracts information from its code.
Consider the minimal example.
I have the following module:
local mod = {}
function mod.foo(a, ...)
print(a, ...)
end
return mod
And the following driver code:
local M = require "mod"
M.foo('a', 1)
M.foo('b')
What is the better way to retrieve the data with the "use" occurrences of the M.foo function?
Ideally, I would like to get the information with the name of the function being called and the values of its arguments. From the example code above, it would be enough to get the mapping like this: {'foo': [('a', 1), ('b')]}.
I'm not sure if Lua has functions for reflection to retrieve this information. So probably I'll need to use one of the existing parsers for Lua to get the complete AST and find the function calls I'm interested in.
Any other suggestions?
If you can not modify the files, you can read the files into a strings then parse mod file and find all functions in it, then use that information to parse the target file for all uses of the mod library
functions = {}
for func in modFile:gmatch("function mod%.(%w+)") do
functions[func] = {}
end
for func, call in targetFile:gmatch("M%.(%w+)%(([^%)]+)%)") do
args = {}
for arg in string.gmatch(call, "([^,]+)") do
table.insert(args, arg)
end
table.insert(functions[func], args)
end
Resulting table can then be serialized
['foo'] = {{"'a'", " 1"}, {"'b'"}}
3 possible gotchas:
M is not a very unique name and could vary possibly match unintended function calls to another library.
This example does not handle if there is a function call made inside the arg list. e.g. myfunc(getStuff(), true)
The resulting table does not know the typing of the args so they are all save as strings representations.
If modifying the target file is an option you can create a wrapper around your required module
function log(mod)
local calls = {}
local wrapper = {
__index = function(_, k)
if mod[k] then
return function(...)
calls[k] = calls[k] or {}
table.insert(calls[k], {...})
return mod[k](...)
end
end
end,
}
return setmetatable({},wrapper), calls
end
then you use this function like so.
local M, calls = log(require("mod"))
M.foo('a', 1)
M.foo('b')
If your module is not just functions you would need to handle that in the wrapper, this wrapper assumes all indexes are a function.
after all your calls you can serialize the calls table to get the history of all the calls made. For the example code the table looks like
{
['foo'] = {{'a', 1}, {'b'}}
}
I have a question on Java 8 Functional Programming. I am trying to achieve something using functional programming, and need some guidance on how to do it.
My requirement is to wrap every method execution inside timer function which times the method execution. Here's the example of timer function and 2 functions I need to time.
timerMethod(String timerName, Function func){
timer.start(timerName)
func.apply()
timer.stop()
}
functionA(String arg1, String arg2)
functionB(int arg1, intArg2, String ...arg3)
I am trying to pass functionA & functionB to timerMethod, but functionA & functionB expects different number & type of arguments for execution.
Any ideas how can I achieve it.
Thanks !!
you should separate it into two things by Separation of Concerns to make your code easy to use and maintaining. one is timing, another is invoking, for example:
// v--- invoking occurs in request-time
R1 result1 = timerMethod("functionA", () -> functionA("foo", "bar"));
R2 result2 = timerMethod("functionB", () -> functionB(1, 2, "foo", "bar"));
// the timerMethod only calculate the timing-cost
<T> T timerMethod(String timerName, Supplier<T> func) {
timer.start(timerName);
try {
return func.get();
} finally {
timer.stop();
}
}
IF you want to return a functional interface rather than the result of that method, you can done it as below:
Supplier<R1> timingFunctionA =timerMethod("A", ()-> functionA("foo", "bar"));
Supplier<R2> timingFunctionB =timerMethod("B", ()-> functionB(1, 2, "foo", "bar"));
<T> Supplier<T> timerMethod(String timerName, Supplier<T> func) {
// v--- calculate the timing-cost when the wrapper function is invoked
return () -> {
timer.start(timerName);
try {
return func.get();
} finally {
timer.stop();
}
};
}
Notes
IF the return type of all of your functions is void, you can replacing Supplier with Runnable and then make the timerMethod's return type to void & remove return keyword from timerMethod.
IF some of your functions will be throws a checked exception, you can replacing Supplier with Callable & invoke Callable#call instead.
Don't hold onto the arguments and then pass them at the last moment. Pass them immediately, but delay calling the function by wrapping it with another function:
Producer<?> f1 =
() -> functionA(arg1, arg2);
Producer<?> f2 =
() -> functionB(arg1, arg2, arg3);
Here, I'm wrapping each function call in a lambda (() ->...) that takes 0 arguments. Then, just call them later with no arguments:
f1()
f2()
This forms a closure over the arguments that you supplied in the lambda, which allows you to use the variables later, even though normally they would have been GC'd for going out of scope.
Note, I have a ? as the type of the Producer since I don't know what type your functions return. Change the ? to the return type of each function.
Introduction
The other answers show how to use a closure to capture the arguments of your function, no matter its number. This is a nice approach and it's very useful, if you know the arguments in advance, so that they can be captured.
Here I'd like to show two other approaches that don't require you to know the arguments in advance...
If you think it in an abstract way, there are no such things as functions with multiple arguments. Functions either receive one set of values (aka a tuple), or they receive one single argument and return another function that receives another single argument, which in turn returns another one-argument function that returns... etc, with the last function of the sequence returning an actual result (aka currying).
Methods in Java might have multiple arguments, though. So the challenge is to build functions that always receive one single argument (either by means of tuples or currying), but that actually invoke methods that receive multiple arguments.
Approach #1: Tuples
So the first approach is to use a Tuple helper class and have your function receive one tuple, either a Tuple2 or Tuple3:
So, the functionA of your example might receive one single Tuple2<String, String> as an argument:
Function<Tuple2<String, String>, SomeReturnType> functionA = tuple ->
functionA(tuple.getFirst(), tuple.getSecond());
And you could invoke it as follows:
SomeReturnType resultA = functionA.apply(Tuple2.of("a", "b"));
Now, in order to decorate the functionA with your timerMethod method, you'd need to do a few modifications:
static <T, R> Function<T, R> timerMethod(
String timerName,
Function<? super T, ? extends R> func){
return t -> {
timer.start(timerName);
R result = func.apply(t);
timer.stop();
return result;
};
}
Please note that you should use a try/finally block to make your code more robust, as shown in holi-java's answer.
Here's how you might use your timerMethod method for functionA:
Function<Tuple2<String, String>, SomeReturnType> timedFunctionA = timerMethod(
"timerA",
tuple -> functionA(tuple.getFirst(), tuple.getSecond());
And you can invoke timedFunctionA as any other function, passing it the arguments now, at invocation time:
SomeReturnType resultA = timedFunctionA.apply(Tuple2.of("a", "b"));
You can take a similar approach with the functionB of your example, except that you'd need to use a Tuple3<Integer, Integer, String[]> for the argument (taking care of the varargs arguments).
The downside of this approach is that you need to create many Tuple classes, i.e. Tuple2, Tuple3, Tuple4, etc, because Java lacks built-in support for tuples.
Approach #2: Currying
The other approach is to use a technique called currying, i.e. functions that accept one single argument and return another function that accepts another single argument, etc, with the last function of the sequence returning the actual result.
Here's how to create a currified function for your 2-argument method functionA:
Function<String, Function<String, SomeReturnType>> currifiedFunctionA =
arg1 -> arg2 -> functionA(arg1, arg2);
Invoke it as follows:
SomeReturnType result = currifiedFunctionA.apply("a").apply("b");
If you want to decorate currifiedFunctionA with the timerMethod method defined above, you can do as follows:
Function<String, Function<String, SomeReturnType>> timedCurrifiedFunctionA =
arg1 -> timerMethod("timerCurryA", arg2 -> functionA(arg1, arg2));
Then, invoke timedCurrifiedFunctionA exactly as you'd do with any currified function:
SomeReturnType result = timedCurrifiedFunctionA.apply("a").apply("b");
Please note that you only need to decorate the last function of the sequence, i.e. the one that makes the actual call to the method, which is what we want to measure.
For the method functionB of your example, you can take a similar approach, except that the type of the currified function would now be:
Function<Integer, Function<Integer, Function<String[], SomeResultType>>>
which is quite cumbersome, to say the least. So this is the downside of currified functions in Java: the syntax to express their type. On the other hand, currified functions are very handy to work with and allow you to apply several functional programming techniques without needing to write helper classes.
I'm wrapping a C++ framework with boost::python and I need to make a C++ method overrideable in python. This is a hook method, which is needed by the framework and has a default implementation in C++, which iterates through a list (passed as parameter) and performs a choice. The problems arise because the choice is stated by returning a pointer to the chosen element (an iterator, in fact), but I can't find a way to return a C++ pointer as a result of a python function. Can anyone help?
Thanks
This is most certainly doable, but you don't really have enough details. What you really need to do is create a c++ function that calls your python function, proceses the python result and returns a c++ result. To paraphrase (let's assume I have a boost object called func that points to some python function that parses a string and returns an int):
using boost::python;
A* test(const std::string &foo) {
object module = import("mymodule");
object func = module.attr("myfunc");
// alternatively, you could set the function by passing it as an argument
// to a c++ function that you have wrapped
object result = func(foo);
int val = extract<int>(result);
return new A(val); // Assumes that you've wrapped A.
}
// file: https://github.com/layzerar/box2d-py/blob/master/python/world.cpp
struct b2ContactFilter_W: b2ContactFilter, wrapper<b2ContactFilter>
{
bool ShouldCollide(b2Fixture* fixtureA, b2Fixture* fixtureB)
{
override func = this->get_override("ShouldCollide");
if (func)
{
return func(ref(fixtureA), ref(fixtureB)); //ref is boost::ref
}
return b2ContactFilter::ShouldCollide(fixtureA, fixtureB);
}
bool ShouldCollideDefault(b2Fixture* fixtureA, b2Fixture* fixtureB)
{
return b2ContactFilter::ShouldCollide(fixtureA, fixtureB);
}
};
class_<b2ContactFilter_W, boost::noncopyable>("b2ContactFilter")
.def("ShouldCollide", &b2ContactFilter::ShouldCollide, &b2ContactFilter_W::ShouldCollideDefault)
;
Is this what you need ?