Assignment should avoided in functional programming, but in clojure we often use let.
Is let just a way of being practical or is assignment not the same as using let? Should we not avoid assignment in functional programming?
Mutable state is generally against the core concepts of functional programming.
However, let merely binds a name to a value. If that value is immutable, there's no reason for it to be inconsistent with functional programming ideals.
One cannot say that assignment in general is against the idea of functional programming (FP).
A def expression is an assignment as well as a let expression. Giving names to things and procedures/functions is a mean of abstraction - and programming means to a big part applying abstraction on recurring problems.
Imperative style misuses assignments for mutation and thus creating/maintaining/mapping of (global) states. Mutation is not possible without assignment.
So FP aims against such kind of mutations not assignments per se.
Actually FP is not even aiming against mutation per se.
Even in functional languages mutation is in some situations required for performance reasons.
There is harmless mutation - mutation of variables which are anyway never ever again referred to for the rest of the program - e.g. because they appear only within a certain scope (e.g. within the scope of a let expression or a function definition). I tend to call them 'benign' mutations. And there is harmful mutation - mutation of variables to which later is referred to - mutation of variables which go on living outside the scope they were created in - thus constituting some kind of an unlimited state. I call them 'malign' mutations.
Actually it is also wrong to say FP avoids state alltogether.
Closures are actually constituting states in FP. Through closures functions can refer to hidden variables which keep a "memory"/state between different function calls. But they are applied in a very controlled manner.
Probably this is why defining FP is so difficult. Very quickly one has oversimplified something thereby causing more confusion than clarifying things.
Related
I want to compute some functions which are dependent on some variables (specific data on which I run the code) and global variables, which are unlikely to be changed, but I want to leave them user-tunable. Just to clarify with an example, suppose I want to declare the following function:
let multiplyByGain x =
x * gain
Where would you declare gain, being gain a global constant for the whole project. In a separate module with constants? That would couple the module with this code, though. Or would you use a curried version:
let multiblyByGain x gain =
x * gain
and then specialize for the specific values? But suppose you have many functions like that, you will have to inject gain to all of them (in a sort of linking module)?
In my specific problem this becomes more cumbersome because both x and gain are arrays which must have the same length, suppose I have to do a Array.zip, e.g.: what is the best practice in terms of functional design to address a global constant, as gain, in a general way?
P.S.: I have found this old postenter link description here, but addresses only a specific problem.
There is no single correct answer to the question and the best approach will depend on a variety of other constraints and requirements that you have. Also, it depends on whether you are asking specifically about F# or whether you are asking about functional programming more generally. I think there are three main points:
Keeping it simple.
Using a module that exposes gain as a global value, which has some initialization code to read configuration seems like a good default approach in F#. If this is changed only rarely (say, before you run the whole computation), then mutation is not going to cause you any troubles. You just need to be careful to avoid changing the values while some computation is still running. I think most F# programmers code tend to be quite pragmatic about this and this seems like the easiest thing to start with.
Unit testing.
If you want to unit ytest your multiplyByGain function with different gain as an argument, then you'll need some way of passing different values of gain to the function from your unit tests. In this case, having it as an additional parameter and using currying is nice, because you can just call it with other values of gain from your tests.
Functional programming.
Some functional language communities (especially Haskell and, sometimes, Scala) are way more strict about state. The purely functional way of keeping state would be to use monads (either the reader monad or some kind of free monad structure). This makes your code a lot more complicated (both conceptually and in terms of extra syntactic overhead), but it is a purely functional solution that eliminates state. In F#, this kind of approach is even more cumbersome, so it's not very common.
I'm aware that there are several definitions for functional programming. I think it's a nebulous category. My personal definition is something close to 'referential transparency'.
This question is not 'What is the definition of functional programming?'. The assumption is that what we know is as functional programming is a grab-bag of a couple of different ideas with some unclear boundaries.
Now the quite amazing book Structure and Interpretation of Computer Programs contains the following reference to the term functional programming.
Programming without any use of assignments, as we did throughout the first two chapters of this book, is accordingly known as functional programming.
To me that seemed odd.
My question is: Can 'programming without assignment' be considered within the definition of functional programming?
Yes, I think it can, though Scala and LISP users would probably call it a quite narrow definition. But while the one true definition of functional programming remains controversial, we can certainly infer something about the style of programming without assignments.
I assume here that by assignment, we mean mutation of a variable. Note that this is quite different from binding
int i;
i = 1; // overwrite whatever i is with 1
versus
let i = 1 in .... -- say that i is a name for an expression, here 1
Once you have no assignment, there is no mutation. When there is no mutation, certain constructs like loops become useless. For, every variable is just a name for an expression that is constant in the context of the loop, so the loop would run either never or forever. The only way to have "varying" variables is through application of a function to some value, which binds the argument name to that value within and for the lifetime of that function. The only way to have looping is recursion. This, in turn, makes functions eminently important, and as a bonus, all functions are by necessity pure since there is no mutation.
So, there you have it: Without mutation, all that is left is programming with pure functions (if we don't count different approaches of declarative programming without functions, but it turns out that this is less general and more specific for certain tasks (think SQL, Prolog)).
Now we can get some popcorn before we decide the question if programming (only) with pure functions is indeed functional programming. :)
Functional programming attempts to ensure freedom from side-effects when invoking functions. Passing a mutable object as a parameter that is NOT returned gives a developer the ability to modify a non-returned object. In other words, side-effects are possible. If you pass primitive or immutable types, you are free from this extra layer of complexity when reasoning about a program. So does good Functional Programming practice dictate anything when you have the choice between passing a mutable object vs passing primitive types?
I am aware of the following properties of PURE functional programming:
If all your types are immutable, it doesn't matter whether they are object types
The mutable object cannot exist outside the scope where it is expected to be mutated
but in reality when you are dealing with huge code bases that have existed prior to Functional Programming gaining a newfound respect, you will often be dealing with data structures that have no corresponding immutable representation, and code will be a mixture of functional and imperative styles.
(Background - I am exposing C++ logic via Java Native Interface and am wondering when to avoid passing objects, but I'm not looking for an answer that directly applies to this use case. I just want some help applying good programming practice in a situation such as this)
I think the only thing that functional programming has to say about this matter is that you should ideally wrap all impure stuff that you expose, in a monad, such as the famous IO monad.
But this is probably too radical for your users.
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 can enumerate many features of functional programming, but when my friend asked me Could you define functional programming for me? I couldn't.
I would say that the defining point of pure functional programming is that all computation is done in functions with no side effects. That is, functions take inputs and return values, but do not change any hidden state, In this paradigm, functions more closely model their mathematical cousins.
This was nailed down for me when I started playing with Erlang, a language with a write-once stack. However, it should be clarified that there is a difference between a programming paradigm, and a programming language. Languages that are generally referred to as functional provide a number of features that encourage or enforce the functional paradigm (e.g., Erlang with it's write-once stack, higher order functions, closures, etc.). However the functional programming paradigm can be applied in many languages (with varying degrees of pain).
A lot of the definitions so far have emphasized purity, but there are many languages that are considered functional that are not at all pure (e.g., ML, Scheme). I think the key properties that make a language "functional" are:
Higher-order functions. Functions are a built-in datatype no different from integers and booleans. Anonymous functions are easy to create and idiomatic (e.g., lambdas).
Everything is an expression. In imperative languages, a distinction is made between statements, which mutate state and affect control flow, and expressions, which yield values. In functional languages (even impure functional languages), expression evaluation is the fundamental unit of execution.
Given these two properties, you naturally get the behavior we think of as functional (e.g., expressing computations in terms of folds and maps). Eliminating mutable state is a way to make things even more functional.
From wikipedia:
In computer science, functional programming is a programming paradigm that treats computation as the evaluation of mathematical functions and avoids state and mutable data. It emphasizes the application of functions, in contrast with the imperative programming style that emphasizes changes in state.
Using a functional approach gives the following benefits:
Concurrent programming is much easier in functional languages.
Functions in FP can never cause side effects - this makes unit testing much easier.
Hot Code Deployment in production environments is much easier.
Functional languages can be reasoned about mathematically.
Lazy evaluation provides potential for performance optimizations.
More expressive - closures, pattern matching, advanced type systems etc. allow programmers to 'say what they mean' more readily.
Brevity - for some classes of program a functional solution is significantly more concise.
There is a great article with more detail here.
Being able to enumerate the features is more useful than trying to define the term itself, as people will use the term "functional programming" in a variety of contexts with many shades of meaning across a continuum, whereas the individual features have individually crisper definitions that are more universally agreed upon.
Below are the features that come to mind. Most people use the term "functional programming" to refer to some subset of those features (the most common/important ones being "purity" and "higher-order functions").
FP features:
Purity (a.k.a. immutability, eschewing side-effects, referential transparency)
Higher-order functions (e.g. pass a function as a parameter, return it as a result, define anonymous function on the fly as a lambda expression)
Laziness (a.k.a. non-strict evaluation, most useful/usable when coupled with purity)
Algebraic data types and pattern matching
Closures
Currying / partial application
Parametric polymorphism (a.k.a. generics)
Recursion (more prominent as a result of purity)
Programming with expressions rather than statements (again, from purity)
...
The more features from the above list you are using, the more likely someone will label what you are doing "functional programming" (and the first two features--purity and higher-order functions--are probably worth the most extra bonus points towards your "FP score").
I have to add that functional programming tends to also abstract control structures of your program as well as the domain - e.g., you no longer do a 'for loop' on some list of things, but you 'map' it with some function to produce the output.
i think functional programming is a state of mind as well as the definition given above.
There are two separate definitions:
The older definition (first-class functions) has been given by Chris Conway.
The newer definition (avoiding side effects like mutation) has been given by John Stauffer. This is more generally known as purely functional programming.
This is a source of much confusion...
It's like drawing a picture by using vectors instead of bitmaps - tell the painter how to change the picture instead of what the picture looks like at each step.
It's application of functions as opposed to changing the state.
I think John Stauffer mostly has the definition. I would also add that you need to be able to pass functions around. Essentially you need high order functions, meaning you can pass functions around easily (although passing blocks is good enough).
For example a very popular functional call is map. It is basically equivalent to
list is some list of items
OutList is some empty list
foreach item in list
OutList.append(function(item))
return OutList
so that code is expressed as map(function, list). The revolutionary concept is that function is a function. Javascript is a great example of a language with high order functions. Basically functions can be treated like a variable and passed into functions or returned from functions. C++ and C have function pointers which can be used similarly. .NET delegates can also be used similarly.
then you can think of all sorts of cool abstractions...
Do you have a function AddItemsInList, MultiplyItemsInList, etc..?
Each function takes (List) and returns a single result
You could create (note, many languages do not allow you to pass + around as a function but it seems the clearest way to express the concept)....
AggregateItemsInList(List, combinefunction, StepFunction)
Increment functions work on indexes...better would be to make them work on list using list operations like next and for incTwo next next if it exists....
function incNormal(x) {
return x + 1
}
function incTwo(x) {
return x + 2
}
AggregateItemsInList(List, +, incNormal)
Want to do every other item?
AggegateItemsInList(List, +, incTwo)
Want to multiply?
AggregateItemsInList(List, *, incNormal)
Want to add exam scores together?
function AddScores (studenta, studentb) {
return studenta.score + studentb.score
}
AggregateItemsInList(ListOfStudents, AddScores, incOne)
High order functions are a very powerful abstraction. Instead of having to write custom methods for numbers, strings, students, etc.. you have one aggregate method that loops through a list of anything and you just have to create the addition operation for each data type.