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Some Advice: Functional Programming with Side Effects
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F# stems from a tradition in programming languages where the emphasis has been on declarative and functional approaches to programming in which state is made explicit, largely by passing extra parameters. Many F# programmers use functional programming techniques first before turning to their imperative alternatives, and we encourage you to do the same, for all the reasons listed at the start of this chapter. However, F# also integrates imperative and functional programming together in a powerful way. F# is actually an extremely succinct imperative programming language! Furthermore, in some cases, no good functional techniques exist to solve a problem, or those that do are too experimental for production use. This means that in practice, using imperative constructs and libraries is common in F#: for example, many of the examples you saw in s 2 and 3 used side effects to report their results or to create GUI components. Regardless, we still encourage you to think functionally, even about your imperative programming. In particular, it s always helpful to be aware of the potential side effects of your overall program and the characteristics of those side effects. The following sections describe five ways to help tame and reduce the use of side effects in your programs.
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CHAPTER 4 INTRODUCING IMPERATIVE PROGRAMMING
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Consider Replacing Mutable Locals and Loops with Recursion
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When imperative programmers begin to use F#, they frequently use mutable local variables or reference cells heavily as they translate code fragments from their favorite imperative language into F#. The resulting code often looks very bad. Over time, they learn to avoid many uses of mutable locals. For example, consider the following (naive) implementation of factorization, transliterated from C code: let factorizeImperative n = let mutable primefactor1 = 1 let mutable primefactor2 = n let mutable i = 2 let mutable fin = false while (i < n && not fin) do if (n % i = 0) then primefactor1 <- i primefactor2 <- n / i fin <- true i <- i + 1 if (primefactor1 = 1) then None else Some (primefactor1, primefactor2) This code can be replaced by the following use of an inner recursive function: let factorizeRecursive n = let rec find i = if i >= n then None elif (n % i = 0) then Some(i,n / i) else find (i+1) find 2 The second code is not only shorter but also uses no mutation, which makes it easier to reuse and maintain. You can also see that the loop terminates (i is increasing toward n) and see the two exit conditions for the function (i >= n and n % i = 0). Note that the state i has become an explicit parameter.
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Separate Pure Computation from Side-Effecting Computations
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Where possible, separate out as much of your computation as possible using side-effect-free functional programming. For example, sprinkling printf expressions throughout your code may make for a good debugging technique but, if not used wisely, can lead to code that is difficult to understand and inherently imperative.
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Separate Mutable Data Structures
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A common technique of object-oriented programming is to ensure that mutable data structures are private, nonescaping, and, where possible, fully separated, which means there is no chance that distinct pieces of code can access each other s internal state in undesirable ways. Fully separated state can even be used inside the implementation of what, to the outside world, appears to be a purely functional piece of code. For example, where necessary, you can use side effects on private data structures allocated at the start of an algorithm and then discard these data structures before returning a result; the overall result is
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CHAPTER 4 INTRODUCING IMPERATIVE PROGRAMMING
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then effectively a side-effect-free function. One example of separation from the F# library is the library s implementation of List.map, which uses mutation internally; the writes occur on an internal, separated data structure that no other code can access. Thus, as far as callers are concerned, List.map is pure and functional. The following is a second example that divides a sequence of inputs into equivalence classes (the F# library function Seq.groupBy does a similar thing): open System.Collections.Generic let divideIntoEquivalenceClasses keyf seq = // The dictionary to hold the equivalence classes let dict = new Dictionary<'key,ResizeArray<'T>>() // Build the groupings seq |> Seq.iter (fun v -> let key = keyf v let ok,prev = dict.TryGetValue(key) if ok then prev.Add(v) else let prev = new ResizeArray<'T>() dict.[key] <- prev prev.Add(v)) // Return the sequence-of-sequences. Don't reveal the // internal collections: just reveal them as sequences dict |> Seq.map (fun group -> group.Key, Seq.readonly group.Value) This uses the Dictionary and ResizeArray mutable data structures internally, but these mutable data structures aren t revealed externally. The inferred type of the overall function is as follows: val divideIntoEquivalenceClasses : ('T -> 'key) -> seq<'T> -> seq<'key * seq<'T>> Here is an example use: > divideIntoEquivalenceClasses (fun n -> n % 3) [ 0 .. 10 ];; val it : seq<int * seq<int>> = seq [(0, seq [0; 3; 6; 9]); (1, seq [1; 4; 7; 10]); (2, seq [2; 5; 8])]
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