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Functional Programming in Go: Breaking the Conventional Perception
When you hear "functional programming," Go usually isn't the first language that comes to mind. You might think of Haskell, with its pure functions and monads (don't panic, we'll explain that in detail later), or JavaScript, which loves to showcase its features with higher - order functions and callbacks. But in fact, you can also do functional programming in Go, and the process is far from dull.
Higher - Order Functions
First of all, let's talk about higher - order functions. Higher - order functions can work well with other functions, either taking them as parameters or returning them as values. In the world of Go, implementing higher - order functions is not only possible but also quite ingenious.
package main
import (
"fmt"
)
func filter(numbers []int, f func(int) bool) []int {
var result []int
for _, value := range numbers {
if f(value) {
result = append(result, value)
}
}
return result
}
func isEven(n int) bool {
return n%2 == 0
}
func main() {
numbers := []int{1, 2, 3, 4}
even := filter(numbers, isEven)
fmt.Println(even) // [2, 4]
}
You see, in this example, the filter function takes an integer slice and a judgment function f, and returns the elements in the slice that meet the judgment conditions. Doesn't it seem a bit like a faster JavaScript?
Currying
Next up is currying. It is the process of breaking down a function that takes multiple arguments into a series of functions, each taking a single argument. Currying is actually not as complicated as it might seem.
package main
import "fmt"
func add(a int) func(int) int {
return func(b int) int {
return a + b
}
}
func main() {
addFive := add(5)
fmt.Println(addFive(3)) // 8
}
In this example, the add function takes an integer a and returns a new function. This new function takes another integer b and returns the result of a + b. Simple, straightforward, and gets the job done without any frills.
Immutability
One of the characteristics of functional programming is immutability. Once something is constructed, it doesn't change. Instead, if you need something different, you build a new one. This might sound wasteful at first, but in fact, it keeps the code clean and reduces side effects.
package main
import "fmt"
func main() {
obj := map[string]int{"a": 1, "b": 2}
newObj := make(map[string]int)
for k, v := range obj {
newObj[k] = v
}
newObj["b"] = 3
fmt.Println(newObj) // map[a:1 b:3]
}
In this example, instead of directly modifying the original obj, we created a new newObj and modified it.
Pure Functions
Pure functions are like tidy friends. They don't touch or modify anything outside their scope. What you pass in is what you use, and what they return is their only effect.
package main
import "fmt"
func square(x int) int {
return x * x
}
func main() {
fmt.Println(square(5)) // 25
}
In this example, the square function only depends on the passed - in parameter x and doesn't affect any external variables.
Functors
In the simplest terms, functors are anything that can map a function. Think of the humble array, applying a function to each item and getting a new array. In Go, there is no built - in general map function, but we can build one ourselves.
package main
import "fmt"
// Functor on a slice of int
func mapInts(values []int, f func(int) int) []int {
result := make([]int, len(values))
for i, v := range values {
result[i] = f(v)
}
return result
}
func main() {
numbers := []int{1, 2, 3, 4}
squared := mapInts(numbers, func(x int) int { return x * x })
fmt.Println(squared) // [1, 4, 9, 16]
}
Here, we defined a mapInts function that takes an integer slice and a function and returns a new slice, where each element is the result of processing the original slice element by the function.
Endofunctors
Now, let's talk about endofunctors. It's just a fancy way of saying a functor that maps a type to the same type. Simply put, starting from a Go slice, you end up with a Go slice of the same type. It's not rocket science, just a matter of type consistency.
Taking the previous mapInts as an example, it's a kind of endofunctor in disguise. It takes []int and returns []int without type conversion.
Monoids
Imagine a party where everyone has to bring a friend. Monoids are like that, but for types. They need two things: an operation that combines two types and a special value, which is like the most likable friend - it gets along with everyone but doesn't change anything about them.
In Go, you can see this with slices or numbers. Let's take numbers as an example because they're easier to work with:
package main
import "fmt"
// Integer addition is a monoid with zero as the identity element
func add(a, b int) int {
return a + b
}
func main() {
fmt.Println(add(5, 5)) // 10
fmt.Println(add(5, 0)) // 5
fmt.Println(add(0, 0)) // 0
}
Here, 0 is our hero, the identity element, which keeps the numbers unchanged.
Monads
"When someone says, 'A monad is a monoid in the category of endofunctors,' they're basically showing off their computer - science vocabulary." To explain in detail: A monad is a programming construct that deals with types and functions in a super - special way - like some people are picky about how their coffee is brewed.
In the simplest terms, a monoid is about combining things together using a special rule, which includes a useless element or identity element. Now, add endofunctors, which are like ordinary old functions but stick to transforming things within their own little universe (category). Put it all together, and you'll see that a monad can be seen as a way to chain functions together in a sequence, but in a super - self - contained way while also respecting the original structure of the data. It's like saying, "We're going on a road trip, but we can only take the scenic backroads, and we'll end up back where we started."
Monads are all - rounders. They can not only handle values with context (such as errors or lists) but also chain operations together by passing the context. In Go, it might be a bit difficult to mimic this, but let's take a look at error handling, which is a practical use of monads.
package main
import (
"errors"
"fmt"
)
// Maybe represents a monad for error handling
func Maybe(value int, err error, f func(int) (int, error)) (int, error) {
if err!= nil {
return 0, err
}
return f(value)
}
func main() {
// Simulate a computation that might fail
process := func(v int) (int, error) {
if v < 0 {
return 0, errors.New("negative value")
}
return v * v, nil
}
// Use our Maybe "monad" to handle potential errors
result, err := Maybe(5, nil, process)
if err!= nil {
fmt.Println("Error:", err)
} else {
fmt.Println("Success:", result) // Success: 25
}
}
This makeshift monad can help us handle computations that might go wrong without causing panics and chaos in the code.
Conclusion
Functional programming in Go might not be the poster child of the functional paradigm, but it's entirely feasible and can even be fun. Who would have thought, right? Now, you should understand that Go can achieve functional programming just like other languages. With a little effort, you can write clean, efficient, and robust code.
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Top comments (7)
Sorry, but not in go. Your first example have terrible efficient because it allocates new memory to each filter. Theoretically you can create lazy iterator in 1.23 but you can't combine it. For example in this rust code no additional allocations and it must work idebtically as imperative code:
While this article may seem fascinating to go developers who mostly come from c, c++ or c# ecosystem, it's totally misleading. And you only know it, if you are familiar with principled FP languages like Haskell or Scala. Go's functional programming features are just advertising sales point, like any other language wich lacks a safisticated type system. And this misleading advertisery is shared among go, Java, Python and JavaScript. Go still could prove itself useful in a cloud context, but nevertheless as a general purpose language.
What's so fascinating even for them? There's nothing here that modern C++ doesn't support.
Why would you do that in Go of all places? The concepts are solid and well-known but there are languages out there which do this better. I don't see the connection to Go.
OK, so how about answering the question in the title? Why is it supposed to be "Ultimate Coding Style"?
Especially since you can do all the same even in C++ nowadays?
Because this is the title the LLM came up with. The whole article is obviously AI slop.
This is interesting. It does look a bit like Javascript with typing. Could even go the way of python by the looks of things?