What are the innovations in using the Go language to develop the dish promotion function of the door-to-door cooking system?

What are the innovations in using the Go language to develop the dish promotion function of the door-to-door cooking system?

With the development of the Internet and mobile Internet, home cooking has become the choice of more and more people. In order to meet this market demand, many companies have developed their own door-to-door cooking systems, of which the dish promotion function is a crucial part. This article will introduce the innovation of using Go language to develop the dish promotion function of the door-to-door cooking system, and present relevant code examples.

Innovation:

1. Dish recommendations based on user reviews

User reviews are one of the important criteria for evaluating whether a dish is good or not. Therefore, in our door-to-door cooking system, we can recommend other dishes of similar taste or the same taste to users based on their reviews.

First of all, we need to use the Go language to build an ORM (Object Relational Mapping) framework to handle database operations. We use GORM. GORM is a very powerful ORM framework that supports a variety of commonly used databases such as MySQL, PostgreSQL and SQLite. Then, we can create a table named "evaluation" in the database to store users' evaluations of the dishes. All reviews will be stored in a field called "comments". When a user places an order through the door-to-door cooking system, we write the evaluation into the database. Finally, we can implement dish recommendations through the following code:

// Function with return type []Dish
func RecommendDishes(evaluation string) []Dish {

// 从数据库中获取评论数据
rows, _ := db.Query("SELECT * FROM evaluation WHERE comments LIKE '%" + evaluation + "%'")
var dishes []Dish
for rows.Next() {
    // 获取菜品id
    var dishId int
    rows.Scan(&dishId, _, _)
    // 根据菜品id获取菜品
    dish := GetDishById(dishId)
    // 将菜品添加到结果数组
    dishes = append(dishes, dish)
}
return dishes

}

2. Recommended dishes based on user collections

The dishes collected by users are one of the information that reflects the user’s tastes and needs. Therefore, we can also recommend the dishes that users like based on their collection records.

We can create a table named "collection" when the user logs in to the door-to-door cooking system to store the IDs of the dishes he has collected. When a user places an order, we store their favorites list in the user's order. Finally, we can recommend dishes through the following code:

// Function with return type []Dish
func RecommendDishesByCollection(userId int) []Dish {

// 从数据库中获取收藏列表
rows, _ := db.Query("SELECT collection FROM user WHERE user_id = ?", userId)
var dishes []Dish
for rows.Next() {
    // 获取菜品id
    var dishId int
    rows.Scan(&dishId)
    // 根据菜品id获取菜品
    dish := GetDishById(dishId)
    // 将菜品添加到结果数组
    dishes = append(dishes, dish)
}
return dishes

}

3. Popular recommendations based on platform operation

Platform operation is the key to mobilizing user enthusiasm and increasing exposure. In the door-to-door cooking system, we can add a "popular recommendation" label to the dish interface, and based on the user's order volume, evaluation volume and other information, popular dishes will be listed as recommended dishes and ranked first. We can implement hot recommendations through the following code:

// Function with return type []Dish
func RecommendDishesByHot() []Dish {

// 从数据库中获取菜品下单量
rows, _ := db.Query("SELECT dish_id, count(*) as nums FROM orders GROUP BY dish_id")
var dishes []Dish
for rows.Next() {
    // 获取菜品id和下单量
    var dishId int
    var nums int
    rows.Scan(&dishId, &nums)
    // 根据菜品id获取菜品
    dish := GetDishById(dishId)
    // 将菜品附加一个下单量的标签
    dish.Tag = "下单量：" + strconv.Itoa(nums)
    // 将菜品添加到结果数组
    dishes = append(dishes, dish)
}
// 按下单量排序
sort.Slice(dishes, func(i, j int) bool {
    return dishes[i].Orders > dishes[j].Orders
})
return dishes

}

Conclusion

This article introduces the innovation of using Go language to develop the dish promotion function of the door-to-door cooking system, and attaches relevant code examples. Various recommendation methods based on user reviews, user collections, and platform operations can help users better explore and choose their favorite dishes.

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