How to build a RESTful API using Golang and use caching?

Integrate caching when building RESTful APIs with Golang: Use Gin to create APIs; integrate Redis cache; define a cache layer to manage cached values; use the cache layer in Gin handlers to get and set data from Redis.

How to integrate caching when building a RESTful API using Golang

When building a RESTful API, caching can greatly improve performance and reduce server usage load and improve user experience. This article will guide you to build a RESTful API and integrate caching using Golang.

Use Gin to create a RESTful API

First, use the Gin framework to create a new Golang RESTful API:

import (
    "github.com/gin-gonic/gin"
)

func main() {
    r := gin.Default()
    r.GET("/api/v1/users", GetUsers)
    r.Run()
}

Integrate Redis cache

To use caching, we will use Redis, a highly available key-value store. Make sure Redis is installed and running.

In Golang, we can use the redigo library to connect to Redis:

import (
    "time"

    "github.com/gomodule/redigo/redis"
)

// redisPool is a global variable to manage the Redis connection pool.
var redisPool *redis.Pool

func init() {
    redisPool = &redis.Pool{
        MaxIdle:   10,
        MaxActive: 10,
        IdleTimeout: 30 * time.Second,
        Dial: func() (redis.Conn, error) {
            return redis.Dial("tcp", "localhost:6379")
        },
    }
}

Cache Layer

Now, let us define a new layer with For managing cache. This layer will provide functions to get, set, and delete cached values.

import (
    "time"

    "github.com/gomodule/redigo/redis"
)

type Cache struct {
    pool *redis.Pool
}

func NewCache(pool *redis.Pool) *Cache {
    return &Cache{
        pool: pool,
    }
}

func (c *Cache) Get(key string) ([]byte, error) {
    conn := c.pool.Get()
    defer conn.Close()

    return redis.Bytes(conn.Do("GET", key))
}

func (c *Cache) Set(key string, value string) error {
    conn := c.pool.Get()
    defer conn.Close()

    _, err := conn.Do("SET", key, value)
    return err
}

func (c *Cache) Delete(key string) error {
    conn := c.pool.Get()
    defer conn.Close()

    _, err := conn.Do("DEL", key)
    return err
}

Using caching

In the Gin handler function, we can use the caching layer to cache the API response. The following is the modified GetUsers handler function:

func GetUsers(c *gin.Context) {
    // 获取 Redis 缓存
    key := "users"
    cachedBytes, err := cache.Get(key)
    if err != nil {
        // 缓存中没有值，从数据库中获取
        users, err := getUserFromDB()
        if err != nil {
            c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
            return
        }

        // 将 users 序列化为 JSON 并存储在缓存中
        userJSON, err := json.Marshal(users)
        if err != nil {
            c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
            return
        }

        err = cache.Set(key, string(userJSON))
        if err != nil {
            c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
            return
        }

        c.JSON(http.StatusOK, users)
    } else {
        // 从缓存中获取值，反序列化回 []User 类型
        var users []User
        err := json.Unmarshal(cachedBytes, &users)
        if err != nil {
            c.JSON(http.StatusInternalServerError, gin.H{"error": err.Error()})
            return
        }

        c.JSON(http.StatusOK, users)
    }
}

// getUserFromDB 从数据库中获取用户
func getUserFromDB() ([]User, error) {
    // 假设这是从数据库获取用户数据的模拟函数
    return []User{{ID: 1, Name: "John"}}, nil
}

Now, the API will first get the response from the cache. If the value does not exist in the cache, it will get the data from the database and put it Stored in cache. This will significantly reduce duplicate requested database queries, thereby improving performance.

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