How to use Vue and NetEase Cloud API to develop a personalized playlist recommendation system

How to use Vue and NetEase Cloud API to develop a personalized playlist recommendation system

With the popularity of music streaming services, people's demand for music is getting higher and higher. Personalized playlist recommendation system has become one of the important functions of modern music applications. This article will introduce how to use Vue and NetEase Cloud API to develop a personalized playlist recommendation system to help readers understand this process and related technologies.

1. Environment settings

First, we need to prepare the development environment. Make sure Node.js and npm are installed.

2. Create Vue project

Enter the following command on the command line to create a new Vue project:

vue create song-recommendation-system

Select the appropriate option according to the prompts, Wait for the project to be created.

3. Install dependencies

Enter the project directory and install the required dependencies:

cd song-recommendation-system
npm install axios vue-router

4. Create API service

We need to use NetEase Cloud API to obtain song and playlist information. Create a file named api.js in the src directory of the project, which defines the API services we need:

import axios from 'axios';

const api = axios.create({
  baseURL: 'https://api.apiopen.top',
});

export const getRecommendations = () => {
  return api.get('/recommendSongs');
};

export const getSongDetail = (id) => {
  return api.get(`/song/detail?id=${id}`);
};

export const getPlaylistDetail = (id) => {
  return api.get(`/playlist/detail?id=${id}`);
};

5. Create Vue components

In src/components Create a file named Recommendations.vue in the directory. This component is used to display personalized song list recommendation results:

<template>
  <div>
    <h2 id="个性化推荐">个性化推荐</h2>
    <ul>
      <li v-for="(song, index) in songs" :key="index">
        <p>{{ song.name }}</p>
        <p>{{ song.artist }}</p>
      </li>
    </ul>
  </div>
</template>

<script>
import { getRecommendations } from '../api';

export default {
  data() {
    return {
      songs: [],
    };
  },
  mounted() {
    this.fetchRecommendations();
  },
  methods: {
    fetchRecommendations() {
      getRecommendations()
        .then((response) => {
          this.songs = response.data.result || [];
        })
        .catch((error) => {
          console.error(error);
        });
    },
  },
};
</script>

6. Create route

In the src directory Create a file named router.js to define routes:

import Vue from 'vue';
import VueRouter from 'vue-router';
import Recommendations from './components/Recommendations';

Vue.use(VueRouter);

const router = new VueRouter({
  mode: 'history',
  routes: [
    { path: '/', component: Recommendations },
  ],
});

export default router;

7. Modify the entry file

Associate components and routes in src/main.js ：

import Vue from 'vue';
import App from './App.vue';
import router from './router';

Vue.config.productionTip = false;

new Vue({
  router,
  render: (h) => h(App),
}).$mount('#app');

8. Write the view

Modify src/App.vue and place the Recommendations component on the home page:

<template>
  <div id="app">
    <header>
      <router-link to="/">首页</router-link>
    </header>
    <main>
      <router-view></router-view>
    </main>
    <footer></footer>
  </div>
</template>

9. Run the application

Run the following command to start the development server:

npm run serve

Open the browser and preview the application at http://localhost:8080.

So far, we have completed the steps of developing a personalized playlist recommendation system using Vue and NetEase Cloud API. The code can be extended and optimized as needed, such as adding more features and styles.

Summary

This article introduces how to use Vue and NetEase Cloud API to develop a personalized playlist recommendation system. We used the Vue framework to build the front-end interface and components, and used the NetEase Cloud API to obtain music data. Readers can further learn and develop other music applications or recommendation systems based on this example. Hope this article can be helpful to you!

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