PHP and UniApp implement automatic data completion and search suggestions

PHP and UniApp realize automatic data completion and search suggestions

With the development of the Internet, search engines have played an important role in users obtaining information. Among them, the automatic data completion and search suggestion functions enable users to get more accurate suggestions when entering keywords, improving the user's search experience. This article will introduce how to use PHP and UniApp to implement data auto-complete and search suggestion functions.

First, we need to prepare a data set that contains the keywords we want users to search for. This data set can be stored in a database or in an array containing keywords. In this article, we assume that the data set is saved in a table in the database with the table name keywords and the field name keyword.

Next, we need to write an interface in PHP to provide data for search suggestions. First, we need to connect to the database. The following is an example PHP code:

<?php
// 连接到数据库
$servername = "localhost";
$username = "root";
$password = "";
$dbname = "your_database_name";
$conn = new mysqli($servername, $username, $password, $dbname);

// 检查连接是否成功
if ($conn->connect_error) {
    die("Connection failed: " . $conn->connect_error);
}

// 获取用户输入的关键词
$keyword = $_GET["keyword"];

// 查询数据库，获取匹配的关键词
$sql = "SELECT keyword FROM keywords WHERE keyword LIKE '%$keyword%'";
$result = $conn->query($sql);

// 将查询结果转化为一个包含关键词的数组
$keywords = array();
while($row = $result->fetch_assoc()) {
    array_push($keywords, $row["keyword"]);
}

// 返回搜索建议的数据
echo json_encode($keywords);

// 关闭数据库连接
$conn->close();
?>

Next, we need to write a component in UniApp to receive the keywords entered by the user and send a request to the backend interface to obtain search suggestion data. The following is an example UniApp code:

<template>
  <div>
    <input type="text" v-model="keyword" @input="getSuggestions" />
    <ul>
      <li v-for="suggestion in suggestions" :key="suggestion">{{ suggestion }}</li>
    </ul>
  </div>
</template>

<script>
export default {
  data() {
    return {
      keyword: '',
      suggestions: []
    };
  },
  methods: {
    getSuggestions() {
      // 向后端接口发送请求获取搜索建议的数据
      uni.request({
        url: 'http://localhost/get_suggestions.php',
        data: {
          keyword: this.keyword
        },
        success: (res) => {
          // 更新搜索建议的数据
          this.suggestions = res.data;
        }
      });
    }
  }
};
</script>

In the above code, we bind the keywords entered by the user to the keyword variable through the v-model directive, The getSuggestions method is automatically called when the user enters keywords. This method will send a request to the backend interface and update the suggestions variable to update the search suggestion data. In the front-end interface, the data in suggestions is rendered onto the page through the v-for command. Users can directly click on the search suggestions to complete the search.

Finally, we need to introduce the above components into UniApp and use them in the page. The following is an example UniApp page code:

<template>
  <div>
    <h1>数据的自动补全与搜索建议</h1>
    <AutoComplete />
  </div>
</template>

<script>
import AutoComplete from '@/components/AutoComplete'

export default {
  components: {
    AutoComplete
  }
}
</script>

Through the above steps, we can realize the automatic completion of data and search suggestion functions. When users enter keywords, matching suggested words will be automatically obtained and displayed on the page for users to choose. After the user selects the suggested word, he or she can perform a search operation.

To sum up, this article introduces how to use PHP and UniApp to realize the automatic completion and search suggestion functions of data. By writing back-end interfaces and front-end components, we can easily provide users with more accurate search suggestions and improve users' search experience. I hope this article will be helpful to developers who use PHP and UniApp to implement data auto-complete and search suggestion functions.

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