python 爬虫 9 （scrapy实例：翻页爬取、爬个人页、存入mysql、redis）

怼烎@ 2023-10-08 12:13 24阅读 0赞

#### 文章目录 ####

*   *  写在前面
     *   *  1、新片场翻页爬取
         *   *  1.1、模仿登录
             *  1.2、访问上限
         *  2、爬取个人详情页
         *  3、存入mysql
         *  4、存入redis

### 写在前面 ###

> 本篇笔记接【python 爬虫  
> 7】：https://blog.csdn.net/a\_\_int\_\_/article/details/104762424

#### 1、新片场翻页爬取 ####

查看每页连接  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70]  
爬取连接  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 1]

pages = response.xpath('//div[@class="page"]/a/@href').extract()
            for page in pages:
                yield response.follow(page, self.parse)

我们发现最多只能爬取到第22页  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 2]  
爬22页后面的内容需要登录

##### 1.1、模仿登录 #####

点击登录，抓取cookie  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 3]  
把这串证书复制下来  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 4]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 5]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 6]  
settings：  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 7]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 8]  
重新执行，发现抓取到100多条的时候就停止了。

##### 1.2、访问上限 #####

找到PHPSESSID  
![在这里插入图片描述][20200412180614118.png]  
查看这串字符，长度为26  
![在这里插入图片描述][20200412181121400.png]  
我们写一个PHPSESSID生成器  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 9]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 10]  
现在就能成功访问多条数据了  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 11]

#### 2、爬取个人详情页 ####

![在这里插入图片描述][20200412214937270.png]  
把爬取视频详情页 打开  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 12]  
打开详情页发现每个用户详情页地址通过data-userid变化  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 13]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 14]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 15]  
爬取用户id  
![在这里插入图片描述][20200412232316393.png]

creator_list = response.xpath('//@data-userid').extract()
            creator_url = 'https://www.xinpianchang.com/u%s'
            print(creator_list)
            for creator in creator_list:
                request = response.follow(creator_url % creator, self.parse_composer)
                request.meta['cid'] = creator
                yield request

![在这里插入图片描述][20200412232354283.png]

def parse_composer(self, response):
            banner = response.xpath('//div[@class="banner-wrap"]/@style').get()
            composer = {
        }
            composer['banner'], = re.findall('background-image:url\((.+?)\)', banner)
            composer['name'] = response.xpath('//p[contains(@class,"creator-name")]/text()').get()
    
            yield composer

运行之后其他的都没问题，visit\_userid\_10037339=1; 这个值会被迭代  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 16]  
访问网页发现，这个值在每次切换个人详情页的时候，就会被设置一次，每隔30几秒会自动删除，这30几秒内连续访问会迭代  
![在这里插入图片描述][20200412232649526.png]  
退出登录后访问发现，访问个人详情页是不需要登录的，所以我们关掉这个页面访问时的cookie

![在这里插入图片描述][20200412233459224.png]  
再次抓取就没有这个问题了  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 17]

#### 3、存入mysql ####

创建数据库xpc： CREATE DATABASE xpc;  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 18]  
新建表composer  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 19]

CREATE TABLE `composer`  (
     `cid` bigint(20) NOT NULL,
     `name` varchar(512)  DEFAULT NULL,
    `banner` varchar(512)  DEFAULT NULL,
    PRIMARY KEY (`cid`) USING BTREE
     ) ENGINE = InnoDB CHARSET = utf8mb4;

items.py

import scrapy
    from scrapy import Field
    
    
    class ComposerItem(scrapy.Item):
        """保存个人详情页信息"""
        table_name = 'composer'
    
        cid = Field()
        banner = Field()
        name = Field()

settings.py  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 20]  
pipelines.py

# -*- coding: utf-8 -*-
    
    # Define your item pipelines here
    #
    # Don't forget to add your pipeline to the ITEM_PIPELINES setting
    # See: https://docs.scrapy.org/en/latest/topics/item-pipeline.html
    import pymysql
    import redis
    from scrapy.exceptions import DropItem
    
    
    class RedisPipeline(object):
        def open_spider(self, spider):
            self.r = redis.Redis(host='127.0.0.1')
    
        def process_item(self, item, spider):
            if self.r.sadd(spider.name, item['name']):
                return item
            # 如果添加name失败就自动删除item，并停止执行process_item
            raise DropItem
    
    
    class MysqlPipeline(object):
        def open_spider(self, spider):
            self.conn = pymysql.connect(
                host="127.0.0.1",
                port=3306,
                db="xpc",
                user="root",
                password="root",
                charset="utf8",
            )
            self.cur = self.conn.cursor()
    
        def close_spider(self, spider):
            self.cur.close()
            self.conn.close()
    
        def process_item(self, item, spider):
            keys, values = zip(*item.items())
            sql = "insert into {} ({}) values ({})" \
                  " ON DUPLICATE KEY UPDATE {};".format(
                item.table_name,
                ','.join(keys),
                ','.join(["'%s'"] * len(values)),
                ','.join(["{}='%s'".format(k) for k in keys])
            )
            sqlp = (sql % (values*2))
            self.cur.execute(sqlp)
            self.conn.commit()
            # 显示sql语句
            print(self.cur._last_executed)
            return item

修改discovery.py

# -*- coding: utf-8 -*-
    import json
    import random
    import re
    
    import scrapy
    from scrapy import Request
    from xpc.items import ComposerItem
    
    str = 'qazwsxedcrfvtgbyhnujmikolp1234567890'
    cookies = dict(Authorization='F8FB7C7E1E8354A671E83548091E835A4181E83528E62CE43391')
    
    
    def gen_sessionid():
        return ''.join(random.choices(str, k=26))
    
    
    class DiscoverySpider(scrapy.Spider):
        name = 'discovery'
        allowed_domains = ['xinpianchang.com', 'openapi-vtom.vmovier.com']
        start_urls = ['https://www.xinpianchang.com/channel/index/sort-like?from=navigator']
        page_count = 0
    
        def parse(self, response):
            self.page_count += 1
            if self.page_count >= 100:
                cookies.update(PHPSESSID=gen_sessionid())
                self.page_count = 0
    
            pid_list = response.xpath('//@data-articleid').extract()
            url = "https://www.xinpianchang.com/a%s?from=ArticleList"
            for pid in pid_list:
                yield response.follow(url % pid, self.parse_post)
            pages = response.xpath('//div[@class="page"]/a/@href').extract()
            for page in pages:
                yield response.follow(page, self.parse, cookies=cookies)
    
        def parse_post(self, response):
            # post = {}
            # 这里get()和extract_first()一样
            # post['title'] = response.xpath('//div[@class="title-wrap"]/h3/text()').get()
            # categorys = response.xpath('//span[contains(@class,"cate")]//text()').extract()
            # post['category'] = ''.join([category.strip() for category in categorys])
            # post['created_at'] = response.xpath('//span[contains(@class,"update-time")]/i//text()').get()
            # post['play_counts'] = response.xpath('//i[contains(@class,"play-counts")]/@data-curplaycounts').get()
            # vid, = re.findall('vid: \"(\w+)\",', response.text)
            # video_url = 'https://openapi-vtom.vmovier.com/v3/video/%s?expand=resource&usage=xpc_web'
            # request = Request(video_url % vid, callback=self.parse_video)
            # request.meta['post'] = post
            # yield request
    
            creator_list = response.xpath('//@data-userid').extract()
            creator_url = 'https://www.xinpianchang.com/u%s'
            for creator in creator_list:
                request = response.follow(creator_url % creator, self.parse_composer)
                request.meta['cid'] = creator
                request.meta['dont_merge_cookies'] = True
                yield request
    
        # def parse_video(self, response):
        #     # post = response.meta['post']
        #     result = json.loads(response.text)
        #     if 'resource' in result['data']:
        #         post['video'] = result['data']['resource']['default']['url']
        #     else:
        #         d = result['data']['third']['data']
        #         post['video'] = d.get('iframe_url', d.get('swf', ''))
        #     yield post
    
        def parse_composer(self, response):
            banner = response.xpath('//div[@class="banner-wrap"]/@style').get()
            composer = ComposerItem()
            composer['cid'] = int(response.meta['cid'])
            banner, = re.findall('background-image:url\((.+?)\)', banner)
            composer['banner'] = banner.replace('\t', '').replace(' ', '')
            name = response.xpath('//p[contains(@class,"creator-name")]/text()').get()
            composer['name'] = name.replace('\t', '').replace(' ', '')
    
            yield composer

![在这里插入图片描述][20200413164100484.png]

#### 4、存入redis ####

settings.py  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 21]

SCHEDULER = "scrapy_redis.scheduler.Scheduler"
    DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
    REDIS_URL = 'redis://127.0.0.1:6379'

启动redis  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 22]  
查看redis的key  
![在这里插入图片描述][20200413165213780.png]  
安装scrapy-redis：pip install scrapy-redis  
![在这里插入图片描述][20200413165327632.png]  
启动爬虫  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 23]  
查看redis  
![在这里插入图片描述][20200413165945107.png]  
![在这里插入图片描述][20200413174136700.png]  
查看discovery:dupefilter里面存的内容： srandmember discovery:dupefilter  
![在这里插入图片描述][20200413205724900.png]  
zrange discovery:requests 0 0 withscores  
![在这里插入图片描述][20200413210520994.png]

在ipython里面解析字符![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 24]  
分析这串数据，发现它是列表包含元组这样的结构  
![在这里插入图片描述][2020041321180251.png]  
用pickle进行二进制序列化  
![在这里插入图片描述][20200413211942405.png]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 25]

In [1]: import redis
    
    In [2]: r = redis.Redis(host='127.0.0.1')
    
    In [3]: m = r.zrange('discovery:requests',0,0,withscores=True)
    
    In [7]: import pickle
    
    In [9]: (a,b), = m
    
    In [10]: pickle.loads(a)

将数据存入redis（一般不会把redis当数据库用）

settings.py  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 26]

> ‘scrapy\_redis.pipelines.RedisPipeline’: 301,

运行爬虫  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 27]  
查看redis  
![在这里插入图片描述][20200413220445314.png]

[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70]: https://img-blog.csdnimg.cn/20200412153333251.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 1]: https://img-blog.csdnimg.cn/20200412172024822.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 2]: https://img-blog.csdnimg.cn/20200412172129672.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 3]: https://img-blog.csdnimg.cn/20200412173453917.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 4]: https://img-blog.csdnimg.cn/2020041217370314.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 5]: https://img-blog.csdnimg.cn/20200412174005435.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 6]: https://img-blog.csdnimg.cn/20200412182210601.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 7]: https://img-blog.csdnimg.cn/20200412174200470.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f_size_16_color_FFFFFF_t_70 8]: https://img-blog.csdnimg.cn/2020041217434892.png?x-oss-process=image/watermark,type_ZmFuZ3poZW5naGVpdGk,shadow_10,text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2FfX2ludF9f,size_16,color_FFFFFF,t_70
[20200412180614118.png]: https://img-blog.csdnimg.cn/20200412180614118.png
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