换坑季-51Job前程无忧 Python爬虫

写了个简易的Python爬虫，实现对目的工作的分析。
说明，只用了正则re库进行数据处理，requests进行请求,开了4个简易的函数线程。
url是以下界面的url：

主要实现了以下CSV功能：

全部代码：

import requests
import re
import csv
from threading import Thread


def req(i):
    count = 1
    try:
        for url in i:
            headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.110 Safari/537.36'}
            response = requests.get(url=url, headers=headers, timeout=5)
            response.encoding = 'GBK'
            content = re.findall(r'.*?.*?.*?(.*?).*?(.*?).*?(.*?)', response.text, re.S)
            # print(content)
            for index in content:
                txt = []
                title = index[0]
                thisUrl = index[1]
                try:
                    thisContent = requests.get(url=thisUrl, headers=headers, timeout=5)
                    text = re.findall(r'
(.*?)
', thisContent.text, re.S)
                    final = ''.join(text).replace('\r\n\t\t\t\t\t\t', '').replace('
', '').replace('
', '').replace('', '').replace('', '').replace('
', '').replace(' ', '').replace('
', '').replace('
', '').replace('\t\t\t\t\t\t\t\t\t\t\t\t', '').replace('', '').replace('', '').replace('', '').replace('', '').replace('', '').replace('
', '')
                    company = index[2]
                    area = index[3]
                    salary = index[4]
                    date = index[5]
                    txt.append(title)
                    txt.append(thisUrl)
                    txt.append(final)
                    txt.append(company)
                    txt.append(area)
                    txt.append(salary)
                    txt.append(date)
                    # print(txt)
                    with open(r'./前程无忧.csv', 'a', newline='', encoding='utf-8-sig') as csvf:
                        spanwriter = csv.writer(csvf)
                        spanwriter.writerow(txt)
                    count = count + 1
                except:
                    print("此次请求详情失败！！！" + thisUrl)
    except:
        print('请求首页失败！' + i)
    print("共%d多少条信息~" % count)


if __name__ == '__main__':
    txt1 = []
    txt2 = []
    txt3 = []
    txt4 = []
    url = 'https://search.51job.com/list/090200,000000,0000,00,9,99,%25E8%25BF%2590%25E7%25BB%25B4%25E5%25B7%25A5%25E7%25A8%258B%25E5%25B8%2588,2,{}.html?lang=c&stype=1&postchannel=0000&workyear=99&cotype=99°reefrom=99&jobterm=99&companysize=99&lonlat=0%2C0&radius=-1&ord_field=0&confirmdate=9&fromType=&dibiaoid=0&address=&line=&specialarea=00&from=&welfare='
    for i in range(1, 6):
        i = url.format(i)
        txt1.append(i)
    for j in range(6, 12):
        j = url.format(j)
        txt2.append(j)
    for k in range(12, 18):
        k = url.format(k)
        txt3.append(k)
    for k in range(18, 24):
        k = url.format(k)
        txt3.append(k)
    t1 = Thread(target=req, args=(txt1,))
    t1.start()
    print('t1线程开始！')
    t2 = Thread(target=req, args=(txt2,))
    t2.start()
    print('t2线程开始！')
    t3 = Thread(target=req, args=(txt3,))
    t3.start()
    print('t3线程开始！')
    t4 = Thread(target=req, args=(txt4,))
    t4.start()
    print('t4线程开始！')

上面这个开了4个线程的代码其实对爬虫还是不太友好。
以下代码可以在详细页进行爬虫，建议使用生产者消费者模式。

import re
import requests


url = 'https://jobs.51job.com/chengdu-jjq/114069603.html?s=01&t=0'
headers = {'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.110 Safari/537.36'}
response = requests.get(url=url, headers=headers, timeout=5)
response.encoding = 'GBK'
# 工作职位
job = re.findall(r'
', response.text)
print(job)
# 薪资
salary = re.findall(r'
.*?.*?(.*?)', response.text, re.S)
print(salary)
# 公司名称
company = re.findall(r'target="_blank" title="(.*?)" class="catn">', response.text)
print(company)
# 公司性质
flag = re.findall(r'
.*?
', response.text)
print(flag)
# 公司规模
people = re.findall(r'
.*?
', response.text)
print(people)
# 职位详细的内容：
content = re.findall(r'
.*?
', response.text, re.S)
# 将正则匹配的内容进行字符串处理
content_str = ''.join(content)
# 城市
txt_city = re.findall(r'.*?(成都.*?) .*?', content_str)
print(txt_city)
# 招多少人
txt_count = re.findall(r'.*?(招\d人).*?', content_str)
print(txt_count)
# 经验
txt_experience = re.findall(r'.*?(无工作经验).*?', content_str)
if len(txt_experience) == 0:
    txt_experience = re.findall(r'.*?(\d+年经验).*?', content_str)
print(txt_experience)
# 发布日期
txt_date = re.findall(r'.*?(\d+-\d+发布).*?', content_str)
print(txt_date)
# 学历要求， 只匹配了大专和本科
txt_education = re.findall(r'.*?(本科).*?', content_str)
if len(txt_education) == 0:
    txt_education = re.findall(r'.*?(大专).*?', content_str)
else:
    txt_education = '无学历要求'
print(txt_education)
# 职位招聘要求内容描述：
descrition = re.findall(r'
(.*?)
', response.text, re.S)
descrition = ''.join(descrition).replace('\r\n\t\t\t\t\t\t', '').replace('
', '').replace('
', '').replace('', '').replace('', '').replace('
', '').replace(' ', '').replace('
', '').replace('
', '').replace('\t\t\t\t\t\t\t\t\t\t\t\t', '').replace('', '').replace('', '').replace('', '').replace('', '').replace('', '').replace('
', '')
print(descrition)