智联招聘获取python岗位的数据
import requests
from lxml import html
import time
import pandas as pd
from sqlalchemy import create_engine
import traceback
from fake_useragent import UserAgent as UA #使用其random方法获取随机ua
class ZhaoPinSpider:
def __init__(self):
#http://sou.zhaopin.com/jobs/searchresult.ashx?jl=%E5%8C%97%E4%BA%AC&kw=python&sm=0&sg=466cc5c88f044d419cef734bd8713830&p=90
self.url=r"http://sou.zhaopin.com/jobs/searchresult.ashx?jl=%E5%8C%97%E4%BA%AC&kw=python&sm=0&sg=466cc5c88f044d419cef734bd8713830&p={}"
self.headers = {'Accept': 'text/html, application/xhtml+xml, image/jxr, */*',
'Accept - Encoding': 'gzip, deflate',
'Accept-Language': 'zh-Hans-CN, zh-Hans; q=0.5',
'Connection': 'Keep-Alive',
'User-Agent': UA().random}
#职位名称
self.Position_Title=[]
# url
self.url_list = []
#反馈率
self.Feedback=[]
#公司名称
self.Company_Name=[]
#职位月薪
self.Monthly_Salary =[]
#工作地点
self.Working_Place =[]
#发布日期
self.Published_Date=[] self.Position_Title_Key = None
self.Feedback_Key = None
self.Company_Name_Key = None
self.Monthly_Salary_Key = None
self.Working_Place_Key = None
self.Published_Date_Key = None
self.url_key="URL"
self.content_dic={}
self.allinfo_dic = {}
#-------------------------------
self.job_name_list = []
self.corporate_name_list = []
self.benefits_list = []
self.monthly_salary_list = []
self.job_place_list = []
self.published_date_list = []
self.job_nature_list = []
self.job_experience_list = []
self.qualifications_list = []
self.need_worker_num_list = []
self.job_type_list = []
self.job_description_list = []
self.company_introduction_list = []
self.company_scale_list = []
self.company_nature_list = []
self.company_industry_list = []
self.company_url_list = []
self.company_address_list = [] def start(self):
try:
for i in range(1,91):
req = requests.Session()
data = req.get(self.url.format(i), headers=self.headers).text
self.get_info(data,req) except Exception as e:
print(e)
def get_info(self,source,req):
etree=html.fromstring(source)
# # 职位名称
# self.Position_Title = []
# # 反馈率
# self.Feedback = []
# # 公司名称
# self.Company_Name = []
# # 职位月薪
# self.Monthly_Salary = []
# # 工作地点
# self.Working_Place = []
# # 发布日期
# self.Published_Date = []
TablesNodes=etree.xpath("//div[@class='newlist_list_content']//table")
max=len(TablesNodes)
if TablesNodes:
index=0
for TablesNode in TablesNodes:
if index!=0:
Nodes=TablesNode.xpath(".//tr[1]/td")
TitleNodes=Nodes[0]
url_nodes=TitleNodes.xpath("./div/a[@par]/@href")[0]
# FeedbackNodes=Nodes[1]
# CompanyNodes =Nodes[2]
# SalaryNodes =Nodes[3]
# PlaceNodes =Nodes[4]
# DateNodes = Nodes[5]
# self.Position_Title.append(TitleNodes.text_content().strip())
# FeedbackStr=FeedbackNodes.text_content().strip()
# self.Feedback.append(FeedbackStr if FeedbackStr else "0%")
# self.Company_Name.append(CompanyNodes.text_content().strip())
# self.Monthly_Salary.append(SalaryNodes.text_content().strip())
# self.Working_Place.append( PlaceNodes.text_content().strip())
# self.Published_Date.append( DateNodes.text_content().strip())
if "xiaoyuan" not in url_nodes:
print(url_nodes)
self.get_next_page(url_nodes, req)
self.allinfo_dic.setdefault("job_name", self.job_name_list)
self.allinfo_dic.setdefault("corporate_name", self.corporate_name_list)
self.allinfo_dic.setdefault("benefits", self.benefits_list)
self.allinfo_dic.setdefault("monthly_salary", self.monthly_salary_list)
self.allinfo_dic.setdefault("job_place", self.job_place_list)
self.allinfo_dic.setdefault("published_date", self.published_date_list)
self.allinfo_dic.setdefault("job_nature", self.job_nature_list)
self.allinfo_dic.setdefault("job_experience", self.job_experience_list)
self.allinfo_dic.setdefault("qualifications", self.qualifications_list)
self.allinfo_dic.setdefault("need_worker_num", self.need_worker_num_list)
self.allinfo_dic.setdefault("job_type", self.job_type_list)
self.allinfo_dic.setdefault("job_description", self.job_description_list)
self.allinfo_dic.setdefault("company_introduction", self.company_introduction_list)
self.allinfo_dic.setdefault("company_scale", self.company_scale_list)
self.allinfo_dic.setdefault("company_nature", self.company_nature_list)
self.allinfo_dic.setdefault("company_industry", self.company_industry_list)
self.allinfo_dic.setdefault("company_url", self.company_url_list)
self.allinfo_dic.setdefault("company_address", self.company_address_list)
self.save_Data()
self.allinfo_dic.clear()
self.job_name_list.clear()
self.corporate_name_list.clear()
self.benefits_list.clear()
self.monthly_salary_list.clear()
self.job_place_list.clear()
self.published_date_list.clear()
self.job_nature_list.clear()
self.job_experience_list.clear()
self.qualifications_list.clear()
self.need_worker_num_list.clear()
self.job_type_list.clear()
self.job_description_list.clear()
self.company_introduction_list.clear()
self.company_scale_list.clear()
self.company_nature_list.clear()
self.company_industry_list.clear()
self.company_url_list.clear()
self.company_address_list.clear()
else:
# Nodes = TablesNode.xpath(".//tr[1]/th")
# TitleNodes = Nodes[0]
# FeedbackNodes =Nodes[1]
# CompanyNodes =Nodes[2]
# SalaryNodes = Nodes[3]
# PlaceNodes =Nodes[4]
# DateNodes =Nodes[5]
# self.Position_Title_Key=TitleNodes.text_content().strip()
# self.Feedback_Key=FeedbackNodes.text_content().strip()
# self.Company_Name_Key=CompanyNodes.text_content().strip()
# self.Monthly_Salary_Key=SalaryNodes.text_content().strip()
# self.Working_Place_Key=PlaceNodes.text_content().strip()
# self.Published_Date_Key=DateNodes.text_content().strip()
index = index+1
def save_Data(self):
df=pd.DataFrame(self.allinfo_dic)
df.to_csv("zhaopininfo.csv")
df.to_csv("zhaopininfo.xlsx")
pd.io.sql.to_sql(df,"all_results",schema="zhaopin",con=self.get_engine(),if_exists="append",index=False)
def get_engine(self):
conn=create_engine("mysql+pymysql://root:Aa1234@localhost:3306/zhaopin?charset=utf8mb4")
return conn def get_next_page(self, nexturl,req):
data=req.get(nexturl).text
self.get_page_info(data) def get_page_info(self,htmlstr):
try:
root=html.fromstring(htmlstr)
job_name=root.xpath("//div[@class='top-fixed-box' and not(@id)]//div[@class='inner-left fl']/h1/text()")[0]
print(job_name)
corporate_name=root.xpath("//div[@class='top-fixed-box' and not(@id)]//div[@class='inner-left fl']/h2/a/text()")[0]
benefits=root.xpath("//div[@class='top-fixed-box' and not(@id)]//div[@class='inner-left fl']/div[@class='welfare-tab-box']")[0].text_content()
#概要
Nodes = root.xpath("//div[@class='terminalpage-left']//ul/li/strong")
monthly_salary=Nodes[0].text_content().strip()
job_place=Nodes[1].text_content().strip()
published_date=Nodes[2].text_content().strip()
job_nature=Nodes[3].text_content().strip()
job_experience=Nodes[4].text_content().strip()
qualifications=Nodes[5].text_content().strip()
need_worker_num=Nodes[6].text_content().strip()
job_type=Nodes[7].text_content().strip() job_description=root.xpath("//div[@class='tab-inner-cont']")[0].text_content().strip()
company_introduction=root.xpath("//div[@class='tab-inner-cont']")[1].text_content().strip() #
companyNodes = root.xpath("//ul[@class='terminal-ul clearfix terminal-company mt20']/li/strong")
company_scale=companyNodes[0].text_content().strip()
company_nature=companyNodes[1].text_content().strip()
company_industry=companyNodes[2].text_content().strip()
company_url=companyNodes[3].text_content().strip()
company_address=None
try:
company_address=companyNodes[4].text_content().strip()
except:
company_address="地址未填写"
self.job_name_list.append(job_name)
self.corporate_name_list.append(corporate_name)
self.benefits_list.append(benefits)
self.monthly_salary_list.append(monthly_salary)
self.job_place_list.append(job_place)
self.published_date_list.append(published_date)
self.job_nature_list.append(job_nature)
self.job_experience_list.append(job_experience)
self.qualifications_list.append(qualifications)
self.need_worker_num_list.append(need_worker_num)
self.job_type_list.append(job_type)
self.job_description_list.append(job_description)
self.company_introduction_list.append(company_introduction)
self.company_scale_list.append(company_scale)
self.company_nature_list.append(company_nature)
self.company_industry_list.append(company_industry)
self.company_url_list.append(company_url)
self.company_address_list.append(company_address)
except:
print(traceback.print_exc()) if __name__=="__main__":
ZhaoPinSpider().start()
智联招聘获取python岗位的数据的更多相关文章
- 智联招聘的python岗位数据结巴分词(二)
上次获取第一次分词之后的内容了 但是数据数据量太大了 ,这时候有个模块就派上用场了collections模块的Counter类 Counter类:为hashable对象计数,是字典的子类. 然后使用m ...
- 智联招聘的python岗位数据结巴分词(一)
如何获取数据点击这里 下载之后的文件名为:all_results.csv 数据样式大概这样.然后下面我分析的是工作要求 也就是那边的绿框那一列. import csv import os impor ...
- 智联招聘的python岗位数据词云制作
# 根据传入的背景图片路径和词频字典.字体文件,生成指定名称的词云图片 def generate_word_cloud(img_bg_path, top_words_with_freq, font_p ...
- 用python抓取智联招聘信息并存入excel
用python抓取智联招聘信息并存入excel tags:python 智联招聘导出excel 引言:前一阵子是人们俗称的金三银四,跳槽的小朋友很多,我觉得每个人都应该给自己做一下规划,根据自己的进步 ...
- python爬取智联招聘职位信息(多进程)
测试了下,采用单进程爬取5000条数据大概需要22分钟,速度太慢了点.我们把脚本改进下,采用多进程. 首先获取所有要爬取的URL,在这里不建议使用集合,字典或列表的数据类型来保存这些URL,因为数据量 ...
- python爬取智联招聘职位信息(单进程)
我们先通过百度搜索智联招聘,进入智联招聘官网,一看,傻眼了,需要登录才能查看招聘信息 没办法,用账号登录进去,登录后的网页如下: 输入职位名称点击搜索,显示如下网页: 把这个URL:https://s ...
- Python+selenium爬取智联招聘的职位信息
整个爬虫是基于selenium和Python来运行的,运行需要的包 mysql,matplotlib,selenium 需要安装selenium火狐浏览器驱动,百度的搜寻. 整个爬虫是模块化组织的,不 ...
- 用生产者消费模型爬取智联招聘python岗位信息
爬取python岗位智联招聘 这里爬取北京地区岗位招聘python岗位,并存入EXECEL文件内,代码如下: import json import xlwt import requests from ...
- 用Python爬取智联招聘信息做职业规划
上学期在实验室发表时写了一个爬取智联招牌信息的爬虫. 操作流程大致分为:信息爬取——数据结构化——存入数据库——所需技能等分词统计——数据可视化 1.数据爬取 job = "通信工程师&qu ...
随机推荐
- P5056 插头dp
题面 Source: unordered_map: #include <iostream> #include <tr1/unordered_map> #include < ...
- Python 学习笔记之—— PIL 库
PIL,全称 Python Imaging Library,是 Python 平台一个功能非常强大而且简单易用的图像处理库.但是,由于 PIL 仅支持到Python 2.7,加上年久失修,于是一群志愿 ...
- [leetcode-609-Find Duplicate File in System]
https://discuss.leetcode.com/topic/91430/c-clean-solution-answers-to-follow-upGiven a list of direct ...
- SPOJ 375 Query on a tree(树链剖分)(QTREE)
You are given a tree (an acyclic undirected connected graph) with N nodes, and edges numbered 1, 2, ...
- 网络流——poj1273(入门)
题目链接:排水沟 题意:现有n个排水沟和m个点(其中1是源点,m是汇点),给定n个排水沟所连接的点,求从源点到汇点的最大流量. [EK解法] #include <algorithm> #i ...
- MQTT在平台中的应用【本文摘自智车芯官网】
MQTT(Message Queuing Telemetry Transport,消息队列遥测传输)是IBM开发的一个即时通讯协议,有可能成为物联网的重要组成部分.该协议支持所有平台,几乎可以把所有联 ...
- JVM高级内存优化面试
Sun HotSpot VM,是JDK和Open JDK中自带的虚拟机,也是目前使用范围最广的Java虚拟机. JVM内存分布程序计数器:是一块较小的内存空间,可以看作是当前线程所执行的字节码的行号指 ...
- 2017Nowcoder Girl初赛重现赛
https://ac.nowcoder.com/acm/contest/315#question A.平方数 代码: #include <bits/stdc++.h> using name ...
- koajs框架学习
目录: 概述 hello world 中间件 路由中间件koa-router body解析中间件koa-bodyparser 授之以渔 一.概述 koa 是由 Express 原班人马打造的,致力于成 ...
- 【转】如何解决每次打开office2010都会出现正在配置以及使用KMS
转自:http://jingyan.baidu.com/article/90895e0fb1525964ec6b0bb5.html 一.使用mini-KMS_Activator_v1.2_Office ...