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51job多线程爬取指定职业信息数据

# datetime:2020/10/7 14:02
# 51job多线程
import requests
import chardet
from bs4 import BeautifulSoup
import csv
from openpyxl import Workbook
import random
import time
import threading

def getOnePageInfo(url):
    # 访问链接
    res = requests.get(url,
                       headers={
                           ‘User-Agent‘: ‘Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50‘}
                       )
    # 转为beautifulsoup对象
    soup = BeautifulSoup(res.text, ‘html.parser‘)

    # 那么我们只能按照实际得到的对象来找信息
    allstring = soup.find_all(‘script‘)[-4].string
    # allstring=soup.find_all(‘script‘)[-4].text

    # 1：使用 = 分割1次， 的第二个值就是所有数据
    data = allstring.split(‘=‘, 1)[-1]

    # 2 :
    index = allstring.find(‘{‘)
    data2 = allstring[index:]

    # 1使用eval()将字符串转换为相关数据
    dict_data = eval(data)

    bigdata = []
    for each in dict_data[‘engine_search_result‘]:
        oneInfo = []
        # 职位名 job_name
        oneInfo.append(each.get(‘job_name‘))
        # 公司名 commpany_name
        oneInfo.append(each.get(‘company_name‘))
        # 薪资 providesalary_text
        oneInfo.append(each.get(‘providesalary_text‘))
        # 工作地点 workarea_text
        oneInfo.append(each.get(‘workarea_text‘))
        # 发布日期 updatedate
        oneInfo.append(each.get(‘updatedate‘))
        # 公司类型 companytype_text
        oneInfo.append(each.get(‘companytype_text‘))
        # 额外信息 attribute_text
        oneInfo.append(str(each.get(‘attribute_text‘)))
        # 所属行业 companyind_text
        oneInfo.append(each.get(‘companyind_text‘))
        # 将最后一条信息放入bigdata
        bigdata.append(oneInfo)
    return bigdata


# 存储二维列表专用类
class MySave():
    def __init__(self):
        pass
    def saveToCsv(self, data, fileName: str, mode=‘w‘):
        with open(fileName, mode=mode, encoding=‘utf-8‘, newline=‘‘)as f:
            csvfile = csv.writer(f)
            # 写入data
            for each in data:
                csvfile.writerow(each)
            print(fileName, ‘存储完成‘)

    def saveToExcel(self, data, fileName):
        # 实例化工作簿对象
        wb = Workbook()
        # 准备工作表
        sheet = wb.active
        # 写入数据
        for each in data:
            sheet.append(each)
        wb.save(fileName)
        print(fileName, ‘存储完成‘)


# 抓多页
jobName = input("请输入搜索关键词：")

def getJobInfo(jobName, startNum, endNum):
    for i in range(startNum, endNum):
        time.sleep(random.randint(1, 3))
        # 拼接链接
        url = f‘http://search.51job.com/list/000000,000000,0000,00,9,99,‘ + jobName + ‘,2,‘ + str(i) + ‘.html‘
        print(f‘正在抓取第{i}页‘)
        # 运行函数访问url，返回数据
        data = getOnePageInfo(url)
        save = MySave()
        # 存储到csv
        save.saveToCsv(data,‘51job数据.csv‘,‘a‘)

# 设置四个线程
t1 = threading.Thread(target=getJobInfo, args=(jobName, 1, 25))
t2 = threading.Thread(target=getJobInfo, args=(jobName, 25, 50))
t3 = threading.Thread(target=getJobInfo, args=(jobName, 51, 75))
t4 = threading.Thread(target=getJobInfo, args=(jobName, 75, 100))
# 开启四个线程
t1.start()
t2.start()
t3.start()
t4.start()

51job多线程爬取指定职业信息数据

标签：enc   EDA   upd   rand   reading   random   eval   com   search   

原文地址：https://www.cnblogs.com/James-221/p/13777794.html