一、 使用scrapy.Selector或BeautifulSoup，实现以下需求（30分）
（1）读取给定的dangdang.html页面内容，注：编码为gbk（5分）
（2）获取页面中所有图书的名称，价格，作者，出版社及图书图片的url地址（20分）
（3）将获取的信息保存至文件（excel、csv、json、txt格式均可）（5分）
网页文件dangdang.html文件下载链接: https://pan.baidu.com/s/1awbG5zqOMdnWzXee7TZm6A 密码: 3urs
1.1使用BeautifulSoup解决
from bs4 import BeautifulSoup as bs
import pandas as pd
def cssFind(book,cssSelector,nth=1):
if len(book.select(cssSelector)) >= nth:
return book.select(cssSelector)[nth-1].text.strip()
else:
return ''
if __name__ == "__main__":
with open("dangdang.html",encoding='gbk') as file:
html = file.read()
soup = bs(html,'lxml')
book_list = soup.select("div ul.bigimg li")
result_list = []
for book in book_list:
item = {}
item['name'] = book.select("a.pic")[0]['title']
item['now_price'] = cssFind(book,"span.search_now_price")
item['pre_price'] = cssFind(book,"span.search_pre_price")
item['author'] = book.select("p.search_book_author a")[0]['title']
item['publisher'] = book.select("p.search_book_author span a")[-1].text
item['detailUrl'] = book.select("p.name a")[0]['href']
item['imageUrl'] = book.select("a.pic img")[0]['src']
if item['imageUrl'] == "images/model/guan/url_none.png":
item['imageUrl'] = book.select("a.pic img")[0]['data-original']
result_list.append(item)
df = pd.DataFrame(result_list,columns=result_list[0].keys())
df.to_excel("当当图书信息.xlsx")
1.2使用scrapy.selector解决
from scrapy.selector import Selector
import pandas as pd
if __name__ == "__main__":
with open("dangdang.html",encoding='gbk') as file:
response = Selector(text=file.read())
book_list = response.xpath("//ul[@class='bigimg']/li")
result_list = []
for book in book_list:
item = {}
item['name'] = book.xpath("a[@class='pic']/@title").extract_first()
item['now_price'] = book.xpath(".//span[@class='search_now_price']/text()").extract_first()
item['pre_price'] = book.xpath(".//span[@class='search_pre_price']/text()").extract_first()
item['author'] = book.xpath("p[@class='search_book_author']//a/@title").extract_first()
item['publisher'] = book.xpath("p[@class='search_book_author']//a/@title").extract()[-1]
item['detailUrl'] = book.xpath(".//p[@class='name']/a/@href").extract_first()
item['imageUrl'] = book.xpath("a[@class='pic']/img/@src").extract_first()
if item['imageUrl'] == "images/model/guan/url_none.png":
item['imageUrl'] = book.xpath("a[@class='pic']/img/@data-original").extract_first()
result_list.append(item)
df = pd.DataFrame(result_list,columns=result_list[0].keys())
df.to_excel("当当图书信息.xlsx")
二、 需求：抓取天猫三只松鼠旗舰店超级满减商品信息（55分）
网站地址如下https://sanzhisongshu.tmall.com/p/rd523844.htm?spm=a1z10.1-b-s.w5001-14855767631.8.19ad32fdW6UhfO&scene=taobao_shop
评分标准如下：
1、创建函数获取页面所有内容，代码无误（5分）
2、得到页面内容后解析信息，获取页面中图片链接，并将图片下载至本地photo文件夹。（10分）
3、获取页面中每个商品信息的商品名称、价格以及商品图片url信息（20分）
4、创建数据库product，及表格productinfo，包含（商品名称、价格及图片地址三个字段）（5分）
5、将第（3）步获取的结果写入数据库（10分）
6、代码规范，有注释（5分）
import requests
from bs4 import BeautifulSoup as bs
import urllib
import os
import pymysql
#获取实例化BeautifulSoup对象
def getSoup(url, encoding="gbk", **params):
reponse = requests.get(url, **params)
reponse.encoding = encoding
soup = bs(reponse.text, 'lxml')
return soup
#下载单个图片函数
def downloadImage(imgUrl, imgName):
imgDir = "photo"
if not os.path.isdir(imgDir):
os.mkdir(imgDir)
imgPath = "%s/%s" %(imgDir,imgName)
urllib.request.urlretrieve(imgUrl,imgPath)
#下载所有图片函数
def downloadAllImages(soup):
image_list = soup.select("img")
count = 0
for image in image_list:
try:
srcStr = image['data-ks-lazyload']
imgFormat = srcStr[-3:]
if imgFormat == 'gif':
continue
count += 1
imgName = "%d.%s" % (count, imgFormat)
imgUrl = "http:" + srcStr
downloadImage(imgUrl, imgName)
except Exception as e:
print(str(e))
#通过css选择器语法选择出标签
def cssFind(movie,cssSelector,nth=1):
if len(movie.select(cssSelector)) >= nth:
return movie.select(cssSelector)[nth-1].text.strip()
else:
return ''
#获取数据库连接函数
def getConn(database ="product"):
args = dict(
host = 'localhost',
user = 'root',
passwd = '.... your password',
charset = 'utf8',
db = database
)
return pymysql.connect(**args)
if __name__ == "__main__":
soup = getSoup("https://sanzhisongshu.tmall.com/p/rd523844.htm" \
"?spm=a1z10.1-b-s.w5001-14855767631.8.19ad32fdW6UhfO&scene=taobao_shop")
#下载所有图片
downloadAllImages(soup)
#获取数据库连接
conn = getConn()
cursor = conn.cursor()
#新建数据库中的表productinfo
sql_list = []
sql_list.append("drop table if exists productinfo")
sql_list.append("create table productinfo(name varchar(200)," \
"price varchar(20),imageUrl varchar(500))")
for sql in sql_list:
cursor.execute(sql)
conn.commit()
#获取商品信息并插入数据库
item_list = soup.select("div.item4line1 dl.item")
for item in item_list:
name = cssFind(item,"dd.detail a")
price = cssFind(item,"dd.detail span.c-price")
imageUrl = item.select("dt img")[0]['data-ks-lazyload']
insert_sql = 'insert into productinfo values("%s","%s","%s")' %(name,price,imageUrl)
cursor.execute(insert_sql)
conn.commit()
三、请以你的理解尽可能准确的描述出scrapy运行的原理图（15分）
在实际编写代码的过程一种，一般按照下列顺序编写代码文件：
1.编写item.py文件；2.编写爬虫文件;3.编写pipelines.py文件；4.编写settings.py文件
在Scrapy框架理解上：
1.爬虫Spiders发送请求Requests给调度器Scheduler
2.调度器Scheduler发送下载网页的请求Requests给下载器Downloader
3.下载器Downloader获取网页相应response交给爬虫Spiders
4.爬虫Spiders对response进行解析形成Item
5.Item传送给管道，管道对数据进行相应处理，数据持久化。
6.Middelwares分为三种：调度中间件Scheduler middlewares、爬虫中间件spider Middlewares、下载中间件Download Middlewares。在编写scrapy-redis分布式爬虫时，redis就相当于调度中间件Scheduler middlewares；对爬虫进行伪装，设置用户代理User-agent和代理Ip,是在爬虫中间件spider Middlewares中进行设置，下载中间件Download Middlewares可以对下载进行相应设置。
