Talking about functional programming from Go language closure

This article learns functional programming from the following aspects:

1. What is the relationship between mathematical formulas and functional programming

Let’s take a simple example. There is a concept in mathematics called mapping (y=f(x)). To put it simply, it is a function. The most familiar one should be the quadratic function (parabola y=a*x*x b*x c)

Now coding implements the value of a certain point on the parabola. We know that a, b, c are parameters, and x is Independent variable, y is the dependent variable. If it were in the past, I might implement it like this (in order to commemorate the c that I haven’t written for a long time, I will write it in c)

double getParabola(double a,double b,double c,double x) { return a*x*x+b*x+c; }

Question 1. Given a parabola, find x =2, x=3, x=4, the value is the following approach

resultA = getParabola(a,b,c,2) resultB = getParabola(a,b,c,2) resultC = getParabola(a,b,c,2)

This is a normal approach in the program. However, from a mathematical perspective, is there any way to become consistent with mathematical formula thinking? The following is another implementation of mine (implemented here using go, because I know how to write c),

func getParabola(aa,bb,cc float32){ var a = aa var b = bb var c = cc a := func(x float32) { return a*x*x+b*x+c } return a }

Then, also for question 1, the solution is as follows

parabola := getParabola(a,b,c) resultA := parabola(2) resultB := parabola(3) resultC := parabola(4)

is Isn't it the same as finding the value of a function? Therefore, mathematical relationships are well represented in functional programming.

2. What are the characteristics of functional programming and what concepts does go support?

Functional programming has three major characteristics

1. Immutability of variables: Once a variable is assigned a value, it cannot be changed. If changes are needed, they must be copied and then modified. In go, once a string variable is assigned a value, it cannot be modified like c, c[2]='a', but it must be explicitly converted to []byte and then modified. But it is already another piece of memory.

2. Functional first-class citizens: Functions are also variables and can be passed as parameters, return values, etc. in the program. This feature should be supported by both c and go.

3. Tail recursion: The concept of recursion was learned in the Fibonacci sequence. If the recursion is very deep, the stack may explode and cause a significant performance degradation. As for tail recursion optimization technology, if the compiler supports it, the stack can be reused in each recursion (tail recursion means that the recursive call occurs in the last step. At this time, the previous results are passed as parameters to the last step of the call, so the previous The state has no effect anymore, so the stack can be reused).

Commonly used techniques in functional programming

1. map&reduce&filter

map is used to call the same function for each input to produce an output, such as for_each in c, map in hadoop, map in python, etc.

reduce is used to add each input to the previous output to get the next output, such as reduce in python and hadoop,

filter is used for filtering, such as c's count_if, etc. .

2. Recursion

3. Pipeline

Put the function instance into an array or list, and then pass the data to the action list, and the input is sequentially passed to each The function operates (meaning that the output of each function is used as the input of another function, the data is flowing, and the calculation is fixed, similar to the concept of storm), and finally we get the result we want.

4. Others (to be further studied)

3. Functional programming and operating efficiency

The most important concept of functional programming is function Equations are first-class citizens, functions and variables are the same. Can be used as parameters, return values, etc. The use of assignment statements is not favored, so recursion is used more often, so the efficiency of functional programming will definitely be lower.

Recently I use closures more. The concept of closure is an environment (one or more variables) plus a function. Every time the closure expression is evaluated, an isolation is obtained. The result is different from an ordinary function. An ordinary function is a piece of executable code. As long as the entrance is determined, the calling position is also determined. For example, in the parabola example above, calling

a:=getParabola(0.2,0.1,0.3) b:=getParabola(0.1,0.1,0.4)

will result in two parabolas. The reason why I think the efficiency will be reduced is because the closure itself is a process of evaluation and assignment, involving the creation and destruction of variables. Of course, I didn't actually test the performance. If subsequent release server efficiency decreases, perhaps this is something to consider.

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