Go フレームワークは将来の技術的課題にどのように対処しますか?

package main

import (
    "fmt"
    "runtime"
)

func main() {
    // 创建一个通道来通信并行任务的结果
    ch := make(chan int)

    // 启动多个 Goroutine 来并行执行任务
    for i := 0; i < 10; i++ {
        go func(n int) {
            res := n * n
            ch <- res
        }(i)
    }

    // 读取通道中的结果并打印
    for i := 0; i < 10; i++ {
        fmt.Println(<-ch)
    }
}

package main

import (
    "context"
    "fmt"
    "log"

    "cloud.google.com/go/functions/metadata"
)

func main() {
    ctx := context.Background()
    m, err := metadata.FromContext(ctx)
    if err != nil {
        log.Fatal(err)
    }
    fmt.Println(fmt.Sprintf("Function deployed to %s with version %s", m.Region, m.VersionID))
}

package main

import (
    "fmt"
    "log"

    "github.com/mitchellh/mapstructure"
    "github.com/tensorflow/tensorflow/tensorflow/go/core/framework/tensor_shape"
    "github.com/tensorflow/tensorflow/tensorflow/go/tf"
)

func main() {
    // 加载和使用预训练的 TensorFlow 模型
    model, err := tf.LoadGraphDef("model.pb")
    if err != nil {
        log.Fatal(err)
    }

    // 创建一个输入 tensor
    input := map[string]interface{}{
        "x": [][]float32{{1}, {2}},
    }

    // 执行预测
    output, err := model.Predict(input, tensor_shape.TensorShape{2, 1})
    if err != nil {
        log.Fatal(err)
    }

    // 打印预测结果
    for i, v := range output[0].Value().([][]float32) {
        fmt.Println(fmt.Sprintf("Output %d: %f", i+1, v))
    }
}

package main

import (
    "fmt"
    "log"
    "net/http"
)

func main() {
    http.HandleFunc("/", handler)
    log.Fatal(http.ListenAndServe(":8080", nil))
}

func handler(w http.ResponseWriter, r *http.Request) {
    fmt.Fprintf(w, "Hello, world!")
}