Python学习（爬虫学习）

1、爬取电影
import requests
from bs4 import BeautifulSoup
import re
import pandas

headers = {
‘Host’: ‘movie.douban.com’,
‘Origin’: ‘movie.douban.com’,
‘User-Agent’: ‘Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Mobile Safari/537.36’,
}
base_url = ‘https://movie.douban.com/top250?start={}&filter=’

response = requests.get(‘https://movie.douban.com/top250?start=0&filter=’, headers=headers)
if response.status_code == 200:
# print(response.text)
pass

pattern1 = re.compile(’<div.?class=“item”>.?<div.?class=“pic”>.?<a.?href="(.?)">’,
re.S) # 去掉所有换行符，并用正则表达式去匹配每一个页面的具体电影
urls = re.findall(pattern1, response.text)

directors = [] # 导演

names = [] # 电影名

stars = [] # 主演

countrys = [] # 电影的出产地

languages = [] # 电影语言

headers_urls = {
‘Host’: ‘movie.douban.com’,
‘User-Agent’: ‘Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.36’
}

肖申克的救赎 The Shawshank Redemption

弗兰克·德拉邦特

蒂姆·罗宾斯

def base_urls(base_url):
urls = []
# 这里我们只能前两页做测试，所以range只设置到了50
# for i in range(0, 275, 25):
# true_url = base_url.format(i)
# print(true_url)
for i in range(0, 50, 25):
true_url = base_url.format(i)
print(true_url)

    response = requests.get(true_url, headers=headers)
    if response.status_code == 200:
        # print(response.text)

        pattern1 = re.compile('<div.*?class="item">.*?<div.*?class="pic">.*?<a.*?href="(.*?)">', re.S)
        # 去掉所有换行符，并用正则表达式去匹配每一个页面的具体电影
        url = re.findall(pattern1, response.text)
        # 因为这里是用findall，他返回的是一个列表，如果我们直接append，会导致列表嵌套，故我们这里用个for循环提取出列表的元素再append进去

        for i in url:
            urls.append(i)

return urls

def parse_url(urls):
# 因为只拿前两页做测试，所以range设置到50
for i in range(0, 50, 1):
res = requests.get(urls[i], headers=headers_urls)
print(res)
if res.status_code == 200:
soup = BeautifulSoup(res.text, ‘lxml’)
# 爬取电影名
name = (soup.find(‘span’, property=“v:itemreviewed”))
names.append(name.string)
# print(names)

        # 爬取导演
        director = soup.find('a', rel="v:directedBy")
        directors.append(director.string)
        # print(director.text)

        # 爬取明星
        star_save = []
        for star in soup.find_all('a', rel="v:starring"):
            star_save.append(star.text)
            stars.append(star_save)
        # print(stars)

        # 爬取制片国家
        # <span class="pl">制片国家/地区:</span> 美国<br>
        # 学到的知识点：通过匹配文本内容找下个兄弟节点
        country = soup.find('span', text='制片国家/地区:').next_sibling[1:]
        countrys.append(country)
        # print(countrys)

        # 爬取影片语言
        # <span class="pl">语言:</span>
        language = soup.find('span', text='语言:').next_sibling[1:]
        languages.append(language)
        # print(language)

print(directors)

print(true_director)

print(a)

if name == ‘main’:
base = base_urls(base_url)
print(base)
print(len(base))
parse_url(base)
print(countrys)
print(directors)
print(languages)
print(names)
#
# 最后我们将数据写入到一个excel表格里
info = {‘Filmname’: names, ‘Directors’: directors, ‘Country’: countrys, ‘Languages’: languages}
pdfile = pandas.DataFrame(info)

pdfile.to_excel('DoubanFilm.xlsx', sheet_name="豆瓣电影")

2、爬取房价
import requests
import bs4

def open_url(url):
headers={“user-agent”:“Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36”}
res=requests.get(url,headers=headers)

return res

def find_data(res):
soup=bs4.BeautifulSoup(res.text,“html.parser”)
content=soup.find(id=“Cnt-Main-Article-QQ”)
#print(content)
target=content.find_all(“p”,style=“TEXT-INDENT: 2em”)

for each in target:
    print(each.text)

def main():
url=“https://news.house.qq.com/a/20170702/003985.htm”
res=open_url(url)
find_data(res)
# with open(“test.txt”,“w”,encoding=“utf-8”) as file:
# file.write(res.text)

if name==“main”:
main()
结果图：

3、 生成表格（表格出了，没数据）
import requests
import bs4
import openpyxl

def open_url(url):
headers={“user-agent”:“Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/79.0.3945.130 Safari/537.36”}
res=requests.get(url,headers=headers)

return res

def find_data(res):
data=[]
soup=bs4.BeautifulSoup(res.text,“html.parser”)
content=soup.find(id=“Cnt-Main-Article-QQ”)
#print(content)
target=content.find_all(“p”,style=“TEXT-INDENT: 2em”)
target=iter(target)

for each in target:
    #print(each.text)
    if each.text.isnumeric():
        data.append([
            re.search(r'\[(.+)\]',next(target).text).group(1),
            re.search(r'\d.*',next(target).text).group(),
            re.search(r'\d.*',next(target).text).group(),
            re.search(r'\d.*',next(target).text).group()])

    return data

def to_excel(data):
wb=openpyxl.Workbook()
wb.guess_types=True
ws=wb.active
ws.append([‘城市’,‘平均房价’,‘平均工资’,‘房价工资比’])
for each in data:
ws.append(each)

wb.save("2017年中国主要城市房价工资比排行榜.xlsx")

def main():
url=“https://news.house.qq.com/a/20170702/003985.htm”
res=open_url(url)
data=find_data(res)
to_excel(data)
# with open(“test.txt”,“w”,encoding=“utf-8”) as file:
# file.write(res.text)

if name==“main”:
main()