打造IP代理池,Python爬取Boss直聘,帮你获取全国各类职业薪酬榜

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爬虫面临的问题

  • 不再是单纯的数据一把抓

多数的网站还是请求来了,一把将所有数据塞进去返回,但现在更多的网站使用数据的异步加载,爬虫不再像之前那么方便

很多人说js异步加载与数据解析,爬虫可以做到啊,恩是的,无非增加些工作量,那是你没遇到牛逼的前端,多数的解决办法只能靠渲染浏览器抓取,效率低下,接着往下走


  • 千姿百态的登陆验证

从12306的说说下面哪个糖是奶糖,到现在各大网站的滑动拼图、汉子点击解锁,这些操作都是在为了阻止爬虫的自动化运行。

你说可以先登录了复制cookie,但cookie也有失效期吧?

何为反爬虫?犀利的解释网上到处搜,简单的逻辑我讲给你听。你几秒钟访问了我的网站一千次,不好意思,我把你的ip禁掉,一段时间你别来了。

很多人又说了,你也太菜了吧,不知道有爬虫ip代理池的开源项目IPProxys吗?那我就呵呵了,几个人真的现在用过免费的ip代理池,你去看看现在的免费代理池,有几个是可用的!

再说了,你通过IPProxys代理池,获取到可用的代理访问人家网站,人家网站不会用同样的办法查到可用的代理先一步封掉吗?然后你只能花钱去买付费的代理

  • 数据源头封锁

平时大家看的什么爬爬豆瓣电影网站啊,收集下某宝评论啊….这些都是公开数据。但现在更多的数据逐步走向闭源化。数据的价值越来越大,没有数据获取的源头,爬虫面临什么问题?

上面说了一堆的爬虫这不好那不好,结果我今天发的文章确是爬虫的,自己打自己的脸? 其实我只是想说说网站数据展示与分析的技巧…恰巧Boss直聘就做的很不错。怎么不错?一点点分析…

  • 数据共享

先来看一张图

我选择黑龙江省的大兴安岭,去看看那里有招聘python的没,多数系统查询不到数据就会给你提示未获取到相关数据,但Boss直聘会悄悄地吧黑龙江省的python招聘信息给你显示处理,够鸡~贼。

  • 数据限制

大兴安岭没有搞python的,那我们去全国看看吧:

这里差一点就把我坑了,我开始天真的以为,全国只有300条(一页30条,共10也)python招聘信息。 然后我回过头去看西安的,也只有10页,然后想着修改下他的get请求parameters,没卵用。

这有啥用?仔细想…一方面可以做到放置咱们爬虫一下获取所有的数据,但这只是你自作多情,这东西是商机!

每天那么多的商家发布招聘信息,进入不了top100,别人想看都看不到你的消息,除非搜索名字。那么如何排名靠前?答案就是最后俩字,靠钱。你是Boss直聘的会员,你发布的就会靠前….

  • 偷换概念

依旧先看图:

我搜索的是ruby,你资料不够,其他来凑….

  • ip解析

老套路,再来看一张图:

Boss直聘的服务器里,留着我的痕迹,多么骄傲的事情啊。你们想不想和我一样?只需要3秒钟…. 三秒钟内你的访问量能超过1000,妥妥被封!

那么我们该怎么办

  • 设置不同的User-Agent

使用pip install fake-useragent安装后获取多种User-Agent,但其实本地保存上几十个,完全够了….

  • 不要太夯(大力)

适当的减慢你的速度,别人不会觉得是你菜….别觉得一秒爬几千比一秒爬几百的人牛逼(快枪手子弹打完的早….不算开车吧?)。

  • 购买付费的代理

为什么我跳过了说免费的代理?因为现在搞爬虫的人太多了,免费的基本早就列入各大网站的黑名单了。

所以解析到的原始数据如下:

先来看看python的薪酬榜:

看一下西安的排位,薪资平均真的好低…..

代码

  1 import requests
  2 from bs4 import BeautifulSoup
  3 import csv
  4 import random
  5 import time
  6 import argparse
  7 from pyecharts.charts import Line
  8 import pandas as pd
  9 ​
 10 ​
 11 class BossCrawler:
 12     def __init__(self, query):
 13 ​
 14         self.query = query
 15         self.filename = 'boss_info_%s.csv' % self.query
 16         self.city_code_list = self.get_city()
 17         self.boss_info_list = []
 18         self.csv_header = ["city", "profession", "salary", "company"]
 19 ​
 20     @staticmethod
 21     def getheaders():
 22         user_list = [
 23             "Opera/9.80 (X11; Linux i686; Ubuntu/14.10) Presto/2.12.388 Version/12.16",
 24             "Opera/9.80 (Windows NT 6.0) Presto/2.12.388 Version/12.14",
 25             "Mozilla/5.0 (Windows NT 6.0; rv:2.0) Gecko/20100101 Firefox/4.0 Opera 12.14",
 26             "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.0) Opera 12.14",
 27             "Opera/12.80 (Windows NT 5.1; U; en) Presto/2.10.289 Version/12.02",
 28             "Opera/9.80 (Windows NT 6.1; U; es-ES) Presto/2.9.181 Version/12.00",
 29             "Opera/9.80 (Windows NT 5.1; U; zh-sg) Presto/2.9.181 Version/12.00",
 30             "Opera/12.0(Windows NT 5.2;U;en)Presto/22.9.168 Version/12.00",
 31             "Opera/12.0(Windows NT 5.1;U;en)Presto/22.9.168 Version/12.00",
 32             "Mozilla/5.0 (Windows NT 5.1) Gecko/20100101 Firefox/14.0 Opera/12.0",
 33             "Opera/9.80 (Windows NT 6.1; WOW64; U; pt) Presto/2.10.229 Version/11.62",
 34             "Opera/9.80 (Windows NT 6.0; U; pl) Presto/2.10.229 Version/11.62",
 35             "Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; fr) Presto/2.9.168 Version/11.52",
 36             "Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; de) Presto/2.9.168 Version/11.52",
 37             "Opera/9.80 (Windows NT 5.1; U; en) Presto/2.9.168 Version/11.51",
 38             "Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; de) Opera 11.51",
 39             "Opera/9.80 (X11; Linux x86_64; U; fr) Presto/2.9.168 Version/11.50",
 40             "Opera/9.80 (X11; Linux i686; U; hu) Presto/2.9.168 Version/11.50",
 41             "Opera/9.80 (X11; Linux i686; U; ru) Presto/2.8.131 Version/11.11",
 42             "Opera/9.80 (X11; Linux i686; U; es-ES) Presto/2.8.131 Version/11.11",
 43             "Mozilla/5.0 (Windows NT 5.1; U; en; rv:1.8.1) Gecko/20061208 Firefox/5.0 Opera 11.11",
 44             "Opera/9.80 (X11; Linux x86_64; U; bg) Presto/2.8.131 Version/11.10",
 45             "Opera/9.80 (Windows NT 6.0; U; en) Presto/2.8.99 Version/11.10",
 46             "Opera/9.80 (Windows NT 5.1; U; zh-tw) Presto/2.8.131 Version/11.10",
 47             "Opera/9.80 (Windows NT 6.1; Opera Tablet/15165; U; en) Presto/2.8.149 Version/11.1",
 48             "Opera/9.80 (X11; Linux x86_64; U; Ubuntu/10.10 (maverick); pl) Presto/2.7.62 Version/11.01",
 49             "Opera/9.80 (X11; Linux i686; U; ja) Presto/2.7.62 Version/11.01",
 50             "Opera/9.80 (X11; Linux i686; U; fr) Presto/2.7.62 Version/11.01",
 51             "Opera/9.80 (Windows NT 6.1; U; zh-tw) Presto/2.7.62 Version/11.01",
 52             "Opera/9.80 (Windows NT 6.1; U; zh-cn) Presto/2.7.62 Version/11.01",
 53             "Opera/9.80 (Windows NT 6.1; U; sv) Presto/2.7.62 Version/11.01",
 54             "Opera/9.80 (Windows NT 6.1; U; en-US) Presto/2.7.62 Version/11.01",
 55             "Opera/9.80 (Windows NT 6.1; U; cs) Presto/2.7.62 Version/11.01",
 56             "Opera/9.80 (Windows NT 6.0; U; pl) Presto/2.7.62 Version/11.01",
 57             "Opera/9.80 (Windows NT 5.2; U; ru) Presto/2.7.62 Version/11.01",
 58             "Opera/9.80 (Windows NT 5.1; U;) Presto/2.7.62 Version/11.01",
 59             "Opera/9.80 (Windows NT 5.1; U; cs) Presto/2.7.62 Version/11.01",
 60             "Mozilla/5.0 (Windows NT 6.1; U; nl; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6 Opera 11.01",
 61             "Mozilla/5.0 (Windows NT 6.1; U; de; rv:1.9.1.6) Gecko/20091201 Firefox/3.5.6 Opera 11.01",
 62             "Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.1; de) Opera 11.01",
 63             "Opera/9.80 (X11; Linux x86_64; U; pl) Presto/2.7.62 Version/11.00",
 64             "Opera/9.80 (X11; Linux i686; U; it) Presto/2.7.62 Version/11.00",
 65             "Opera/9.80 (Windows NT 6.1; U; zh-cn) Presto/2.6.37 Version/11.00",
 66             "Opera/9.80 (Windows NT 6.1; U; pl) Presto/2.7.62 Version/11.00",
 67             "Opera/9.80 (Windows NT 6.1; U; ko) Presto/2.7.62 Version/11.00",
 68             "Opera/9.80 (Windows NT 6.1; U; fi) Presto/2.7.62 Version/11.00",
 69             "Opera/9.80 (Windows NT 6.1; U; en-GB) Presto/2.7.62 Version/11.00",
 70             "Opera/9.80 (Windows NT 6.1 x64; U; en) Presto/2.7.62 Version/11.00",
 71             "Opera/9.80 (Windows NT 6.0; U; en) Presto/2.7.39 Version/11.00"
 72         ]
 73         user_agent = random.choice(user_list)
 74         headers = {'User-Agent': user_agent}
 75         return headers
 76 ​
 77     def get_city(self):
 78         headers = self.getheaders()
 79         r = requests.get("http://www.zhipin.com/wapi/zpCommon/data/city.json", headers=headers)
 80         data = r.json()
 81         return [city['code'] for city in data['zpData']['hotCityList'][1:]]
 82 ​
 83     def get_response(self, url, params=None):
 84         headers = self.getheaders()
 85         r = requests.get(url, headers=headers, params=params)
 86         r.encoding = 'utf-8'
 87         soup = BeautifulSoup(r.text, "lxml")
 88         return soup
 89 ​
 90     def get_url(self):
 91         for city_code in self.city_code_list:
 92             url = "https://www.zhipin.com/c%s/" % city_code
 93             self.per_page_info(url)
 94             time.sleep(10)
 95 ​
 96     def per_page_info(self, url):
 97         for page_num in range(1, 11):
 98             params = {"query": self.query, "page": page_num}
 99             soup = self.get_response(url, params)
100             lines = soup.find('div', class_='job-list').select('ul > li')
101             if not lines:
102                 # 代表没有数据了,换下一个城市
103                 return
104             for line in lines:
105                 info_primary = line.find('div', class_="info-primary")
106                 city = info_primary.find('p').text.split(' ')[0]
107                 job = info_primary.find('div', class_="job-title").text
108                 # 过滤答非所谓的招聘信息
109                 if self.query.lower() not in job.lower():
110                     continue
111                 salary = info_primary.find('span', class_="red").text.split('-')[0].replace('K', '')
112                 company = line.find('div', class_="info-company").find('a').text.lower()
113                 result = dict(zip(self.csv_header, [city, job, salary, company]))
114                 print(result)
115                 self.boss_info_list.append(result)
116 ​
117     def write_result(self):
118         with open(self.filename, "w+", encoding='utf-8', newline='') as f:
119             f_csv = csv.DictWriter(f, self.csv_header)
120             f_csv.writeheader()
121             f_csv.writerows(self.boss_info_list)
122 ​
123     def read_csv(self):
124         data = pd.read_csv(self.filename, sep=",", header=0)
125         data.groupby('city').mean()['salary'].to_frame('salary').reset_index().sort_values('salary', ascending=False)
126         result = data.groupby('city').apply(lambda x: x.mean()).round(1)['salary'].to_frame(
127             'salary').reset_index().sort_values('salary', ascending=False)
128         print(result)
129         charts_bar = (
130             Line()
131                 .set_global_opts(
132                 title_opts={"text": "全国%s薪酬榜" % self.query})
133                 .add_xaxis(result.city.values.tolist())
134                 .add_yaxis("salary", result.salary.values.tolist())
135         )
136         charts_bar.render('%s.html' % self.query)
137 ​
138 ​
139 if __name__ == '__main__':
140     parser = argparse.ArgumentParser()
141     parser.add_argument("-k", "--keyword", help="请填写所需查询的关键字")
142     args = parser.parse_args()
143     if not args.keyword:
144         print(parser.print_help())
145     else:
146         main = BossCrawler(args.keyword)
147         main.get_url()
148         main.write_result()
149         main.read_csv()

https://www.cnblogs.com/7758520lzy/p/11978672.html

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