Python爬虫练习(requests模块)

Python爬虫练习(requests模块)

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一、使用正则表达式解析页面和提取数据

1、爬取动态数据(js格式)

爬取http://fund.eastmoney.com/fund.html

流程：

######a.分析页面

用浏览器打开链接，清空已加载的数据，点击下一页，可看到动态数据已被封装成js格式：

var db = {...}

######b.获取url

######c.获取响应

######d.使用正则表达式清洗数据

######e.转为二维列表

f.遍历

import re
import requests
'''
http://fund.eastmoney.com/Data/Fund_JJJZ_Data.aspx?t=1&lx=1&
letter=&gsid=&text=&sort=zdf,desc&page=3,200&dt=1530794512554&atfc=&onlySale=0
'''
def getFund(page):
    '''
    获取js格式数据
    :param page: 页码
    :return:
    '''
    #设置url
    url = '''http://fund.eastmoney.com/Data/Fund_JJJZ_Data.aspx?t=1&lx=1&letter=&
          gsid=&text=&sort=zdf,desc&page=%d,200&dt=1530794512554&atfc=&onlySale=0
           '''%page

    # 获取响应
    response = requests.get(url).content.decode("utf-8")
    # print(response)
    # d.使用正则表达式清洗数据
    datare = ".*datas:(.*),count"
    datas = re.findall(datare,response)

    # 转为二维列表
    datas = eval(datas[0])
    # print(datas)
    # 遍历
    for data in datas:
        print(data)

if __name__ == '__main__':
    # 获取基金数据，
    page = input("输入页码：")
    getFund(int(page))

二、使用bs4解析页面和提取数据

1、抓取抓取51job岗位数量

流程：a.设置URL，请求头 b.获取响应 c.创建bs4对象 d.找到岗位数量标签类名

import requests
from bs4 import BeautifulSoup

# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

# 设置获取python岗位数量的url
url = "https://search.51job.com/list/030200,000000,0000,00,9,99,python,2,1.html"

# 获取响应
response = requests.get(url,headers=headers)
# 解码
html = response.content.decode('gbk')
# 创建bs4对象
soup = BeautifulSoup(html,'lxml')
#获取岗位标签
#通过类名rt找到岗位数量标签
jobNum = soup.select('.rt')[0].text
print(jobNum.strip())
输出：
共3506条职位

2、抓取基金

流程：a.设置URL，请求头 b.获取响应 c.创建bs4对象 d.找到基金列表类名 e.保存为csv文件

import csv

import requests
from bs4 import BeautifulSoup

# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

# 抓取全部，翻页
for i in range(1,2):
    # 设置URL
    url = "http://quote.stockstar.com/fund/stock_3_1_%d.html" % i
    # 获取响应
    response = requests.get(url,headers=headers)
    # < meta
    # http - equiv = "Content-Type"
    # content = "text/html; charset=gb2312" >
    # 编码格式为gb2312 ,即中文简体
    # 而gbk编码包含简体和繁体，所以解码时使用gbk
    html = response.content.decode('gbk')
    soup = BeautifulSoup(html,'lxml')
    # 获取当前页的全部基金
    stackList = soup.find('tbody',id='datalist').find_all('tr')
    print(len(stackList))
    for stack in stackList:
        # 基金代号  #datalist > tr.hoverTr > td:nth-child(1) > a
        stackId = stack.select("td:nth-of-type(1) > a")[0].text
        # 基金简称  #datalist > tr:nth-child(1) > td:nth-child(2) > a
        stackName = stack.select("td:nth-of-type(2) > a")[0].text
        # url
        stackUrl = stack.select("td:nth-of-type(1) > a")[0]["href"]
        # 基金净值 #datalist > tr:nth-child(1) > td:nth-child(3)
        stackMoney = stack.select("td:nth-of-type(3)")[0].text

        print(stackId,stackName,stackUrl,stackMoney)
        #写入csv文件
        with open('./fund.csv','a+',newline='',encoding='utf-8',errors='ignore') as f:
            writer = csv.writer(f)
            writer.writerow([stackId,stackName,stackUrl,stackMoney])

3、把数据存入数据库(MySQL)

把fund.csv存入数据库中。

流程：a.创建fund数据库 b.连接数据库 c.创建游标 d.读取文本 e.循环写入文本 f.创建sql插入语句 g.执行sql语句，提交 h.关闭文件、游标、数据库连接

import pymysql
# 连接数据库
conn = pymysql.connect(
    host='127.0.0.1', user='root', password="123456",
    database='fund', port=3306,
    charset='utf8'
)

# 创建游标
cursor = conn.cursor()
# 读取文本
stockData = open('fund.csv','r',encoding='utf-8')
# 循环写入文本
for stock in stockData.readlines():
    s = stock.split(',')
    print(s)
    # 由于最后一个字符带有换行符，所以要去掉
    print(s[3].strip())
    #创建sql插入语句 %r自动给字符串加上单引号
    sql = "insert into stock(stackId,stackName,stackUrl,stackMoney) values (%r,%r,%r,%r)" \
          %(s[0],s[1],s[2],s[3].strip())
    #执行sql语句，提交
    cursor.execute(sql)
    conn.commit()

# 关闭文件、游标、数据库连接
stockData.close()
cursor.close()
conn.close()

4、抓取岗位

流程：a.设置种子url获取总页数 b.循环获取每页的数据 c.获取响应 d.创建bs4对象 e.匹配符合条件的属性，获取岗位信息列表

import requests
from bs4 import BeautifulSoup

# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

def getJobPageTotal(url):
    '''
    获取岗位总页数
    :param url: 种子url
    :return: 总页数
    '''
    return 2

def getJobDetial(url):
    '''
    获取岗位细节
    :param url:
    :return: (地点,类型,招聘人数,职责,要求)
    '''

    response = requests.get(url,headers=headers).text
    soup = BeautifulSoup(response,'lxml')
    # #position_detail > div > table > tbody > tr.c.bottomline > td:nth-child(1)
    # position_detail > div > table > tbody > tr.c.bottomline

    # 地点 类型 招聘人数 职责 要求
    jobAddr = soup.select('tr.c.bottomline > td:nth-of-type(1)')[0].text.strip('工作地点：')
    jobType = soup.select('tr.c.bottomline > td:nth-of-type(2)')[0].text.strip('职位类别：')
    jobPNum = soup.select('tr.c.bottomline > td:nth-of-type(3)')[0].text.strip('招聘人数：')
    jobDuty = soup.find_all(class_='squareli')[0].text 
    jobDuReq = soup.find_all(class_='squareli')[1].text
    # print(jobAddr,jobType,jobPNum,jobDuty,jobDuReq)
    return jobAddr,jobType,jobPNum,jobDuty,jobDuReq


def getJobInfo(url):
    '''
    获取岗位信息
    :param url:
    :return:
    '''
    # 获取响应
    response = requests.get(url,headers=headers).text
    # print(response)
    #创建bs4对象
    soup = BeautifulSoup(response,'lxml')
    #匹配符合条件的属性
    # [,]匹配所有符合条件的属性
    jobList = soup.find_all('tr',class_=['even','add'])
    # print(jobList)
    for job in jobList:
        # tr:nth-child(2) > td.l.square > a    获取岗位名称
        jobName = job.select('td:nth-of-type(1) > a')[0].text
        #获取岗位url
        jobUrl = r"https://hr.tencent.com/" + job.select('td:nth-of-type(1) > a')[0]["href"]
        #获取岗位细节
        jobDetail = getJobDetial(jobUrl)

       
        print(jobName,jobUrl,jobDetail)

if __name__ == '__main__':
    # 设置种子url获取总页数 获取职位
    positions = ['python']
    url = "https://hr.tencent.com/position.php?keywords=%s" % positions[0]
    pageTotal = getJobPageTotal(url)
    # 循环获取每页的数据
    for i in range(pageTotal):
        # https: // hr.tencent.com / psition.php?keywords = python & start = 20  # a
        #点击下一页时，start加10，每页显示10条数据
        url = r"https://hr.tencent.com/position.php?keywords=%s&start=%d#a"%(positions[0],i*10)
        getJobInfo(url)

三、使用xpath解析页面和提取数据

1、抓取51城市列表

流程：a.设置请求体、url b.获取响应 c.创建xml树形结构对象 d.匹配城市列表类名，获取城市列表

e.遍历城市列表

import requests
import lxml
from lxml import etree
# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

# 设置url
url = "https://jobs.51job.com/"
# 获取响应
response = requests.get(url,headers=headers).content.decode('gbk')
# print(response)
mytree = lxml.etree.HTML(response)
# 匹配城市列表类名，获取城市列表
# /html/body/div[2]/div[2]/div[2]/div[1]
cityList = mytree.xpath('//div[@class="e e4"][1]//div[@class="lkst"]/a')
# print(cityList)
for city in cityList:
    cityName = city.xpath('./text()')[0]
    cityUrl = city.xpath('./@href')[0]
    print(cityName,cityUrl)

2、抓取51岗位信息

流程：a.设置请求体、url b.获取响应 c.创建xml树形结构对象 d.匹配岗位列表类名，获取岗位列表

e.遍历岗位列表

import requests
import lxml
from lxml import etree
# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

def getJobInfo(url):
    '''
    获取岗位信息
    :param url:
    :return:
    '''
    #获取响应
    response = requests.get(url,headers=headers).content.decode('gbk')
    # print(response)
    #创建xml树形结构
    mytree = lxml.etree.HTML(response)
    #匹配岗位列表类名，获取岗位列表
    jobList = mytree.xpath('//div[@class="detlist gbox"]/div')
    # print(jobList)

    for job in jobList:
       # e.遍历岗位列表
       # 岗位名
       # / html / body / div[3] / div[3] / div[1] / div[2] / div[1] / p[1] / span[1]
       jobName = job.xpath('.//span[@class="title"]/a/@title')[0]
       # url
       jobUrl = job.xpath('.//span[@class="title"]/a/@href')[0]
       # 公司名
       company = job.xpath('.//p[@class="info"]/a/@title')[0]
        # 工作地点
       jobAddr = job.xpath('.//p[@class="info"]/span[@class="location name"]/text()')[0]
        # 薪资
       money = job.xpath('.//p[@class="info"]/span[3]/text()')[0]
        # 要求
       orders = job.xpath('.//p[@class="order"]/text()')[0]
       order = ""
       for i in orders:
           order += i.strip()

       # 工作描述
       content = job.xpath('.//p[@class="text"]/text()')[0]
       print(jobName, jobUrl, company, jobAddr, money, order)
       print(content)

if __name__ == '__main__':
    url = "https://jobs.51job.com/guangzhou/"
    getJobInfo(url)

3、抓取51岗位页数

流程：a.设置请求体、url b.获取响应 c.创建xml树形结构对象 d.匹配总页数类名 e.正则获取数量

import re

'''
a.设置请求体、url   b.获取响应 c.创建xml树形结构对象 d.匹配总页数类名

'''
import requests
import lxml
from lxml import etree
# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

def getJobTotalPage(url):
    '''
    获取岗位总页数
    :param url:
    :return: int 总页数
    '''
    # 获取响应
    response = requests.get(url, headers=headers).content.decode('gbk')
    # print(response)
    # 创建xml树形结构
    mytree = lxml.etree.HTML(response)
    # 匹配岗位列表类名，获取岗位列表
    totalPage = mytree.xpath('//*[@id="cppageno"]/span[1]/text()')[0]

    # 正则匹配数量
    totalPage = re.findall('.*共(\d*)页。*',totalPage)[0]
    print(totalPage)
    return int(totalPage)

if __name__ == '__main__':
    url = "https://jobs.51job.com/beijing/"
    getJobTotalPage(url)

4、抓取51job

流程：a.设置种子url b.获取城市列表 c.循环城市列表 d.获取总页数 e.获取岗位信息

import csv
import time
import requests
import lxml
from lxml import etree
import re

'''
a.设置种子url b.获取城市列表 c.循环城市列表 d.获取总页数 e.获取岗位信息
'''

# 设置请求头
headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

def getCityList(url):
    '''
    获取城市列表
    :param url:
    :return: {"cityName":"cityUrl"}
    '''
    # 获取响应
    response = requests.get(url, headers=headers).content.decode('gbk')
    # print(response)
    mytree = lxml.etree.HTML(response)
    # 匹配城市列表类名，获取城市列表
    # /html/body/div[2]/div[2]/div[2]/div[1]
    cityList = mytree.xpath('//div[@class="e e4"][1]//div[@class="lkst"]/a')
    # print(cityList)
    cityDict = {}
    for city in cityList:
        cityName = city.xpath('./text()')[0]
        cityUrl = city.xpath('./@href')[0]
        cityDict[cityName] = cityUrl
    return cityDict

def getPageTotal(url):
    '''
    获取总页数
    :param url:
    :return: 总页数
    '''
    # 获取响应
    response = requests.get(url, headers=headers).content.decode('gbk')
    # print(response)
    # 创建xml树形结构
    mytree = lxml.etree.HTML(response)
    # 匹配岗位列表类名，获取岗位列表
    totalPage = mytree.xpath('//*[@id="cppageno"]/span[1]/text()')[0]

    # 正则匹配数量
    totalPage = re.findall('.*共(\d*)页。*', totalPage)[0]
    # print(totalPage)
    return int(totalPage)


def getJobInfo(cityName,cityUrl,pageTotal):
    '''
    获取岗位信息
    :param cityName: 城市名称
    :param cityUrl: 城市url
    :param pageTotal: 总页数
    :return:
    '''
    for i in range(1,pageTotal+1):
        #设置url
        url = cityUrl + "p%d" %i
        # 获取响应
        response = requests.get(url, headers=headers).content.decode('gbk')
        # print(response)
        # 创建xml树形结构
        mytree = lxml.etree.HTML(response)
        # 匹配岗位列表类名，获取岗位列表
        jobList = mytree.xpath('//div[@class="detlist gbox"]/div')
        # print(jobList)
        if jobList:
            for job in jobList:
                # e.遍历岗位列表
                # 岗位名
                # / html / body / div[3] / div[3] / div[1] / div[2] / div[1] / p[1] / span[1]
                jobName = job.xpath('.//span[@class="title"]/a/@title')[0]
                # url
                jobUrl = job.xpath('.//span[@class="title"]/a/@href')[0]
                # 公司名
                company = job.xpath('.//p[@class="info"]/a/@title')[0]
                # 工作地点
                jobAddr = job.xpath('.//p[@class="info"]/span[@class="location name"]/text()')[0]
                # 薪资
                money = job.xpath('.//p[@class="info"]/span[3]/text()')
                if money:
                    money = money[0]
                else:
                    money = "面谈"
                # 要求
                orders = job.xpath('.//p[@class="order"]/text()')[0]
                order = ""
                for i in orders:
                    order += i.strip()

                # 工作描述
                content = job.xpath('.//p[@class="text"]/text()')[0]
                print(url)
                # print(jobName, jobUrl, company, jobAddr, money, order)
                # print(content)
                # 写入文件
                with open('./data/'+ cityName+ '.csv','a+',encoding='utf-8',errors='ignore') as f:
                    writer = csv.writer(f)
                    writer.writerow([jobName, jobUrl, company, jobAddr, money, order,content])

if __name__ == '__main__':
    #设置种子url
    starUrl = "https://jobs.51job.com/"
    #获取城市列表
    cityList = getCityList(starUrl)
    # 循环城市列表
    for cityName,cityUrl in cityList.items():
        # d.获取总页数
        pageTotal = getPageTotal(cityUrl)
        time.sleep(1)
        # 获取岗位信息
        getJobInfo(cityName,cityUrl,pageTotal)

5、爬取Jsp页面

流程：a.设置种子url b.设置表单数据 c.获取响应 d.创建xml树形结构 e.获取总页数 f.循环获取每页数据 g.设置动态的表单数据 h.获取响应

import requests
import lxml
import math
from lxml import etree

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}
# 设置种子url
starUrl = "http://www.hshfy.sh.cn/shfy/gweb2017/ktgg_search_content.jsp"
# 设置表单数据
data = {
    "yzm": "yWFF",
    "ft": "",
    "ktrqks": "2018-07-07",
    "ktrqjs": "2018-08-07",
    "spc": "",
    "yg": "",
    "bg": "",
    "ah": "",
    "pagesnum": "1",
}
# 获取响应
response = requests.get(starUrl, data=data, headers=headers).text
# print(response)
# 创建xml树形结构
mytree = lxml.etree.HTML(response)
# 获取总页数
# //*[@id="ktgg_search_content"]/div
# //*[@id="ktgg_search_content"]/div/div/font/strong
pageTotal = int(mytree.xpath('/html/body/div/div/font/strong/text()')[0])
pageTotal = math.ceil(pageTotal / 15)
# print(pageTotal)
# 循环获取每页数据
for i in range(1,pageTotal+1):
    # 设置表单数据
    data = {
        "yzm": "yWFF",
        "ft": "",
        "ktrqks": "2018-07-07",
        "ktrqjs": "2018-08-07",
        "spc": "",
        "yg": "",
        "bg": "",
        "ah": "",
        "pagesnum": i,
    }
    url = "http://www.hshfy.sh.cn/shfy/gweb2017/ktgg_search_content.jsp"
    # 获取响应
    response = requests.get(url, data=data, headers=headers).text
    # print(response)
    # 创建xml树形结构
    mytree = lxml.etree.HTML(response)
    # // *[ @ id = "report"] / tbody / tr[1] / td[1] / b
    reportList = mytree.xpath('//*[@id="report"]/tbody//tr[position()>1]')
    for report in reportList:
        # 法院
        fy = report.xpath('td[1]/font/text()')[0]
        # 法庭
        ft = report.xpath('td[2]/font/text()')[0]
        # 开庭时间
        fTime = report.xpath('td[3]/text()')[0]
        print(fy,ft,fTime)

6、项目交易

流程：a.获取总页数 b.获取项目信息

import requests
import lxml
from lxml import etree

headers = {
    "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/65.0.3325.181 Safari/537.36"}

def getPageTotal():
    '''
    获取总页数
    :return: 总页数 Int
    '''
    url = "http://bbs.pinggu.org/prj/list/-4_1.html"
    response = requests.get(url,headers=headers).content.decode('gbk')
    mytree = lxml.etree.HTML(response)
    # / html / body / div[11] / div[29] / a[11]
    pageTotal = mytree.xpath('//*[@class="liebiao_fanye"]/a[last()]/text()')[0]
    pageTotal = pageTotal.replace('...','').strip()
    # print(pageTotal)
    return int(pageTotal)

def getDetailInfo(url):
    '''
    获取项目详细信息
    :param url:
    :return:
    '''
    response = requests.get(url, headers=headers).content.decode('gbk')
    mytree = lxml.etree.HTML(response)
    # /html/body/div[11]/div/div[2]/div[1]/ul
    projectList = mytree.xpath('//*[@class="ul-xiangq"]')[0]
    # 关键词
    pkey = projectList.xpath('./li[2]/span[2]/text()')
    if pkey:
        pkey = pkey[0]
    else:
        pkey = ''
    # 发布人
    pPublicer = projectList.xpath('./li[3]/span[2]/text()')[0]
    # 项目描述
    contents = projectList.xpath('./li[6]/span[2]/text()')
    content = ''
    if contents:
        for c in contents:
            content += c.strip()

    print(pkey,pPublicer,content)
    return (pkey,pPublicer,content)

def getProjectInfo(pageTotal):
    '''
    获取每页的项目信息
    :param pageTotal:
    :return:
    '''
    for i in range(1,pageTotal+1):
        url = "http://bbs.pinggu.org/prj/list/-4_%d.html" % i
        response = requests.get(url,headers=headers).content.decode('gbk')
        mytree = lxml.etree.HTML(response)
        projectList = mytree.xpath('//div[@class="liebiao_tiao"]')
        # print(projectList)
        for project in projectList:
            # 编号
            pId = project.xpath('.//div[@class="guding"]/a/text()')[0]
            # 名称
            pName = project.xpath('.//div[@class="ming"]/a/text()')[0]
            # url
            pUrl = 'http://bbs.pinggu.org'+project.xpath('.//div[@class="guding"]/a/@href')[0]
            # 获取项目详细信息
            pDetail = getDetailInfo(pUrl)
            # 价格
            pPrice = project.xpath('.//div[@class="jiage"]/text()')[0]
            # 竞标人数
            pPNum = project.xpath('.//div[@class="renshu"]/text()')[0]
            # 发布时间
            pTime = project.xpath('.//div[@class="shijian"]/text()')[0]
            # print(pId,pName,pUrl,pPrice,pPNum,pTime)

if __name__ == '__main__':
    # 获取总页数
    pageTotal = getPageTotal()
    # 获取项目信息
    getProjectInfo(pageTotal)

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