【头歌】Scrapy爬虫（二）热门网站数据爬取

m0_748255262025-01-22 11:39
第1关：猫眼电影排行TOP100信息爬取

本关任务：爬取猫眼电影榜单TOP100榜 的100部电影信息保存到本地MySQL数据库。

相关知识

为了完成本关任务，你需要掌握：

MySQL相关知识（默认已掌握）；

Scrapy settings.py文件设置的具体含义；

网站多页内容的爬取(翻页)；

数据匹配详解。

step1/maoyan/maoyan/items.py

# -*- coding: utf-8 -*-

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html

import scrapy

class MaoyanItem(scrapy.Item):

    #********** Begin **********#
    name = scrapy.Field()
    starts = scrapy.Field()
    releasetime = scrapy.Field()
    score = scrapy.Field()
    
    #********** End **********#

step1/maoyan/maoyan/pipelines.py

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
import pymysql
from maoyan import settings
class MaoyanPipeline(object):
    def process_item(self, item, spider):
        #********** Begin **********#
        #1.连接数据库
        connection = pymysql.connect(
            host='localhost',  # 连接的是本地数据库
            port=3306,         #数据库端口名
            user='root',        # 自己的mysql用户名
            passwd='123123',  # 自己的密码
            db='mydb',      # 数据库的名字
            charset='utf8',     # 默认的编码方式
        )                    
        #2.建表、给表插入数据，完成后关闭数据库连接，return返回item
        name = item['name']
        starts = item['starts']
        releasetime = item['releasetime']
        score = item['score']
        try:
            with connection.cursor() as cursor:
                sql1 = 'Create Table If Not Exists mymovies(name varchar(50) CHARACTER SET utf8 NOT NULL,starts text CHARACTER SET utf8 NOT NULL,releasetime varchar(50) CHARACTER SET utf8 DEFAULT NULL,score varchar(20) CHARACTER SET utf8 NOT NULL,PRIMARY KEY(name))'
                # 单章小说的写入
                sql2 = 'Insert into mymovies values ('%s','%s','%s','%s')' % (name, starts, releasetime, score)
                cursor.execute(sql1)
                cursor.execute(sql2)
            # 提交本次插入的记录
            connection.commit()
        finally:
            # 关闭连接
            connection.close()    
            return item
        #********** End **********#

step1/maoyan/maoyan/spiders/movies.py

# -*- coding: utf-8 -*-
import scrapy
from maoyan.items import MaoyanItem

class MoviesSpider(scrapy.Spider):
    name = 'movies'
    allowed_domains = ['127.0.0.1']
    offset = 0
    url = "http://127.0.0.1:8080/board/4?offset="
    #********** Begin **********#
    #1.对url进行定制，为翻页做准备
    start_urls = [url + str(offset)]
    #2.定义爬虫函数parse()
    def parse(self, response):
        item = MaoyanItem()
        movies = response.xpath("//div[ @class ='board-item-content']")
        for each in movies:
            #电影名
            name = each.xpath(".//div/p/a/text()").extract()[0]
            #主演明星
            starts = each.xpath(".//div[1]/p/text()").extract()[0]
            #上映时间
            releasetime = each.xpath(".//div[1]/p[3]/text()").extract()[0]
            score1 = each.xpath(".//div[2]/p/i[1]/text()").extract()[0]
            score2 = each.xpath(".//div[2]/p/i[2]/text()").extract()[0]
            #评分
            score = score1 + score2
            item['name'] = name
            item['starts'] = starts
            item['releasetime'] = releasetime
            item['score'] = score
            yield item
    #3.在函数的最后offset自加10，然后重新发出请求实现翻页功能
        if self.offset < 90:
            self.offset += 10
            yield scrapy.Request(self.url+str(self.offset), callback=self.parse)

    #********** End **********#
第2关：小说网站玄幻分类第一页小说爬取

本关任务：爬目标网页的3本小说保存到本

为了完成本关任务，你需要掌握：

xpath匹配：循环获取相同标签下的内容；

多个item类的处理；

深入二级页面的数据爬取。

地MySQL数据库，目标网页为全书网玄幻分类首页。

step2/NovelProject/NovelProject/items.py

# -*- coding: utf-8 -*-

# Define here the models for your scraped items
#
# See documentation in:
# https://doc.scrapy.org/en/latest/topics/items.html

import scrapy
#存放全部小说信息
class NovelprojectItem(scrapy.Item):
    #********** Begin **********#
    name = scrapy.Field()
    author = scrapy.Field()
    state = scrapy.Field()
    description = scrapy.Field()
    
    
    #********** End **********#

#单独存放小说章节
class NovelprojectItem2(scrapy.Item):
    #********** Begin **********#
    tablename = scrapy.Field()           # 表命名时需要
    title = scrapy.Field()
    
    #********** End **********#

step2/NovelProject/NovelProject/pipelines.py

# -*- coding: utf-8 -*-

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html
import pymysql
from NovelProject.items import NovelprojectItem,NovelprojectItem2
class NovelprojectPipeline(object):
    def process_item(self, item, spider):

        #********** Begin **********#
    
        #1.和本地的数据库mydb建立连接        
        connection = pymysql.connect(
            host='localhost',    # 连接的是本地数据库
            port = 3306,         # 端口号
            user='root',         # 自己的mysql用户名
            passwd='123123',     # 自己的密码
            db='mydb',           # 数据库的名字
            charset='utf8',      # 默认的编码方式：
        )
        
        
        #2.处理来自NovelprojectItem的item（处理完成后return返回item）
        if isinstance(item, NovelprojectItem):
            # 从items里取出数据
            name = item['name']
            author = item['author']
            state = item['state']
            description = item['description']
            try:
                with connection.cursor() as cursor:
                    # 小说信息写入
                    sql1 = 'Create Table If Not Exists novel(name varchar(20) CHARACTER SET utf8 NOT NULL,author varchar(10) CHARACTER SET utf8,state varchar(20) CHARACTER SET utf8,description text CHARACTER SET utf8,PRIMARY KEY (name))'
                    sql2 = 'Insert into novel values ('%s','%s','%s','%s')' % (name, author, state, description)
                    cursor.execute(sql1)
                    cursor.execute(sql2)
                # 提交本次插入的记录
                connection.commit()
            finally:
                # 关闭连接
                connection.close()
            return item       
        
        #3.处理来自NovelprojectItem2的item（处理完成后return返回item）
        elif isinstance(item, NovelprojectItem2):
            tablename = item['tablename']
            title = item['title']
            try:
                with connection.cursor() as cursor:
                    # 小说章节的写入
                    sql3 = 'Create Table If Not Exists %s(title varchar(20) CHARACTER SET utf8 NOT NULL,PRIMARY KEY (title))' % tablename
                    sql4 = 'Insert into %s values ('%s')' % (tablename, title)
                    cursor.execute(sql3)
                    cursor.execute(sql4)
                connection.commit()
            finally:
                connection.close()
            return item
        
        #********** End **********#

step2/NovelProject/NovelProject/spiders/novel.py

# -*- coding: utf-8 -*-
import scrapy
import re
from scrapy.http import Request
from NovelProject.items import NovelprojectItem
from NovelProject.items import NovelprojectItem2

class NovelSpider(scrapy.Spider):
    name = 'novel'
    allowed_domains = ['127.0.0.1']
    start_urls = ['http://127.0.0.1:8000/list/1_1.html']   #全书网玄幻魔法类第一页

    #********** Begin **********#
    #1.定义函数，通过'马上阅读'获取每一本书的 URL
    def parse(self, response):
        book_urls = response.xpath('//li/a[@class="l mr10"]/@href').extract()
        three_book_urls = book_urls[0:3]  # 只取3本
        for book_url in three_book_urls:
            yield Request(book_url, callback=self.parse_read)
    #2.定义函数，进入小说简介页面，获取信息，得到后yield返回给pipelines处理，并获取'开始阅读'的url，进入章节目录
    def parse_read(self, response):
        item = NovelprojectItem()
        # 小说名字
        name = response.xpath('//div[@class="b-info"]/h1/text()').extract_first()
        #小说简介
        description = response.xpath('//div[@class="infoDetail"]/div/text()').extract_first()
        # 小说连载状态
        state = response.xpath('//div[@class="bookDetail"]/dl[1]/dd/text()').extract_first()
        # 作者名字
        author = response.xpath('//div[@class="bookDetail"]/dl[2]/dd/text()').extract_first()
        item['name'] = name
        item['description'] = description
        item['state'] = state
        item['author'] = author
        yield item
        # 获取开始阅读按钮的URL，进入章节目录
        read_url = response.xpath('//a[@class="reader"]/@href').extract()[0]
        yield Request(read_url, callback=self.parse_info)
    #3.定义函数，进入章节目录，获取小说章节名并yield返回
    def parse_info(self, response):
        item = NovelprojectItem2()
        tablename = response.xpath('//div[@class="main-index"]/a[3]/text()').extract_first()
        titles = response.xpath('//div[@class="clearfix dirconone"]/li')
        for each in titles:
            title = each.xpath('.//a/text()').extract_first()
            item['tablename'] = tablename
            item['title'] = title
            yield item

在测试行会输出你mydb数据库中表的个数，应该有4个表，预期输出为：

相关推荐
德迅云安全-甲锵3 小时前
网络爬虫技术如何影响网络安全的
爬虫
小盼江21 小时前
Hadoop美食推荐系统 爬虫1.8w+数据 协同过滤余弦函数推荐美食 Springboot Vue Element-UI前后端分离
hadoop·爬虫·美食
m0_748248771 天前
小白爬虫——selenium入门超详细教程
爬虫·selenium·测试工具
流星Studio2 天前
某Websocket反爬逆向分析+请求加解密+还原html
爬虫·python·js逆向
程序设计实验室2 天前
编写爬虫下载公众号上好看的壁纸
爬虫·python
小白学大数据2 天前
Django多线程爬虫：突破数据抓取瓶颈
数据库·爬虫·scrapy·数据分析·django
B站计算机毕业设计超人2 天前
计算机毕业设计Python+卷积神经网络租房推荐系统 租房大屏可视化 租房爬虫 hadoop spark 58同城租房爬虫 房源推荐系统
大数据·爬虫·python·机器学习·课程设计·数据可视化·推荐算法
B站计算机毕业设计超人2 天前
计算机毕业设计PySpark+Hadoop+Hive机票预测 飞机票航班数据分析可视化大屏 航班预测系统 机票爬虫 飞机票推荐系统 大数据毕业设计
大数据·hadoop·爬虫·python·spark·课程设计·数据可视化
热门推荐
01Windows10安装PCL1.14.0及点云配准02(欧拉)openEuler系统添加网卡文件配置流程、(欧拉)openEuler系统手动配置ipv6地址流程、(欧拉)openEuler系统网络管理说明03半导体应用系统一些小知识收集(strip&wafer mapping,EAP&scada)04Dell服务器升级ubuntu 22.04失败解决05密码学原理技术-第六章-introduction to pulibc-key cryptography06优化手机性能，解决卡顿问题：关闭这3个微信开关，释放内存空间07leetcode - 1769. Minimum Number of Operations to Move All Balls to Each Box08centos7 init.d 和system.d09渗透测试之SQLMAP工具详解 kali自带SQLmap解释 重点sqlmap --tamper 使用方式详解 搞完你就很nice了10小米路由器简单救砖