思路：
1、将需要查询城市列表，通过城市接口转换成相应的code码
2、遍历城市、职位生成url
3、通过url获取列表页面信息，遍历列表页面信息
4、再根据列表页面信息的job_link获取详情页面信息，将需要的信息以字典data的形式存在列表datas里
5、判断列表页面是否有下一页，重复步骤3、4；同时将列表datas一直传递下去
6、一个城市、职位url爬取完后，将列表datas接在列表datas_list后面，重复3、4、5
7、最后将列表datas_list的数据，遍历写在Excel里面
知识点：
1、将response内容以json形式输出，解析json并取值
2、soup 的select()和find_all()和find()方法使用
3、异常Exception的使用
4、wldt创建编辑Excel的使用
import requests, time, xlwt
from bs4 import BeautifulSoup class MyJob():
def __init__(self, mycity, myquery):
self.city = mycity
self.query = myquery
self.list_url = "https://www.zhipin.com/job_detail/?query=%s&city=%s&industry=&position="%(self.query, self.city)
self.datas = []
self.header = {
'authority': 'www.zhipin.com',
'method': 'GET',
'scheme': 'https',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8',
'accept-encoding': 'gzip, deflate, br',
'accept-language': 'zh-CN,zh;q=0.9',
'cache-control': 'max-age=0',
'cookie': 'lastCity=101210100;uab_collina=154408714637849548916323;toUrl=/;c=1558272251;g=-;l=l=%2Fwww.zhipin.com%2Fuser%2Flogin.html&r=; Hm_lvt_194df3105ad7148dcf2b98a91b5e727a=1555852331,1556985726,1558169427,1558272251; __a=40505844.1544087205.1558169426.1558272251.41.14.4.31; Hm_lpvt_194df3105ad7148dcf2b98a91b5e727a=1558272385',
'referer': 'https://www.zhipin.com/?ka=header-logo',
'upgrade-insecure-requests': '',
'user-agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.110 Safari/537.36'
} #将城市转化为code码
def get_city(self,city_list):
city_url = "https://www.zhipin.com/wapi/zpCommon/data/city.json" #获取城市
json = requests.get(city_url).json()
zpData = json["zpData"]["cityList"]
list = []
for city in city_list :
for data_sf in zpData:
for data_dq in data_sf["subLevelModelList"]:
if city == data_dq["name"]:
list.append(data_dq["code"])
return list #获取所有页内容
def get_job_list(self, url, datas):
print(url)
html = requests.get(url, headers=self.header).text
soup = BeautifulSoup(html, 'html.parser')
jobs = soup.select(".job-primary")
for job in jobs:
data = {}
# 招聘id
data["job_id"] = job.find_all("div", attrs={"class": "info-primary"})[0].find("a").get("data-jobid")
# 招聘链接
data["job_link"] = "https://www.zhipin.com" + job.find_all("div", attrs={"class": "info-primary"})[0].find("a").get("href")
# 招聘岗位
data["job_name"] = job.find_all("div", attrs={"class": "info-primary"})[0].find("div", attrs={"class": "job-title"}).get_text()
# 薪资
data["job_red"] = job.find_all("div", attrs={"class": "info-primary"})[0].find("span", attrs={"class": "red"}).get_text()
# 地址 #工作年限 #学历
data["job_address"] = job.find_all("div", attrs={"class": "info-primary"})[0].find("p").get_text().split(" ")
# 企业链接
data["job_company_link"] = job.find_all("div", attrs={"class": "info-company"})[0].find("a").get("href")
# 企业信息
data["job_company"] = job.find_all("div", attrs={"class": "info-company"})[0].find("p").get_text().split(" ")
# boss链接
data["job_publis_link"] = job.find_all("div", attrs={"class": "info-publis"})[0].find("img").get("src")
# boos信息
data["job_publis"] = job.find_all("div", attrs={"class": "info-publis"})[0].find("h3").get_text().split(" ")
time.sleep(5)
self.get_job_detail(data) # 获取job详情页内容
print(data)
datas.append(data) # 将某条job添加到datas中，直到将当前页添加完 try:
next_url = soup.find("div", attrs={"class": "page"}).find("a", attrs={"class": "next"}).get("href")
#if next_url[-1] =="3": # 第二页自动抛异常
if next_url in "javascript:;": # 最后一页自动抛异常
raise Exception()
except Exception as e:
print("最后一页了；%s" % e)
return datas # 返回所有页内容
else:
time.sleep(5)
next_url = "https://www.zhipin.com" + next_url
self.get_job_list(next_url, datas)
return datas # 返回所有页内容 #获取详情页内容
def get_job_detail(self, data):
print(data["job_link"])
html = requests.get(data["job_link"], headers=self.header).text
soup = BeautifulSoup(html, 'html.parser')
# 招聘公司
data["detail_content_name"] = soup.find_all("div", attrs={"class": "detail-content"})[0].find("div", attrs={"class": "name"}).get_text()
# 福利
data["detail_primary_tags"] = soup.find_all("div", attrs={"class": "info-primary"})[0].find("div", attrs={"class": "job-tags"}).get_text().strip()
# 招聘岗位
data["detail_primary_name"] = soup.find_all("div", attrs={"class": "info-primary"})[0].find("h1").get_text()
# 招聘状态
data["detail_primary_status"] = soup.find_all("div", attrs={"class": "info-primary"})[0].find("div", attrs={"class": "job-status"}).get_text()
# 薪资
data["detail_primary_salary"] = soup.find_all("div", attrs={"class": "info-primary"})[0].find("span", attrs={"class": "salary"}).get_text()
# 地址 #工作年限 #学历
data["detail_primary_address"] = soup.find_all("div", attrs={"class": "info-primary"})[0].find("p").get_text()
# 工作地址
data["detail_content_address"] = soup.find_all("div", attrs={"class": "detail-content"})[0].find("div", attrs={"class": "location-address"}).get_text()
# 职位描述
data["detail_content_text"] = soup.find_all("div", attrs={"class": "detail-content"})[0].find("div", attrs={"class": "text"}).get_text().strip().replace("；", "\n")
# boss名字
data["detail_op_name"] = soup.find_all("div", attrs={"class": "detail-op"})[1].find("h2", attrs={"class": "name"}).get_text()
# boss职位
data["detail_op_job"] = soup.find_all("div", attrs={"class": "detail-op"})[1].find("p", attrs={"class": "gray"}).get_text().split("·")[0]
# boss状态
data["detail_op_status"] = soup.find_all("div", attrs={"class": "detail-op"})[1].find("p", attrs={"class": "gray"}).get_text().split("·")[1] #将获取的数据写入Excel
def setExcel(self, datas_list):
book = xlwt.Workbook(encoding='utf-8')
table = book.add_sheet("boss软件测试")
table.write(0, 0, "编号")
table.write(0, 1, "招聘链接")
table.write(0, 2, "招聘岗位")
table.write(0, 3, "薪资")
table.write(0, 4, "地址")
table.write(0, 5, "企业链接")
table.write(0, 6, "企业信息")
table.write(0, 7, "boss链接")
table.write(0, 8, "boss信息")
table.write(0, 9, "detail详情")
i = 1
for data in datas_list:
table.write(i, 0, data["job_id"])
table.write(i, 1, data["job_link"])
table.write(i, 2, data["job_name"])
table.write(i, 3, data["job_red"])
table.write(i, 4, data["job_address"])
table.write(i, 5, data["job_company_link"])
table.write(i, 6, data["job_company"])
table.write(i, 7, data["job_publis_link"])
table.write(i, 8, data["job_publis"]) table.write(i, 10, data["detail_content_name"])
table.write(i, 11, data["detail_primary_name"])
table.write(i, 12, data["detail_primary_status"])
table.write(i, 13, data["detail_primary_salary"])
table.write(i, 14, data["detail_primary_address"])
table.write(i, 15, data["detail_content_text"])
table.write(i, 16, data["detail_op_name"])
table.write(i, 17, data["detail_op_job"])
table.write(i, 18, data["detail_op_status"])
table.write(i, 19, data["detail_primary_tags"])
table.write(i, 20, data["detail_content_address"])
i += 1
book.save(r'C:\%s_boss软件测试.xls' % time.strftime('%Y%m%d%H%M%S'))
print("Excel保存成功") if __name__ == '__main__':
city_list = MyJob("","").get_city(["杭州"])
query_list = ["软件测试", "测试工程师"]
datas_list = []
for city in city_list:
for query in query_list:
myjob = MyJob(city, query)
datas = myjob.get_job_list(myjob.list_url, myjob.datas)
datas_list.extend(datas)
myjob.setExcel(datas_list)