数据分析的小练习

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我是靠谱客的博主贪玩大象，最近开发中收集的这篇文章主要介绍数据分析的小练习，觉得挺不错的，现在分享给大家，希望可以做个参考。

概述

查看源码：

git地址：https://github.com/champion-yang/dataAnalysis

题目要求以及完成情况：

1.从指定招聘网站爬取数据，提取有效数据，并保存为json格式文件。
完成情况：bossZhipin
利用scrapy框架将boss直聘的相关信息爬取下来，保存为bossData.json文件.代码查看bossZhipin文件夹
2.设置post请求参数并将信息返回给变量response
完成情况：postReq.py
使用了resquests，json包，将请求头，请求信息，请求地址传入到resquests请求中，注意请求方式
3.将提取出来的数据转化为json格式，并赋值变量
完成情况：dataToJson.py
使用了json，resquests，BeautifulSoup，爬取笔趣网小说狂神，拿到了每一章的标题和对应的链接，并转化为json格式，赋值给变量jsonObj
4.用with函数创建json文件，通过json方法，写入json数据
完成情况：withFunBuildJson.py
使用3中拿到的json数据，通过encode()编码为二进制文件，写入build.json文件中

OK！直接上代码！
1.
使用了scrapy框架，这里给出爬虫的代码管道文件的代码

# -*- coding: utf-8 -*-
import scrapy

from bossZhipin.items import BosszhipinItem

class BossSpider(scrapy.Spider):
    name = 'boss'
    allowed_domains = ['zhipin.com']

    offset = 1
    url = 'https://www.zhipin.com/c101010100-p100109/?page='
    start_urls = [ url + str(offset)]
    url1 = 'https://www.zhipin.com'
    def parse(self, response):
        for each in response.xpath("//div[@class='job-primary']"):
            item = BosszhipinItem()
            item['company'] = each.xpath("./div[@class='info-company']/div/h3/a/text()").extract()[0]
            item['company_link'] = self.url1 + each.xpath("./div[@class='info-company']/div/h3/a/@href").extract()[0]
            item['position'] = each.xpath("./div[@class='info-primary']/h3/a/div[@class='job-title']/text()").extract()[0]
            item['wages'] = each.xpath("./div[@class='info-primary']/h3/a/span[@class]/text()").extract()[0]
            item['place'] = each.xpath("./div[@class='info-primary']/p/text()").extract()[0]
            item['experience'] = each.xpath("./div[@class='info-primary']/p/text()").extract()[1]
            yield scrapy.Request(item['company_link'],meta={'item':item},callback=self.get_company_info)
        if self.offset < 10:
            self.offset += 1
        yield scrapy.Request(self.url + str(self.offset) , callback=self.parse)
        
    def get_company_info(self,response):
        item = response.meta['item']
        company_link = item['company_link']
        company_infos = response.xpath("//div[@id='main']/div[3]/div/div[2]/div/div[1]/div/text()").extract()
        position_nums = response.xpath("//div[@id='main']/div[1]/div/div[1]/div[1]/span[1]/a/b/text()").extract()
        for position_num,company_info in zip(position_nums,company_infos):
            item['position_num'] = position_num
            item['company_info'] = company_info
            print(item['position_num'],item['company_info'])
            yield item

import json
# dumps和
class BosszhipinPipeline(object):
    def __init__(self):
        self.filename = open('bossData.json','wb')
    def process_item(self, item, spider):
        # 将获取到的数据保存为json格式
        text = json.dumps(dict(item),ensure_ascii=False) + 'n'
        self.filename.write(text.encode('utf-8'))
        return item

    def close_spider(self,spider):
        print('爬虫关闭')
        self.filename.close()

结果示例图

post参数包括：请求地址，请求信息，请求头

import requests,json
url = "http://xsxxgk.huaibei.gov.cn/site/label/8888?IsAjax=1&dataType=html&_=0.27182235250895626"
data ={
    "siteId":"4704161",
    "pageSize":"15",
    "pageIndex":"4",
    "action":"list",
    "isDate":"true",
    "dateFormat":"yyyy-MM-dd",
    "length":"46",
    "organId":"33",
    "type":"4",
    "catId":"3827899",
    "cId":"",
    "result":"暂无相关信息",
    "labelName":"publicInfoList",
    "file":"/xsxxgk/publicInfoList-xs"
}
headers = {
    "Accept":"text/html, */*; q=0.01","Accept-Encoding":"gzip, deflate",
    "Accept-Language":"zh-CN,zh;q=0.9,en;q=0.8",
    "Connection":"keep-alive",
    "Content-Length":"253",
    "Content-Type":"application/x-www-form-urlencoded; charset=UTF-8",
    "Cookie":"SHIROJSESSIONID=f30feb26-6495-4287-a5a6-27bbd76bf960",
    "Host":"xsxxgk.huaibei.gov.cn",
    "Origin":"http",
    "Referer":"http",
    "User-Agent":"Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36",
    "X-Requested-With":"XMLHttpRequest"
}
response = requests.post(url=url,data =data,headers=headers)
# response = requests.post(url=url,data =json.dumps(data),headers=headers) # 注意請求的方式是json还是text
print(response.text)

3&4.

import json,os
import requests
from bs4 import BeautifulSoup
import time

# 获取所有的章节名和章节地址
if __name__ == '__main__':
    # 拿到url地址
    target = 'http://www.biquw.com/book/7627/'
    req = requests.get(url=target)
    # 拿到html文档
    html = req.text
    # 解析html文档信息
    div_bf = BeautifulSoup(html)  # 创建bf对象来存储html信息
    div = div_bf.find_all('div',class_='book_list')
    a_list = div_bf.select('div>ul>li>a')
    titleList1 = []
    titleList2 = []
    for each in a_list:
        # 拿到每一章的标题和连接
        str1 = each.string
        str2 = target+each.get('href')
        titleList1.append(str1)
        titleList2.append(str2)
        d = dict(zip(titleList1,titleList2))
    jsonObj = json.dumps(d).encode()
    print(type(jsonObj))
    with open('build.json','wb') as f:
        f.write(jsonObj)