Python爬取Json数据的示例
Python教程栏目介绍爬取Json数据实例
相关免费学习推荐:python教程(视频)
本文中以爬取其中的AI流转率数据为例。
该地址返回的响应内容为Json类型,其中红框标记的项即为AI流转率值:
实现代码如下:
import requests import json import csv # 爬虫地址 url = 'https://databank.yushanfang.com/api/ecapi?path=/databank/crowdFullLink/flowInfo&fromCrowdId=3312&beginTheDate=201810{}&endTheDate=201810{}&toCrowdIdList[0]=3312&toCrowdIdList[1]=3313&toCrowdIdList[2]=3314&toCrowdIdList[3]=3315' # 携带cookie进行访问 headers = { 'Host':'databank.yushanfang.com', 'Referer':'https://databank.yushanfang.com/', 'Connection':'keep-alive', 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.84 Safari/537.36', 'Cookie':'_tb_token_=iNkDeJLdM3MgvKjhsfdW; bs_n_lang=zh_CN; cna=aaj1EViI7x0CATo9kTKvjzgS; ck2=072de851f1c02d5c7bac555f64c5c66d; c_token=c74594b486f8de731e2608cb9526a3f2; an=5YWo5qOJ5pe25Luj5a6Y5pa55peX6Iiw5bqXOnpmeA%3D%3D; lg=true; sg=\"=19\"; lvc=sAhojs49PcqHQQ%3D%3D; isg=BPT0Md7dE_ic5Ie3Oa85RxaMxbLK3UqJMMiN6o5VjH8C-ZRDtt7aRXb3fXGEAVAP', } rows = [] for n in range(20, 31): row = [] row.append(n) for m in range (21, 32): if m < n + 1: row.append("") else: # 格式化请求地址,更换请求参数 reqUrl = url.format(n, m) # 打印本次请求地址 print(url) # 发送请求,获取响应结果 response = requests.get(url=reqUrl, headers=headers, verify=False) text = response.text # 打印本次请求响应内容 print(text) # 将响应内容转换为Json对象 jsonobj = json.loads(text) # 从Json对象获取想要的内容 toCntPercent = jsonobj['data']['interCrowdInfo'][1]['toCntPercent'] # 生成行数据 row.append(str(toCntPercent)+"%") # 保存行数据 rows.append(row) # 生成Excel表头 header = ['AI流转率', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31'] # 将表头数据和爬虫数据导出到Excel文件 with open('D:\\res\\pachong\\tmall.csv', 'w', encoding='gb18030') as f : f_csv = csv.writer(f) f_csv.writerow(header) f_csv.writerows(rows)
import csv import json import ssl import urllib.request # 爬虫地址 url = 'https://databank.yushanfang.com/api/ecapi?path=/databank/crowdFullLink/flowInfo&fromCrowdId=3312&beginTheDate=201810{}&endTheDate=201810{}&toCrowdIdList[0]=3312&toCrowdIdList[1]=3313&toCrowdIdList[2]=3314&toCrowdIdList[3]=3315' # 不校验证书 ssl._create_default_https_context = ssl._create_unverified_context # 携带cookie进行访问 headers = { 'Host':'databank.yushanfang.com', 'Referer':'https://databank.yushanfang.com/', 'Connection':'keep-alive', 'User-Agent':'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.84 Safari/537.36', 'Cookie':'_tb_token_=iNkDeJLdM3MgvKjhsfdW; bs_n_lang=zh_CN; cna=aaj1EViI7x0CATo9kTKvjzgS; ck2=072de851f1c02d5c7bac555f64c5c66d; c_token=c74594b486f8de731e2608cb9526a3f2; an=5YWo5qOJ5pe25Luj5a6Y5pa55peX6Iiw5bqXOnpmeA%3D%3D; lg=true; sg=\"=19\"; lvc=sAhojs49PcqHQQ%3D%3D; isg=BPT0Md7dE_ic5Ie3Oa85RxaMxbLK3UqJMMiN6o5VjH8C-ZRDtt7aRXb3fXGEAVAP', } rows = [] n = 20 while n <31: row = [] row.append(n) m =21 while m <32: if m < n + 1: row.append("") else: # 格式化请求地址,更换请求参数 reqUrl = url.format(n, m) # 打印本次请求地址 print(reqUrl) # 发送请求,获取响应结果 request = urllib.request.Request(url=reqUrl, headers=headers) response = urllib.request.urlopen(request) text = response.read().decode('utf8') # 打印本次请求响应内容 print(text) # 将响应内容转换为Json对象 jsonobj = json.loads(text) # 从Json对象获取想要的内容 toCntPercent = jsonobj['data']['interCrowdInfo'][1]['toCntPercent'] # 生成行数据 row.append(str(toCntPercent) + "%") m = m+1 rows.append(row) n = n+1 # 生成Excel表头 header = ['AI流转率', '21', '22', '23', '24', '25', '26', '27', '28', '29', '30', '31'] # 将表头数据和爬虫数据导出到Excel文件 with open('D:\\res\\pachong\\tmall.csv', 'w', encoding='gb18030') as f : f_csv = csv.writer(f) f_csv.writerow(header) f_csv.writerows(rows)
导出内容如下:
到此这篇关于使用Python爬取Json数据的文章就介绍到这了。
相关免费学习推荐:php编程(视频)
以上就是Python爬取Json数据的示例的详细内容,更多请关注其它相关文章!