基于springboot+vue+爬虫实现电影推荐系统

一，项目简介
这是一个前后端分离的电影管理和推荐系统，采用Vue.js + Spring Boot技术栈开发，电影数据来源于豆瓣，采用Python爬虫进行爬取相关电影的数据，将数据插入MYSQL数据库，然后在前端进行数据展示。后台主要进行电影相关基本数据的管理功能。给用户推荐的电影数据写入到REDIS数据库中进行存储。推荐算法采用协同过滤算法，采用于ItemCF和UserCF相结合的方式来进行推荐。

二，环境介绍
语言环境：Java: jdk1.8
数据库：Mysql: mysql5.7+Redis
应用服务器：Tomcat: tomcat8.5.31
开发工具：IDEA或eclipse
前端技术栈：

• Vue.js
• ElementUI
• axios

后端技术栈：

• Spring Boot
• MyBatis
• Apache Shiro
• Spring Data Redis

三，系统展示
前端分类列表

详情展示

全文检索

电影推荐

后台管理



电影管理

注册

登陆

四，核心代码展示

package com.fivesix.fivesixserver.controller;
 
import com.fivesix.fivesixserver.entity.Menu;
import com.fivesix.fivesixserver.service.MenuService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
 
import java.util.List;
 
@RestController
public class MenuController {
 
    @Autowired
    MenuService menuService;
 
    @GetMapping("/api/menu")
    public List<Menu> getMenusOfUser() {
        return menuService.listAllByCurrUser();
    }
 
    @GetMapping("/api/admin/role/menu")
    public List<Menu> getMenusOfRole() {
        return menuService.listAllByRole(1);
    }
 
}

        

          
        
        
        

          

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package com.fivesix.fivesixserver.controller;
 
import com.fivesix.fivesixserver.entity.Movie;
import com.fivesix.fivesixserver.service.MovieService;
import org.springframework.beans.factory.annotation.Autowired;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.multipart.MultipartFile;
 
import java.io.File;
import java.io.IOException;
import java.util.Comparator;
import java.util.List;
import java.util.UUID;
import java.util.stream.Collectors;
 
@RestController
public class MovieController {
 
    @Autowired
    MovieService movieService;
 
    /*
    前台请求接口
     */
    @GetMapping("/api/movies")
    public List<Movie> list() throws Exception {
        System.out.println("load all movies sorted by rate successfully.");
        return movieService.list().stream().sorted(Comparator.comparingDouble(Movie::getRate).reversed()).collect(Collectors.toList());
    }
 
    @GetMapping("/api/movies/page/{pageIndex}")
    public List<Movie> listByPageIndex(@PathVariable("pageIndex") int pageIndex) {
        System.out.printf("请求起始为%d:的21部电影\n",pageIndex);
        return movieService.listByPageIndex(pageIndex).stream().sorted(Comparator.comparingDouble(Movie::getRate).reversed()).collect(Collectors.toList());
    }
 
    @GetMapping("/api/movies/category/{cid}/{dateOrRate}")
    public Object listByCategory(@PathVariable("cid") int cid, @PathVariable("dateOrRate") int dateOrRate) throws Exception {
        List<Movie> res;
        if (cid == 0) {
            res =  movieService.list();
        }else{
            res = movieService.listByCategory(cid);
        }
        if (dateOrRate == 1) return res.stream().sorted(Comparator.comparingDouble(Movie::getRate).reversed()).collect(Collectors.toList());
        else return res.stream().sorted(Comparator.comparing(Movie::getDate).reversed()).collect(Collectors.toList());
    }
 
    @GetMapping("/api/search")
    public List<Movie> listByKeywords(@RequestParam("keywords") String keywords) {
        if (!keywords.equals("")){
            System.out.println("search result returned.");
            return movieService.listByKeywords(keywords).stream().sorted(Comparator.comparing(Movie::getDate).reversed()).collect(Collectors.toList());
        }else{
            return null;
        }
    }
 
    /*
    以下为后台请求接口
     */
    @PostMapping("/api/admin/content/movie/update")
    public Movie save(@RequestBody Movie movie, @RequestParam(value = "changeCategories") String categoriesIsChanged) throws Exception {
 
        Movie movie1 = movieService.getByMovieName(movie.getTitle());
        if (movie1 != null) {
            if (categoriesIsChanged.equals("true")) {
                movieService.updateMovieAndCategories(movie);
                System.out.println("update movie and categories.");
            } else {
                movieService.update(movie);
                System.out.println("update movie.");
            }
        } else {
            movieService.save(movie);
            System.out.println("add new movie.");
        }
        return movie;
    }
 
    @PostMapping("/api/admin/content/movie/delete")
    public void delete(@RequestBody Movie movie) throws Exception{
        movieService.deleteById(movie.getId());
        System.out.println("delete movie by id successfully.");
    }
 
    /*
    电影封面上传
     */
    @PostMapping("/api/admin/content/movie/cover")
    public String coversUpload(MultipartFile file) throws Exception {
        String folder = "D:/workspace/fivesix/img/full";
        File imageFolder = new File(folder);
        //对文件重命名，保留文件的格式png/jpg
        String newName = UUID.randomUUID().toString();
        File f = new File(imageFolder, newName + file.getOriginalFilename()
                .substring(file.getOriginalFilename().length() - 4));
        if (!f.getParentFile().exists())
            f.getParentFile().mkdirs();
        try {
            file.transferTo(f);
            String imgURL = "http://localhost:8443/api/file/" + f.getName();
            return imgURL;
        } catch (IOException e) {
            e.printStackTrace();
            return "";
        }
    }
}

        

          
        
        
        

          

          AI 代码解读
        
      
      

package com.fivesix.fivesixserver.controller;
 
import com.fivesix.fivesixserver.entity.User;
import com.fivesix.fivesixserver.result.Result;
import com.fivesix.fivesixserver.service.UserService;
import org.apache.shiro.SecurityUtils;
import org.apache.shiro.authc.AuthenticationException;
import org.apache.shiro.authc.UsernamePasswordToken;
import org.apache.shiro.crypto.SecureRandomNumberGenerator;
import org.apache.shiro.crypto.hash.SimpleHash;
import org.apache.shiro.subject.Subject;
import org.springframework.web.bind.annotation.*;
import org.springframework.web.util.HtmlUtils;
 
import java.util.List;
 
 
@RestController
public class UserController {
 
    private final UserService userService;
 
    public UserController (UserService userService) {
        this.userService = userService;
    }
 
    @PostMapping(value = "/api/login")
    public Result login(@RequestBody User requestUser,@RequestParam(value = "rememberMe") boolean rememberMe) {
        String requestUserName = HtmlUtils.htmlEscape(requestUser.getUsername());
        Subject subject = SecurityUtils.getSubject();
        UsernamePasswordToken usernamePasswordToken = new UsernamePasswordToken(requestUserName,requestUser.getPassword());
        usernamePasswordToken.setRememberMe(rememberMe);
        try{
            subject.login(usernamePasswordToken);
            return new Result(200,"login successfully");
 
        } catch (AuthenticationException e) {
            e.printStackTrace();
            return new Result(400,"账号或密码错误");
        }
    }
 
    @PostMapping("/api/register")
    public Result register(@RequestBody User user) {
        String username = HtmlUtils.htmlEscape(user.getUsername());
        user.setUsername(username);
        //生成盐
        String salt = new SecureRandomNumberGenerator().nextBytes().toString();
        user.setSalt(salt);
        //设置迭代次数
        int times = 2;
        //生成加密的密码
        String encodedPassword = new SimpleHash("md5",user.getPassword(),salt,times).toString();
        user.setPassword(encodedPassword);
 
        try {
            userService.register(user);
            return new Result(200,"register successfully.");
        }catch (Exception e) {
            e.printStackTrace();
            return new Result(400,e.getMessage());
        }
    }
 
    @GetMapping("api/logout")
    public Result logout() {
        Subject subject = SecurityUtils.getSubject();
        subject.logout();
        return new Result(200,"登出成功");
    }
 
    @GetMapping("api/authentication")
    public Result authenticate() {
        return new Result(200,"认证成功");
    }
 
    @GetMapping("api/admin/user")
    public List<User> getAllUsers() {
        return userService.listAll();
    }
 
    @PostMapping("api/admin/user/delete")
    public Result delete(@RequestBody User user) {
        try {
            userService.deleteUser(user);
            return new Result(200,"删除用户成功");
        }catch (Exception e) {
            return new Result(400,"删除用户失败");
        }
    }
 
    @PutMapping("api/admin/user/update")
    public Result update(@RequestBody User user) {
        try{
            userService.updateUser(user);
            return new Result(200,"更新用户成功");
        }catch (Exception e){
            return new Result(400,"更新用户失败");
        }
    }
}

        

          
        
        
        

          

          AI 代码解读
        
      
      

使用Python来进行电影数据爬取的核心代码

# -*- coding: utf-8 -*-
import scrapy
import json
import re
import time
from douban.items import DoubanItem
from fake_useragent import UserAgent
import random
 
class MovieHotSpider(scrapy.Spider):
    #爬虫的名称，在命令行可以方便的运行爬虫
    name = "movie_hot"
    allowed_domains = ["movie.douban.com"]
    #pro = ['139.224.37.83','115.223.7.110','221.122.91.75']
    # 拼接豆瓣电影URL
    BASE_URL = 'https://movie.douban.com/j/search_subjects?type=movie&tag=%s&sort=recommend&page_limit=%s&page_start=%s'
    MOVIE_TAG = '华语'
    PAGE_LIMIT = 20
    page_start = 0
 
    domains = BASE_URL % (MOVIE_TAG, PAGE_LIMIT, page_start)
 
    #伪装浏览器
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/86.0.4240.111 Safari/537.36"
        #,"Cookie":'_vwo_uuid_v2=D65EBF690D9454DE4C13354E37DC5B9AA|3bb7e6e65f20e31141b871b4fea88dc2; __yadk_uid=QBp8bLKHjCn5zS2J5r8xV7327R0wnqkU; douban-fav-remind=1; gr_user_id=0a41d8d1-fe39-4619-827a-17961cf31795; viewed="35013197_10769749_23008813_26282806_34912177_22139960_35003794_30249691_26616244_27035127"; push_noty_num=0; push_doumail_num=0; __utmv=30149280.21320; bid=gplG4aEN4Xc; ll="108288"; ap_v=0,6.0; __utma=30149280.819011260.1572087992.1604448803.1604453561.105; __utmc=30149280; __utmz=30149280.1604453561.105.65.utmcsr=accounts.douban.com|utmccn=(referral)|utmcmd=referral|utmcct=/; __gads=ID=eddb65558a1da756-223ab4f88bc400c8:T=1604453562:RT=1604453562:S=ALNI_MZGB_I69qmiL2tt3lm57JVX1i4r2w; __utmb=30149280.4.10.1604453561; dbcl2="213202515:Ip9mjwUAab4"; ck=wxUS; __utma=223695111.897479705.1572088003.1604448803.1604455298.71; __utmb=223695111.0.10.1604455298; __utmc=223695111; __utmz=223695111.1604455298.71.42.utmcsr=accounts.douban.com|utmccn=(referral)|utmcmd=referral|utmcct=/; _pk_ref.100001.4cf6=%5B%22%22%2C%22%22%2C1604455298%2C%22https%3A%2F%2Faccounts.douban.com%2F%22%5D; _pk_ses.100001.4cf6=*; _pk_id.100001.4cf6=e11874c5506d4ab1.1572088003.71.1604455342.1604450364.'
    }
 
    #总共爬取的页数
    pages = 100
    # 爬虫从此开始
    def start_requests(self):
        print('~~~~爬取列表: '+ self.domains)
        yield scrapy.Request(
            url = self.domains,
            headers=self.headers,
            callback=self.request_movies
        )
 
    # 分析列表页
    def request_movies(self, response):
        infos = response.text
        # 使用JSON模块解析响应结果
        infos = json.loads(infos)
        # 迭代影片信息列表
        for movie_info in infos['subjects']:
            print('~~~爬取电影: ' + movie_info['title'] + '/'+ movie_info['rate'])
            # 提取影片页面url，构造Request发送请求，并将item通过meta参数传递给影片页面解析函数
            yield scrapy.Request(
                url = str(movie_info['url']),
                headers = self.headers,
                callback = self.request_movie,
                dont_filter=True
            )
        #如果已经爬完pages或者当前标签下没有更多电影时退出
        if self.pages > 0 and len(infos['subjects']) == self.PAGE_LIMIT:
            self.pages -= 1
            self.page_start += self.PAGE_LIMIT
            url = self.BASE_URL % (self.MOVIE_TAG,self.PAGE_LIMIT,self.page_start)
            time.sleep(5)
            print('-----爬取列表: ' + url)
            yield scrapy.Request(
                url=url,
                headers=self.headers,
                callback=self.request_movies,
                dont_filter=True
            )
 
    # 分析详情页
    def request_movie(self, response):
        #组装数据
        movie_item = DoubanItem()
        title = response.css('div#content>h1>span:nth-child(1)::text').extract_first()
        t = re.findall('[\u3002\uff1b\uff0c\uff1a\u201c\u201d\uff08\uff09\u3001\uff1f\u300a\u300b\u4e00-\u9fa5_0-9]', title)
        #获取非info区域数据
        movie_item['title'] = ''.join(t)
        movie_item['date'] = response.css('div#content>h1>span.year::text').extract_first()[1:-1]
        movie_item['rate'] = response.css('strong.rating_num::text').extract_first()
        #movie_item['commentCount'] = response.css('div.rating_sum>a.rating_people>span::text').extract_first()
        #movie_item['start'] = '/'.join(response.css('span.rating_per::text').extract())
        #movie_item['better'] = '/'.join(response.css('div.rating_betterthan>a::text').extract())
        movie_item['abs'] = response.css('#link-report>span::text').extract_first().strip()
        movie_item['cover'] = response.css('#mainpic>a>img::attr(src)').extract_first()
 
        # 获取整个信息字符串
        info = response.css('div.subject div#info').xpath('string(.)').extract_first()
        # 提取所以字段名
        fields = [s.strip().replace(':', '') for s in response.css('div#info span.pl::text').extract()]
        # 提取所有字段的值
        values = [re.sub('\s+', '', s.strip()) for s in re.split('\s*(?:%s):\s*' % '|'.join(fields), info)][1:]
        # 处理列名称
        for i in range(len(fields)):
 
            if '导演' == fields[i]:
                fields[i] = 'director'
            if '编剧' == fields[i]:
                fields[i] = 'scriptwriter'
            if '主演' == fields[i]:
                fields[i] = 'actors'
            if '类型' == fields[i]:
                fields[i] = 'categories'
            if '制片国家/地区' == fields[i]:
                fields[i] = 'district'
            if '语言' == fields[i]:
                fields[i] = 'language'
            if '片长' == fields[i]:
                fields[i] = 'duration'
        # 将所有信息填入item
        other_info = list(zip(fields,values))
        for field,value  in other_info:
            if field in ['IMDb链接','上映日期','官方网站','又名']:
                other_info.remove((field,value))
        final_info = dict(other_info[:-1])
        movie_item.update(final_info)
 
        # 处理缺失字段
        if not 'director' in movie_item.keys():
            movie_item['director'] = '/'
        if not 'scriptwriter' in movie_item.keys():
            movie_item['scriptwriter'] = '/'
        if not 'actors' in movie_item.keys():
            movie_item['actors'] = '/'
        if not 'categories' in movie_item.keys():
            movie_item['categories'] = '/'
        if not 'district' in movie_item.keys():
            movie_item['district'] = '/'
        if not 'language' in movie_item.keys():
            movie_item['language'] = '/'
        if not 'duration' in movie_item.keys():
            movie_item['duration'] = '/'
        print('~完成爬取电影: ' + movie_item['title'] + '/' + movie_item['rate'])
        #将数据加入到字典中
        yield movie_item

        

          
        
        
        

          

          AI 代码解读
        
      
      

五，项目总结
项目采用前后端分离的方式来进行开发实现，并进行了数据的爬取操作，相关亮点比较多，业务功能相对较少。主要实现数据的爬取及展示以及相关的推荐功能。