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北京数据
重庆数据
美国Rockwell
澳大利亚悉尼
印尼雅加达
London 英国
# -*- coding: utf-8 -*-
# All rights reversed, commercial use not allowed #! python3 # quickWeather.py - Prints the current weather for a location from the command line. """ k(开尔文）=273.15+T(摄氏度） json返回的是开尔文温度 Created on Sat Apr 16 10:24:28 2016 @author: daxiong """ import json, requests,sys,pylab,numpy #城市名称 cityName="beijing" #城市ID号 cityID="2038349" #我的免费appID appID="0383ae59663e14ab5a6855d5b6ad5d00" #获取时间段数 cnt="30" # Download the JSON data from OpenWeatherMap.org's API url="http://api.openweathermap.org/data/2.5/forecast/city?id=%s&APPID=%s&cnt=%s"%(cityID,appID,cnt) response = requests.get(url) response.raise_for_status() # Load JSON data into a Python variable. weatherData = json.loads(response.text) # Print weather descriptions. #主要获取weatherData---weather---main和description信息 w = weatherData['list'] print('Current weather in %s:' % (cityName)) temperature_list=[] cnt_list=[] time_list=[] for i in range(int(cnt)): time=w[i]['dt_txt'] print(time) main=w[i]['weather'][0]['main'] description=w[i]['weather'][0]['description'] temp=w[i]['main']['temp'] temp_Chinese=temp-273.15 temp_Chinese_round=round(temp_Chinese,2) temperature_list.append(temp_Chinese_round) cnt_list.append(i+1) time_list.append(str(time)) print(main, '-',description,'-',temp_Chinese_round,"摄氏度") print() barwidth=0.5 pylab.bar(cnt_list,temperature_list,width=barwidth,color='y') pylab.xlabel("times") pylab.ylabel('temperature') pylab.title("%s temperature prediction(x axis every 3 hours per tickt)"%cityName) pylab.show() #计算最高气温和最低气温 list_temperature_time=zip(temperature_list,time_list) dict_temperature_time=dict(list_temperature_time) max_temp=max(dict_temperature_time.keys()) min_temp=min(dict_temperature_time.keys()) print("最高气温:",max_temp,'摄氏度','-',dict_temperature_time[max_temp]) print("最低气温:",min_temp,'摄氏度','-',dict_temperature_time[min_temp]) #温差列表,用于统计哪天人最容易生病 temperature_difference_list=[] for i in range(len(temperature_list)-1): temperature_difference=temperature_list[i+1]-temperature_list[i] temperature_difference_list.append(temperature_difference) time_difference_list=[] for i in range(len(time_list)-1): time_difference=time_list[i]+'-'+time_list[i+1] time_difference_list.append(time_difference) list_temperature_time_difference=zip(temperature_difference_list,time_difference_list) dict_temperature_time_difference=dict(list_temperature_time_difference) max_temp_difference=max(dict_temperature_time_difference.keys()) min_temp_difference=min(dict_temperature_time_difference.keys()) print("最高温差:",round(max_temp_difference,2),'摄氏度','-',dict_temperature_time_difference[max_temp_difference]) print("最低温差:",round(min_temp_difference,2),'摄氏度','-',dict_temperature_time_difference[min_temp_difference]) #最容易生病时间段，取温差绝对值最大的key if abs(max_temp_difference)>abs(min_temp_difference): ill_likely_day=dict_temperature_time_difference[max_temp_difference] else: ill_likely_day=dict_temperature_time_difference[min_temp_difference] print("最容易生病时间段:",ill_likely_day) #统计温差又高到底排序的时间段 #温差绝对值列表 absolute_temperature_difference_list=[abs(i) for i in temperature_difference_list] list_temperature_time_difference=zip(absolute_temperature_difference_list,time_difference_list) dict_absolute_temperature_time_difference=dict(list_temperature_time_difference) sorted_temperature_time_difference=sorted(dict_absolute_temperature_time_difference.items(),reverse=True) ''' # Compute location from command line arguments. if len(sys.argv) < 2: print('Usage: quickWeather.py location') sys.exit() location = ' '.join(sys.argv[1:]) len(weatherData) Out[21]: 5 for i in weatherData: print(i) city #城市信息 cod #内部参数 cnt #预测天数 list #信息列表，主要获取weatherData---weather---main和description信息 message #内部参数 weatherData Out[23]: {'city': {'coord': {'lat': 30.25, 'lon': 107.75}, 'country': 'CN', 'id': 1814905, 'name': 'Chongqing Shi', 'population': 0, 'sys': {'population': 0}}, 'cnt': 1, 'cod': '200', 'list': [{'clouds': {'all': 44}, 'dt': 1460775600, 'dt_txt': '2016-04-16 03:00:00', 'main': {'grnd_level': 937.55, 'humidity': 98, 'pressure': 937.55, 'sea_level': 1025.81, 'temp': 288.16, 'temp_kf': 0.4, 'temp_max': 288.16, 'temp_min': 287.759}, 'rain': {'3h': 0.01}, 'sys': {'pod': 'd'}, 'weather': [{'description': 'light rain', 'icon': '10d', 'id': 500, 'main': 'Rain'}], 'wind': {'deg': 267.501, 'speed': 1.63}}], 'message': 0.0109} #pylab.hist(temperature_list) pylab.plot(cnt_list,temperature_list,'ro') pylab.xlabel("times") pylab.ylabel('temperature') pylab.title("%s temperature prediction"%cityName) pylab.show() '''
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