WIN Reality招聘全栈工程师（Golang开发方向 - 奥斯汀）

从技术栈来看，这是一个典型的Go全栈岗位，结合了Vue.js前端和Go后端。以下是一些Go相关的技术实现示例，符合该职位描述中的API开发和服务器构建要求：

1. RESTful API示例（使用标准库）

package main

import (
    "encoding/json"
    "net/http"
    "github.com/go-chi/chi/v5"
)

type PerformanceMetrics struct {
    UserID    string  `json:"user_id"`
    BattingAvg float64 `json:"batting_average"`
    ExitVelocity float64 `json:"exit_velocity"`
}

func main() {
    r := chi.NewRouter()
    
    // 对应职位描述中的"向客户提供性能洞察"
    r.Get("/api/users/{id}/metrics", func(w http.ResponseWriter, r *http.Request) {
        userID := chi.URLParam(r, "id")
        
        metrics := PerformanceMetrics{
            UserID:        userID,
            BattingAvg:    0.327,
            ExitVelocity:  92.4,
        }
        
        w.Header().Set("Content-Type", "application/json")
        json.NewEncoder(w).Encode(metrics)
    })
    
    // 对应"改进新用户体验"的数据端点
    r.Post("/api/onboarding", func(w http.ResponseWriter, r *http.Request) {
        var onboardingData map[string]interface{}
        json.NewDecoder(r.Body).Decode(&onboardingData)
        
        // 处理用户引导数据
        w.WriteHeader(http.StatusCreated)
        json.NewEncoder(w).Encode(map[string]string{
            "status": "onboarding_complete",
            "next_step": "vr_training",
        })
    })
    
    http.ListenAndServe(":8080", r)
}

2. Go模板服务器示例（对应Web应用服务器）

package main

import (
    "html/template"
    "net/http"
    "github.com/go-chi/chi/v5"
)

func main() {
    r := chi.NewRouter()
    
    // 使用Go模板渲染仪表盘页面
    r.Get("/dashboard", func(w http.ResponseWriter, r *http.Request) {
        tmpl := template.Must(template.ParseFiles(
            "templates/layout.html",
            "templates/dashboard.html",
        ))
        
        data := struct {
            Title      string
            UserName   string
            Metrics    []PerformanceMetric
        }{
            Title:    "Performance Dashboard",
            UserName: "Player123",
            Metrics:  getPerformanceData(),
        }
        
        tmpl.ExecuteTemplate(w, "layout", data)
    })
    
    http.ListenAndServe(":8080", r)
}

type PerformanceMetric struct {
    Date     string
    Value    float64
    Category string
}

3. 数据库操作示例（MariaDB）

package main

import (
    "database/sql"
    "log"
    _ "github.com/go-sql-driver/mysql"
)

type UserSession struct {
    ID        string
    Duration  int
    Timestamp string
}

func saveTrainingSession(db *sql.DB, session UserSession) error {
    // 对应"启用新的数据分析系统"需求
    query := `
        INSERT INTO training_sessions 
        (user_id, duration_seconds, session_timestamp) 
        VALUES (?, ?, ?)
    `
    
    _, err := db.Exec(query, 
        session.ID, 
        session.Duration, 
        session.Timestamp,
    )
    
    return err
}

func getRealTimeMetrics(db *sql.DB, userID string) (map[string]interface{}, error) {
    // 对应"提供准确的实时指标"
    query := `
        SELECT 
            AVG(exit_velocity) as avg_velocity,
            COUNT(*) as total_sessions,
            MAX(session_timestamp) as last_training
        FROM training_sessions 
        WHERE user_id = ? 
        AND session_timestamp > DATE_SUB(NOW(), INTERVAL 7 DAY)
    `
    
    var metrics struct {
        AvgVelocity   float64
        TotalSessions int
        LastTraining  string
    }
    
    err := db.QueryRow(query, userID).Scan(
        &metrics.AvgVelocity,
        &metrics.TotalSessions,
        &metrics.LastTraining,
    )
    
    result := map[string]interface{}{
        "weekly_avg_velocity": metrics.AvgVelocity,
        "weekly_sessions":     metrics.TotalSessions,
        "last_training":       metrics.LastTraining,
    }
    
    return result, err
}

4. 监控和健康检查端点

package main

import (
    "net/http"
    "time"
    "github.com/prometheus/client_golang/prometheus"
    "github.com/prometheus/client_golang/prometheus/promhttp"
)

var (
    requestsTotal = prometheus.NewCounterVec(
        prometheus.CounterOpts{
            Name: "http_requests_total",
            Help: "Total HTTP requests",
        },
        []string{"path", "method"},
    )
    
    requestDuration = prometheus.NewHistogramVec(
        prometheus.HistogramOpts{
            Name: "http_request_duration_seconds",
            Help: "HTTP request duration",
        },
        []string{"path"},
    )
)

func init() {
    prometheus.MustRegister(requestsTotal)
    prometheus.MustRegister(requestDuration)
}

func monitoringMiddleware(next http.Handler) http.Handler {
    return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {
        start := time.Now()
        
        // 记录请求指标
        requestsTotal.WithLabelValues(r.URL.Path, r.Method).Inc()
        
        next.ServeHTTP(w, r)
        
        duration := time.Since(start).Seconds()
        requestDuration.WithLabelValues(r.URL.Path).Observe(duration)
    })
}

func main() {
    r := chi.NewRouter()
    r.Use(monitoringMiddleware)
    
    // CloudWatch/Prometheus指标端点
    r.Handle("/metrics", promhttp.Handler())
    
    // 健康检查端点（对应基础设施监控）
    r.Get("/health", func(w http.ResponseWriter, r *http.Request) {
        // 检查数据库连接、Redis连接等
        healthStatus := map[string]interface{}{
            "status":    "healthy",
            "timestamp": time.Now().UTC(),
            "services": map[string]string{
                "database": "connected",
                "redis":    "connected",
                "api":      "operational",
            },
        }
        
        json.NewEncoder(w).Encode(healthStatus)
    })
    
    http.ListenAndServe(":8080", r)
}

这些示例展示了如何实现职位描述中提到的核心功能：性能指标API、用户仪表盘、实时数据系统、监控和健康检查。技术栈选择上使用了chi路由（轻量级且符合Go习惯）、标准库模板、MariaDB驱动和Prometheus监控，这些都与AWS ECS容器化部署和RESTful API设计需求相匹配。