How to write high-performance golang code using generics

Generics introduce flexibility, reusability and improve performance in the Go language by using type constraints to ensure that type parameters have the desired behavior. Practical examples of generic functions, types, and data structures include caching data structures and benchmarking, which can significantly improve code performance to optimize Go applications.

How to use generics to write high-performance Go code

Generics were introduced in Go 1.18 and can be accessed by using type parameters Instead of concrete types, more general functions, methods, and types are defined. Using generics can improve code reusability, flexibility, and performance.

Type parameter restrictions

Although generics bring flexibility, they need to be restricted using constraints to ensure that type parameters have the desired behavior. Restrictions can be defined as interfaces, types, or a combination of both. For example, you can use the following constraint to restrict that type parameters must support comparison operations:

type Ordered interface {
    // 比较两个值并返回 -1、0 或 1
    Compare(v Ordered) int
}

Generic functions

You can declare a generic function using type parameters. For example:

func Max[T Ordered](values []T) T {
    max := values[0]
    for _, v := range values {
        if v.Compare(max) > 0 {
            max = v
        }
    }
    return max
}

This function can be used to find the maximum value of any type that implements the Ordered constraint.

Generic types

You can also declare generic types. For example, you can define a generic linked list type:

type List[T any] struct {
    head *Node[T]
    tail *Node[T]
}

This linked list can store elements of any type.

Practical case

Cache data structure

Generics can be used to implement efficient cache data structures. For example, you can define a generic LRU cache:

type LRUCache[K comparable, V any] struct {
    cache map[K]*Node[K, V]
    list  *List[K, V]
    cap   int
}

This cache uses dictionaries and linked lists to track element usage.

Benchmark

Using generics can improve performance. Here is an example of a benchmark implemented using generics:

func BenchmarkMaxInt(b *testing.B) {
    for n := 0; n < b.N; n++ {
        Max([]int{1, 2, 3, 4, 5})
    }
}

func BenchmarkMaxFloat64(b *testing.B) {
    for n := 0; n < b.N; n++ {
        Max([]float64{1.1, 2.2, 3.3, 4.4, 5.5})
    }
}

Benchmark results often show significant performance improvements after using generics and type constraints.

Conclusion

Using generics can introduce flexibility, reusability, and performance improvements into your Go code. It is important to understand type parameter restrictions to ensure that type parameters behave as expected. Generics open up new possibilities for optimizing Go applications and creating more reliable, efficient code.

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