python爬虫(4)——scrapy框架

系统 130 0

安装

urllib库更适合写爬虫文件,scrapy更适合做爬虫项目。

步骤:

  1. 先更改pip源,国外的太慢了,参考:https://www.jb51.net/article/159167.htm
  2. 升级pip:python -m pip install --upgrade pip
  3. pip install wheel
  4. pip install lxml
  5. pip install Twisted
  6. pip install scrapy

常用命令

核心目录 python爬虫(4)——scrapy框架_第1张图片

python爬虫(4)——scrapy框架_第2张图片

  1. 新建项目:scrapy startproject mcq
  2. 运行独立的爬虫文件(不是项目):比如

python爬虫(4)——scrapy框架_第3张图片

然后输入命令scrapy runspider gg.py

  1. 获取设置信息:cd到项目,比如scrapy settings --get BOT_NAME

  2. 交互式爬取:scrapy shell http://www.baidu.com,可以使用python代码

  3. scrapy版本信息:scrapy version

  4. 爬取并且在浏览器显示:scrapy view http://news.1152.com,将网页下载到本地打开

  5. 测试本地硬件性能:scrapy bench ,每分钟可以爬取多少页面

  6. 依据模板创建爬虫文件:scrapy genspider -l ,有以下模板 python爬虫(4)——scrapy框架_第4张图片

    选择basic,scrapy genspider -t basic haha baidu.com (注意:这里填可爬取的域名,域名是不以www、edu……开头的)

python爬虫(4)——scrapy框架_第5张图片

  1. 测试爬虫文件是否合规:scrapy check haha

  2. 运行爬虫项目下的文件:scrapy crawl haha
    不显示中间的日志信息:scrapy crawl haha --nolog

  3. 查看当前项目下可用的爬虫文件:scrapy list

  4. 指定某个爬虫文件获取url:
    F:\scrapy项目\mcq>scrapy parse --spider=haha http://www.baidu.com

XPath表达式

XPath与正则简单对比:

  1. XPath表达式效率会高一点
  2. 正则表达式功能强一点
  3. 一般来说,优先选择XPath,但是XPath解决不了的问题我们就选正则去解决

/:逐层提取

text()提取标签下面的文本

如要提取标题:/html/head/title/text()

//标签名:提取所有名为……的标签

如提取所有的div标签://div

//标签名[@属性='属性值']:提取属性为……的标签

@属性表示取某个属性值

使用scrapy做当当网商品爬虫

新建爬虫项目:F:\scrapy项目>scrapy startproject dangdang

F:\scrapy项目>cd dangdang

F:\scrapy项目\dangdang>scrapy genspider -t basic dd dangdang.com

python爬虫(4)——scrapy框架_第6张图片

修改items.py:

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

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

import scrapy


class DangdangItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title=scrapy.Field() #商品标题
    link=scrapy.Field() #商品链接
    comment=scrapy.Field() #商品评论
    
          
        

我们翻一下页,分析两个链接:

http://category.dangdang.com/pg2-cid4008154.html

http://category.dangdang.com/pg3-cid4008154.html

可以找到初始链接:http://category.dangdang.com/pg1-cid4008154.html

分析页面源码,可以从name="itemlist-title" 下手,因为这个正好有48个结果,即一页商品的数量。

ctrl+f 条评论,可以发现正好有48条记录。

dd.py:

          
            # -*- coding: utf-8 -*-
import scrapy
from dangdang.items import DangdangItem
from scrapy.http import Request
class DdSpider(scrapy.Spider):
    name = 'dd'
    allowed_domains = ['dangdang.com']
    start_urls = ['http://category.dangdang.com/pg1-cid4008154.html']

    def parse(self, response):
        item=DangdangItem()
        item["title"]=response.xpath("//a[@name='itemlist-title']/@title").extract()
        item["link"]=response.xpath("//a[@name='itemlist-title']/@href").extract()
        item["comment"]=response.xpath("//a[@name='itemlist-review']/text()").extract()
        # print(item["title"])
        yield item
        for i in range(2,11): #爬取2~10页
            url='http://category.dangdang.com/pg'+str(i)+'-cid4008154.html'
            yield Request(url, callback=self.parse)

          
        

对于dd里的Request:

url: 就是需要请求,并进行下一步处理的url
callback: 指定该请求返回的Response,由那个函数来处理。

先把settings.py的robots改为False:

settings.py:

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

# Scrapy settings for dangdang project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://docs.scrapy.org/en/latest/topics/settings.html
#     https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://docs.scrapy.org/en/latest/topics/spider-middleware.html

BOT_NAME = 'dangdang'

SPIDER_MODULES = ['dangdang.spiders']
NEWSPIDER_MODULE = 'dangdang.spiders'


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'dangdang (+http://www.yourdomain.com)'

# Obey robots.txt rules
ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32

# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

# Disable cookies (enabled by default)
#COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

# Override the default request headers:
#DEFAULT_REQUEST_HEADERS = {
#   'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#   'Accept-Language': 'en',
#}

# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    'dangdang.middlewares.DangdangSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'dangdang.middlewares.DangdangDownloaderMiddleware': 543,
#}

# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    'scrapy.extensions.telnet.TelnetConsole': None,
#}

# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html

ITEM_PIPELINES = {
   'dangdang.pipelines.DangdangPipeline': 300,
}
# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
          
        

运行:F:\scrapy项目\dangdang>scrapy crawl dd --nolog

去settings.py将pipeline开启: python爬虫(4)——scrapy框架_第7张图片

pipelines.py:

          
            # -*- coding: utf-8 -*-
import pymysql
# 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


class DangdangPipeline(object):
    def process_item(self, item, spider):
        conn=pymysql.connect(host='127.0.0.1',user="root",passwd="123456",db="dangdang")
        cursor = conn.cursor()
        for i in range(len(item["title"])):
            title=item["title"][i]
            link=item["link"][i]
            comment=item["comment"][i]
            # print(title+":"+link+":"+comment)
            sql="insert into goods(title,link,comment) values('%s','%s','%s')"%(title,link,comment)
            # print(sql)
            try:
                cursor.execute(sql)
                conn.commit()
            except Exception as e:
                print(e)
        conn.close()
        return item

          
        

登录mysql,创建一个数据库:mysql> create database dangdang;

mysql> use dangdang

mysql> create table goods(id int(32) auto_increment primary key,title varchar(100),link varchar(100) unique,comment varchar(100));

最后运行 scrapy crawl dd --nolog

python爬虫(4)——scrapy框架_第8张图片

每页48条,48*10=480,爬取成功!

完整项目源代码参考我的github

scrapy模拟登陆实战

以这个网站为例http://edu.iqianyue.com/,我们不爬取内容,只模拟登陆,所以不需要写item.py

点击登陆,用fiddler查看真正的登陆网址:http://edu.iqianyue.com/index_user_login

python爬虫(4)——scrapy框架_第9张图片

修改login.py:

          
            # -*- coding: utf-8 -*-
import scrapy
from scrapy.http import FormRequest, Request


class LoginSpider(scrapy.Spider):
    name = 'login'
    allowed_domains = ['iqianyue.com']
    start_urls = ['http://iqianyue.com/']
    header={"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:68.0) Gecko/20100101 Firefox/68.0"}
    #编写start_request()方法,第一次会默认调取该方法中的请求
    def start_requests(self):
        #首先爬一次登录页,然后进入回调函数parse()
        return [Request("http://edu.iqianyue.com/index_user_login",meta={"cookiejar":1},callback=self.parse)]
    def parse(self, response):
        #设置要传递的post信息,此时没有验证码字段
        data={
            "number":"swineherd",
            "passwd":"123",
        }
        print("登录中……")
        #通过ForRequest.from_response()进行登录
        return FormRequest.from_response(response,
                                          #设置cookie信息
                                          meta={"cookiejar":response.meta["cookiejar"]},
                                          #设置headers信息模拟成浏览器
                                          headers=self.header,
                                          #设置post表单中的数据
                                          formdata=data,
                                          #设置回调函数
                                          callback=self.next,
                                          )
    def next(self,response):
        data=response.body
        fp=open("a.html","wb")
        fp.write(data)
        fp.close()
        print(response.xpath("/html/head/title/text()").extract())
        #登录后访问
        yield Request("http://edu.iqianyue.com/index_user_index",callback=self.next2,meta={"cookiejar":1})
    def next2(self,response):
        data=response.body
        fp=open("b.html","wb")
        fp.write(data)
        fp.close()
        print(response.xpath("/html/head/title/text()").extract())
          
        

python爬虫(4)——scrapy框架_第10张图片

scrapy新闻爬虫实战

目标:爬取百度新闻首页所有新闻

F:>cd scrapy项目

F:\scrapy项目>scrapy startproject baidunews

F:\scrapy项目>cd baidunews

F:\scrapy项目\baidunews>scrapy genspider -t basic n1 baidu.com

抓包分析

找到json文件:
python爬虫(4)——scrapy框架_第11张图片

idle查看一下 python爬虫(4)——scrapy框架_第12张图片

首页ctrl+f: python爬虫(4)——scrapy框架_第13张图片

在首页往下拖触发所有新闻,在fiddler中找到存储url、title等等的js文件(并不是每一个js文件都有用)

发现不止js文件有新闻信息,还有别的,要细心在fiddler找!

http://news.baidu.com/widget?id=LocalNews&ajax=json&t=1566824493194

http://news.baidu.com/widget?id=civilnews&t=1566824634139

http://news.baidu.com/widget?id=InternationalNews&t=1566824931323

http://news.baidu.com/widget?id=EnterNews&t=1566824931341

http://news.baidu.com/widget?id=SportNews&t=1566824931358

http://news.baidu.com/widget?id=FinanceNews&t=1566824931376

http://news.baidu.com/widget?id=TechNews&t=1566824931407

http://news.baidu.com/widget?id=MilitaryNews&t=1566824931439

http://news.baidu.com/widget?id=InternetNews&t=1566824931456

http://news.baidu.com/widget?id=DiscoveryNews&t=1566824931473

http://news.baidu.com/widget?id=LadyNews&t=1566824931490

http://news.baidu.com/widget?id=HealthNews&t=1566824931506

http://news.baidu.com/widget?id=PicWall&t=1566824931522

我们可以发现真正影响新闻信息的是widget?后面的id值

写个脚本把id提取出来: python爬虫(4)——scrapy框架_第14张图片

两种不同的链接的源代码的url也不同:

items.py:

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

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

import scrapy


class BaidunewsItem(scrapy.Item):
    # define the fields for your item here like:
    # name = scrapy.Field()
    title=scrapy.Field()
    link=scrapy.Field()
    content=scrapy.Field()
          
        

n1.py:

          
            # -*- coding: utf-8 -*-
import scrapy
from baidunews.items import BaidunewsItem #从核心目录
from scrapy.http import Request
import re
import time
class N1Spider(scrapy.Spider):
    name = 'n1'
    allowed_domains = ['baidu.com']
    start_urls = ["http://news.baidu.com/widget?id=LocalNews&ajax=json"]
    allid=['LocalNews', 'civilnews', 'InternationalNews', 'EnterNews', 'SportNews', 'FinanceNews', 'TechNews', 'MilitaryNews', 'InternetNews', 'DiscoveryNews', 'LadyNews', 'HealthNews', 'PicWall']
    allurl=[]
    for k in range(len(allid)):
        thisurl="http://news.baidu.com/widget?id="+allid[k]+"&ajax=json"
        allurl.append(thisurl)

    def parse(self, response):
        while True: #每隔5分钟爬一次
            for m in range(len(self.allurl)):
                yield Request(self.allurl[m], callback=self.next)
                time.sleep(300) #单位为秒
    cnt=0
    def next(self,response):
        print("第" + str(self.cnt) + "个栏目")
        self.cnt+=1
        data=response.body.decode("utf-8","ignore")
        pat1='"m_url":"(.*?)"'
        pat2='"url":"(.*?)"'
        url1=re.compile(pat1,re.S).findall(data)
        url2=re.compile(pat2,re.S).findall(data)
        if(len(url1)!=0):
            url=url1
        else :
            url=url2
        for i in range(len(url)):
            thisurl=re.sub("\\\/","/",url[i])
            print(thisurl)
            yield Request(thisurl,callback=self.next2)
    def next2(self,response):
        item=BaidunewsItem()
        item["link"]=response.url
        item["title"]=response.xpath("/html/head/title/text()")
        item["content"]=response.body
        print(item)
        yield item
          
        

将settings的pipeline开启:

将robots改为False,scrapy crawl n1 --nolog即可运行

scrapy豆瓣网登录爬虫

要在settings里加上:

USER_AGENT = 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_3) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.54 Safari/536.5'

关于scrapy.http.FormRequest和scrapy.http.FormRequest.from_response的用法区别参考这篇博客:https://blog.csdn.net/qq_33472765/article/details/80958820

d1.py:

          
            # -*- coding: utf-8 -*-
import scrapy
from scrapy.http import Request, FormRequest


class D1Spider(scrapy.Spider):
    name = 'd1'
    allowed_domains = ['douban.com']
    # start_urls = ['http://douban.com/']
    headers = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:68.0) Gecko/20100101 Firefox/68.0"}

    def start_requests(self):
        # 首先爬一次登录页,然后进入回调函数parse()
        print("开始:")
        return [Request("https://accounts.douban.com/passport/login",meta={"cookiejar":1},callback=self.login)]

    def login(self, response):
        #判断验证码
        captcha=response.xpath("//")
        data = {
            "ck": "",
            "name": "***",
            "password": "***",
            "remember": "false",
            "ticket": ""
        }
        print("登陆中……")
        return FormRequest(url="https://accounts.douban.com/j/mobile/login/basic",
                                         # 设置cookie信息
                                         meta={"cookiejar": response.meta["cookiejar"]},
                                         # 设置headers信息模拟成浏览器
                                         headers=self.headers,
                                         # 设置post表单中的数据
                                         formdata=data,
                                         # 设置回调函数
                                         callback=self.next,
                                         )
    def next(self,response):
        #跳转到个人中心
        yield Request("https://www.douban.com/people/202921494/",meta={"cookiejar":1},callback=self.next2)
    def next2(self, response):
        title = response.xpath("/html/head/title/text()").extract()
        print(title)
          
        

现在的豆瓣是滑块验证码,对于现在的我这个菜鸡还不会处理。

在urllib中使用XPath表达式

先安装lxml模块:pip install lxml,然后将网页数据通过lxml下的etree转化为treedata的形式。

          
            import urllib.request
from lxml import etree
data=urllib.request.urlopen("http://www.baidu.com").read().decode("utf-8","ignore")
treedata=etree.HTML(data)
title=treedata.xpath("//title/text()")
print(title)
          
        

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