Python 读写json文件

本文旨在记录将读入url后的json文件转为python格式从而进行分析

• 读入url，保存json文件

import urllib, jsonresponse = urllib.urlopen(url)data = json.loads(response.read())

• json切片

def dict_slice(adict, start, end):    keys = adict.keys()    dict_slice = {}    for k in keys[start:end]:        dict_slice[k] = adict[k]    return dict_sliceresult = dict_slice(data, 1, 2)result = result[u'rows'][0][u'elements'][0][u'distance'][u'text']#取出json内部分内容

• json格式转为python格式

distance = json.dumps(result)#转为python格式

实例代码

该代码主要实现计算两个城市之间的距离，利用google distance matrix的api，更多应用示例见以下链接：

https://developers.google.com/maps/documentation/distance-matrix/start

该代码根据读取xls文件中的相应城市地址，从而进行计算并输出所有的距离

#!/usr/bin/env python2# -*- coding: utf-8 -*-"""Created on Sun May 21 22:49:59 2017@author: chenjingwen"""import xlrdimport numpy as npimport urllib, jsonimport csvdef dict_slice(adict, start, end):    keys = adict.keys()    dict_slice = {}    for k in keys[start:end]:        dict_slice[k] = adict[k]    return dict_slicefiled = xlrd.open_workbook('Distance1.xls') # 打开xls文件table = filed.sheets()[0]nrows = table.nrowsdestination=[]  originations = []  #将table中第一行的数据读取并添加到data_list中for i in range(nrows):    dest = table.row_values(i)[0].encode("utf-8")    origin = table.row_values(i)[1].encode("utf-8")    destination.append(dest)    originations.append(origin)website0 = 'https://maps.googleapis.com/maps/api/distancematrix/json?units=imperial&origins='#origins = 'Washington,DC'website1 = '&destinations='#destination = 'New,York,City,NY'website2 = '&key=AIzaSyD1SqEGEsCe3iaktwXALoSDx3b4JiDA0Dw'#输入apiresult = []for i in range(444,nrows):    url = website0 + originations[i] + website1 + destination[i] + website2    response = urllib.urlopen(url)    data = json.loads(response.read())    res = dict_slice(data, 1, 2)    res = res[u'rows'][0][u'elements'][0][u'distance'][u'text']    distance = json.dumps(res)    result.append([i,distance])with open('destination_result.csv','w') as f: #this will save the results of all frames,you can just uncomment it        f_csv = csv.writer(f)        f_csv.writerows(result)