I have been studying functional programming and one of the requirements is that they are pure in the sense that they only return the computed value and not touch anything else or throw exceptions, they don't also access shared mutable objects - this makes them inherently thread safe.
So then what would be the correct approach to implement a pure function that takes objects as arguments rather than primitive values. Would I have to deep clone them when passing to a function ?
If the function is a pure function, i.e. does not modify existing objects, whether they are passed as parameters or lying around somewhere else, there is no sense is copying or cloning the argument objects.
You could also see it the other way round: if cloning arguments is necessary, the invoked code is not functional and cloning the arguments doesn’t turn it into functional code, it’s actually working around a design flaw.
In the best case, you would be working with immutable objects which prevent modifications intrinsically, however, using immutable objects doesn’t change the way how the functional code should behave, they just enforce some aspects of it. When a particular class does not offer immutable objects, you can still use it in the right way, without the need to re-implement it in an immutable way.
Generally, it is not a good idea to develop your code assuming that all other code will misbehave and that it was your code’s task to solve the issues of that misbehavior.
The objects should ideally be immutable. Immutability and functional programming go hand-to-hand.
If having all immutable objects isn't feasible, yes, you would ideally need to make deep copies of everything to ensure changes to them don't effect anything else outside of the function.
Related
Coming from Wolfram Mathematica, I like the idea that whenever I pass a variable to a function I am effectively creating a copy of that variable. On the other hand, I am learning that in Julia there are the notions of mutable and immutable types, with the former passed by reference and the latter passed by value. Can somebody explain me the advantage of such a distinction? why arrays are passed by reference? Naively I see this as a bad aspect, since it creates side effects and ruins the possibility to write purely functional code. Where I am wrong in my reasoning? is there a way to make immutable an array, such that when it is passed to a function it is effectively passed by value?
here an example of code
#x is an in INT and so is immutable: it is passed by value
x = 10
function change_value(x)
x = 17
end
change_value(x)
println(x)
#arrays are mutable: they are passed by reference
arr = [1, 2, 3]
function change_array!(A)
A[1] = 20
end
change_array!(arr)
println(arr)
which indeed modifies the array arr
There is a fair bit to respond to here.
First, Julia does not pass-by-reference or pass-by-value. Rather it employs a paradigm known as pass-by-sharing. Quoting the docs:
Function arguments themselves act as new variable bindings (new
locations that can refer to values), but the values they refer to are
identical to the passed values.
Second, you appear to be asking why Julia does not copy arrays when passing them into functions. This is a simple one to answer: Performance. Julia is a performance oriented language. Making a copy every time you pass an array into a function is bad for performance. Every copy operation takes time.
This has some interesting side-effects. For example, you'll notice that a lot of the mature Julia packages (as well as the Base code) consists of many short functions. This code structure is a direct consequence of near-zero overhead to function calls. Languages like Mathematica and MatLab on the other hand tend towards long functions. I have no desire to start a flame war here, so I'll merely state that personally I prefer the Julia style of many short functions.
Third, you are wondering about the potential negative implications of pass-by-sharing. In theory you are correct that this can result in problems when users are unsure whether a function will modify its inputs. There were long discussions about this in the early days of the language, and based on your question, you appear to have worked out that the convention is that functions that modify their arguments have a trailing ! in the function name. Interestingly, this standard is not compulsory so yes, it is in theory possible to end up with a wild-west type scenario where users live in a constant state of uncertainty. In practice this has never been a problem (to my knowledge). The convention of using ! is enforced in Base Julia, and in fact I have never encountered a package that does not adhere to this convention. In summary, yes, it is possible to run into issues when pass-by-sharing, but in practice it has never been a problem, and the performance benefits far outweigh the cost.
Fourth (and finally), you ask whether there is a way to make an array immutable. First things first, I would strongly recommend against hacks to attempt to make native arrays immutable. For example, you could attempt to disable the setindex! function for arrays... but please don't do this. It will break so many things.
As was mentioned in the comments on the question, you could use StaticArrays. However, as Simeon notes in the comments on this answer, there are performance penalties for using static arrays for really big datasets. More than 100 elements and you can run into compilation issues. The main benefit of static arrays really is the optimizations that can be implemented for smaller static arrays.
Another package-based options suggested by phipsgabler in the comments below is FunctionalCollections. This appears to do what you want, although it looks to be only sporadically maintained. Of course, that isn't always a bad thing.
A simpler approach is just to copy arrays in your own code whenever you want to implement pass-by-value. For example:
f!(copy(x))
Just be sure you understand the difference between copy and deepcopy, and when you may need to use the latter. If you're only working with arrays of numbers, you'll never need the latter, and in fact using it will probably drastically slow down your code.
If you wanted to do a bit of work then you could also build your own array type in the spirit of static arrays, but without all the bells and whistles that static arrays entails. For example:
struct MyImmutableArray{T,N}
x::Array{T,N}
end
Base.getindex(y::MyImmutableArray, inds...) = getindex(y.x, inds...)
and similarly you could add any other functions you wanted to this type, while excluding functions like setindex!.
The redux best practices says not to mix plain javascript object with immutablejs objects. I'm trying my hand at functional programming and it seems like the monads require the computations/values to be stored inside an object, or some container of sorts. AFAIK immutablejs maps can't store methods. Are there any issues with using FP libraries like Folktale? I haven't noticed any noticeable issues with the basic todo app (which is all I can try at the moment), so I'm hoping for some clarification on immutablejs best practices, hopefully FP leaning.
Never mix plain JavaScript objects with Immutable.JS
Ok, I feel like a fool. I read the linked article again and saw that it's not about performance, but to avoid confusion as to when data passed is immutable or a pojo. Here's the relevant section from the article
In fact, sometimes you might be tempted to put a normal JavaScript object inside an Immutable map. Don't do this. Mixing immutable and mutable state in the same object will reap confusion.
http://jlongster.com/Using-Immutable-Data-Structures-in-JavaScript
Scala claims than OO and FP can be combined.
I wonder how this can be achieved in practice. I mean object can change, so making them immutable means i have to create a new object whenever something changes right? This doesn't seem too effective to me.
By the way, if i make external reference to an object property from a function, doesn't it hurts referential transparency?
Don't think of this as one paradigm imposing restrictions on the other but as how can one take the best of both paradigms.
As a simple example:
Objects have functions which can be internal to an object. Now the internal functions can be immutable within an object and those results of a function can be used to change the state of a object.
Thinking at a different level one can use functions to create a library that can be used by objects.
How I like to make the best of both is I tend to make libraries (modules) for the more abstract processing using a functional language and then use OO languages for the layers closer to human and external processing. This is not a hard and fast rule but a guideline from where I start.
In a purely functional language, couldn't one still define an "assignment" operator, say, "<-", such that the command, say, "i <- 3", instead of directly assigning the immutable variable i, would create a copy of the entire current call stack, except replacing i with 3 in the new call stack, and executing the new call stack from that point onward? Given that no data actually changed, wouldn't that still be considered "purely functional" by definition? Of course the compiler would simply make the optimization to simply assign 3 to i, in which case what's the difference between imperative and purely functional?
Purely functional languages, such as Haskell, have ways of modelling imperative languages, and they are not shy about admitting it either. :)
See http://www.haskell.org/tutorial/io.html, in particular 7.5:
So, in the end, has Haskell simply
re-invented the imperative wheel?
In some sense, yes. The I/O monad
constitutes a small imperative
sub-language inside Haskell, and thus
the I/O component of a program may
appear similar to ordinary imperative
code. But there is one important
difference: There is no special
semantics that the user needs to deal
with. In particular, equational
reasoning in Haskell is not
compromised. The imperative feel of
the monadic code in a program does not
detract from the functional aspect of
Haskell. An experienced functional
programmer should be able to minimize
the imperative component of the
program, only using the I/O monad for
a minimal amount of top-level
sequencing. The monad cleanly
separates the functional and
imperative program components. In
contrast, imperative languages with
functional subsets do not generally
have any well-defined barrier between
the purely functional and imperative
worlds.
So the value of functional languages is not that they make state mutation impossible, but that they provide a way to allow you to keep the purely functional parts of your program separate from the state-mutating parts.
Of course, you can ignore this and write your entire program in the imperative style, but then you won't be taking advantage of the facilities of the language, so why use it?
Update
Your idea is not as flawed as you assume. Firstly, if someone familiar only with imperative languages wanted to loop through a range of integers, they might wonder how this could be achieved without a way to increment a counter.
But of course instead you just write a function that acts as the body of the loop, and then make it call itself. Each invocation of the function corresponds to an "iteration step". And in the scope of each invocation the parameter has a different value, acting like an incrementing variable. Finally, the runtime can note that the recursive call appears at the end of the invocation, and so it can reuse the top of the function-call stack instead of growing it (tail call). Even this simple pattern has almost all of the flavour of your idea - including the compiler/runtime quietly stepping in and actually making mutation occur (overwriting the top of the stack). Not only is it logically equivalent to a loop with a mutating counter, but in fact it makes the CPU and memory do the same thing physically.
You mention a GetStack that would return the current stack as a data structure. That would indeed be a violation of functional purity, given that it would necessarily return something different each time it was called (with no arguments). But how about a function CallWithStack, to which you pass a function of your own, and it calls back to your function and passes it the current stack as a parameter? That would be perfectly okay. CallCC works a bit like that.
Haskell doesn't readily give you ways to introspect or "execute" call stacks, so I wouldn't worry too much about that particular bizarre scheme. However in general it is true that one can subvert the type system using unsafe "functions" such as unsafePerformIO :: IO a -> a. The idea is to make it difficult, not impossible, to violate purity.
Indeed, in many situations, such as when making Haskell bindings for a C library, these mechanisms are quite necessary... by using them you are removing the burden of proof of purity from the compiler and taking it upon yourself.
There is a proposal to actually guarantee safety by outlawing such subversions of the type system; I'm not too familiar with it, but you can read about it here.
Immutability is a property of the language, not of the implementation.
An operation a <- expr that copies data is still an imperative operation, if values that refer to the location a appear to have changed from the programmers point of view.
Likewise, a purely functional language implementation may overwrite and reuse variables to its heart's content, as long as each modification is invisible to the programmer. For example, the map function can in principle overwrite a list instead of creating a new, whenever the language implementation can deduce that the old list won't be needed anywhere.
I was recently watching a webcast on Clojure. In it the presenter made a comment in the context of discussing the FP nature of Clojure which went something like (I hope I don't misrepresent him) "Mock objects are mocking you".
I also heard a similar comment a while back when I watched a webcast when Microsoft's Reactive Framework was starting to appear . It went something like "Mock objects are for those who don't know math")
Now I know that both comments are jokes/tongue-in-cheek etc etc (and probably badly paraphrased), but underlying them is obviously something conceptual which I don't understand as I haven't really made the shift to the FP paradigm.
So, I would be grateful if someone could explain whether FP does in fact render mocking redundant and if so how.
In pure FP you have referentially transparent functions that compute the same output every time you call them with the same input. All the state you need must therefore be explicitly passed in as parameters and out as function results, there are no stateful objects that are in some way "hidden behind" the function you call. This, however, is, what your mock objects usually do: simulate some external, hidden state or behavior that your subject under test relies on.
In other words:
OO: Your objects combine related state and behavior.
Pure FP: State is something you pass between functions that by themselves are stateless and only rely on other stateless functions.
I think the important thing to think about is the idea of using tests help you to structure your code. Mocks are really about deferring decisions you don't want to take now (and a widely misunderstood technique). Instead of object state, consider partial functions. You can write a function that takes defers part of its behaviour to a partial function that's passed in. In a unit test, that could be a fake implementation that lets you just focus on the code in hand. Later, you compose your new code with a real implementation to build the system.
Actually, when we were developing the idea of Mocks, I always thought of Mocks this way. The object part was incidental.