本文主要介绍了使用python遍历指定城市的一周气温的实现方法。具有很好的参考价值，下面跟着小编一起来看下吧
处于兴趣，写了一个遍历指定城市五天内的天气预报，并转为华氏度显示。
把城市名字写到一个列表里这样可以方便的添加城市。并附有详细注释
import requests
import json
#定义一个函数 避免代码重写多次。
def gettemp(week,d_or_n,date):
wendu=data['result']['weather'][week]['info'][d_or_n][date] #对字典进行拆分
return int(wendu)
def getft(t):
ft=t*1.8+32
return float(str(ft)[0:4])
cities=['保定','北京','上海','武汉','郑州','齐齐哈尔'] #这里可以指定想要遍历的城市
url='http://api.avatardata.cn/Weather/Query?key=68e75677978441f6872c1106175b8673&cityname=' #用于和cities里的城市进行字符串拼接
low=0
high=2
for city in cities:
r = requests.get(url+city) # 最基本的GET请求
#print(r.status_code) 获取返回状态200是成功
#print(r.text) 打印解码后的返回数据
data=json.loads(r.text) #返回的json数据被转换为字典类型
#print(type(data)) data 的数据类型是字典 所以可以按照字典操作（字典里的列表就按列表操作）
print(city,'近五天天气预报：')
for i in range(5):
week='周'+str(data['result']['weather'][i]['week']) #对字典类型进行逐个拆分 如列表 元组等。
daylow=gettemp(i,'day',low)
dlf=getft(daylow)
dayhigh=gettemp(i,'day',high)
dhf=getft(dayhigh)
nightlow=gettemp(i,'night',low)
nlf=getft(nightlow)
nighthigh=gettemp(i,'night',high)
nhf=getft(nighthigh)
print(week,'白天气温:',daylow,'~',dayhigh,'摄氏度','晚上气温:',nightlow,'~',nighthigh,'摄氏度')
print(' ','白天气温:',dlf,'~',dhf,'华氏度','晚上气温:',nlf,'~',nhf,'华氏度')
print('\n')
{"result":{"realtime":{"wind":{"windspeed":null,"direct":"西风","power":"3级","offset":null},"time":"16:00:00","weather":{"humidity":"27","img":"0","info":"晴","temperature":"13"},"dataUptime":"1490517362","date":"2017-03-26","city_code":"101090201","city_name":"保定","week":"0","moon":"二月廿九"},"life":{"date":"2017-3-26","info":{"kongtiao":["开启制暖空调","您将感到有些冷，可以适当开启制暖空调调节室内温度，以免着凉感冒。"],"yundong":["较适宜","天气较好，但考虑风力较强且气温较低，推荐您进行室内运动，若在户外运动注意防风并适当增减衣物。"],"ziwaixian":["中等","属中等强度紫外线辐射天气，外出时建议涂擦SPF高于15、PA+的防晒护肤品，戴帽子、太阳镜。"],"ganmao":["较易发","昼夜温差较大，较易发生感冒，请适当增减衣服。体质较弱的朋友请注意防护。"],"xiche":["较适宜","较适宜洗车，未来一天无雨，风力较小，擦洗一新的汽车至少能保持一天。"],"wuran":null,"chuanyi":["冷","天气冷，建议着棉服、羽绒服、皮夹克加羊毛衫等冬季服装。年老体弱者宜着厚棉衣、冬大衣或厚羽绒服。"]}},"weather":[{"date":"2017-03-26","week":"日","nongli":"二月廿九","info":{"dawn":null,"day":["0","晴","17","西北风","3-4 级","06:12"],"night":["0","晴","2","西南风","微风","18:36"]}},{"date":"2017-03-27","week":"一","nongli":"二月三十","info":{"dawn":["0","晴","2","西南风","微风","18:36"],"day":["0","晴","15","南风","微风","06:11"],"night":["7","小雨","3","南风","微风","18:37"]}},{"date":"2017-03-28","week":"二","nongli":"三月初一","info":{"dawn":["7","小雨","3","南风","微风","18:37"],"day":["1","多云","15","南风","微风","06:09"],"night":["0","晴","3","南风","微风","18:38"]}},{"date":"2017-03-29","week":"三","nongli":"三月初二","info":{"dawn":["0","晴","3","南风","微风","18:38"],"day":["0","晴","18","南风","微风","06:08"],"night":["0","晴","3","北风","微风","18:39"]}},{"date":"2017-03-30","week":"四","nongli":"三月初三","info":{"dawn":["0","晴","3","北风","微风","18:39"],"day":["0","晴","17","北风","微风","06:06"],"night":["0","晴","3","北风","微风","18:40"]}}],"pm25":{"key":"Baoding","show_desc":"0","pm25":{"curPm":"34","pm25":"14","pm10":"26","level":"1","quality":"优","des":"空气很好，可以外出活动"},"dateTime":"2017年03月26日16时","cityName":"保定"},"isForeign":0},"error_code":0,"reason":"Succes"}
这是返回的一个json数据，可以通过json格式化工具查看会方便一些，通过json.loads其实都是字典列表的一些嵌套，而想要取的数据 在字典里"result"里， 而data['result'] 又是一个字典，
{'life': {'date': '2017-3-26', 'info': {'yundong': ['较适宜', '天气较好，但考虑风力较强且气温较低，推荐您进行室内运动，若在户外运动注意防风并适当增减衣物。'], 'xiche': ['较适宜', '较适宜洗车，未来一天无雨，风力较小，擦洗一新的汽车至少能保持一天。'], 'ganmao': ['较易发', '昼夜温差较大，较易发生感冒，请适当增减衣服。体质较弱的朋友请注意防护。'], 'ziwaixian': ['中等', '属中等强度紫外线辐射天气，外出时建议涂擦SPF高于15、PA+的防晒护肤品，戴帽子、太阳镜。'], 'chuanyi': ['冷', '天气冷，建议着棉服、羽绒服、皮夹克加羊毛衫等冬季服装。年老体弱者宜着厚棉衣、冬大衣或厚羽绒服。'], 'wuran': None, 'kongtiao': ['开启制暖空调', '您将感到有些冷，可以适当开启制暖空调调节室内温度，以免着凉感冒。']}}, 'weather': [{'date': '2017-03-26', 'week': '日', 'info': {'dawn': None, 'night': ['0', '晴', '2', '西南风', '微风', '18:36'], 'day': ['0', '晴', '17', '西北风', '3-4 级', '06:12']}, 'nongli': '二月廿九'}, {'date': '2017-03-27', 'week': '一', 'info': {'dawn': ['0', '晴', '2', '西南风', '微风', '18:36'], 'night': ['7', '小雨', '3', '南风', '微风', '18:37'], 'day': ['0', '晴', '15', '南风', '微风', '06:11']}, 'nongli': '二月三十'}, {'date': '2017-03-28', 'week': '二', 'info': {'dawn': ['7', '小雨', '3', '南风', '微风', '18:37'], 'night': ['0', '晴', '3', '南风', '微风', '18:38'], 'day': ['1', '多云', '15', '南风', '微风', '06:09']}, 'nongli': '三月初一'}, {'date': '2017-03-29', 'week': '三', 'info': {'dawn': ['0', '晴', '3', '南风', '微风', '18:38'], 'night': ['0', '晴', '3', '北风', '微风', '18:39'], 'day': ['0', '晴', '18', '南风', '微风', '06:08']}, 'nongli': '三月初二'}, {'date': '2017-03-30', 'week': '四', 'info': {'dawn': ['0', '晴', '3', '北风', '微风', '18:39'], 'night': ['0', '晴', '3', '北风', '微风', '18:40'], 'day': ['0', '晴', '17', '北风', '微风', '06:06']}, 'nongli': '三月初三'}], 'isForeign': 0, 'pm25': {'pm25': {'des': '空气很好，可以外出活动', 'curPm': '34', 'level': '1', 'pm10': '26', 'pm25': '14', 'quality': '优'}, 'show_desc': '0', 'key': 'Baoding', 'dateTime': '2017年03月26日16时', 'cityName': '保定'}, 'realtime': {'city_name': '保定', 'weather': {'info': '晴', 'img': '0', 'humidity': '27', 'temperature': '13'}, 'week': '0', 'wind': {'windspeed': None, 'power': '3级', 'offset': None, 'direct': '西风'}, 'city_code': '101090201', 'date': '2017-03-26', 'dataUptime': '1490517362', 'time': '16:00:00', 'moon': '二月廿九'}}
相同的方法取 data['result']['weather'] 这又是一个元组，
[{'nongli': '二月廿九', 'info': {'night': ['0', '晴', '2', '西南风', '微风', '18:36'], 'dawn': None, 'day': ['0', '晴', '17', '西北风', '3-4 级', '06:12']}, 'week': '日', 'date': '2017-03-26'}, {'nongli': '二月三十', 'info': {'night': ['7', '小雨', '3', '南风', '微风', '18:37'], 'dawn': ['0', '晴', '2', '西南风', '微风', '18:36'], 'day': ['0', '晴', '15', '南风', '微风', '06:11']}, 'week': '一', 'date': '2017-03-27'}, {'nongli': '三月初一', 'info': {'night': ['0', '晴', '3', '南风', '微风', '18:38'], 'dawn': ['7', '小雨', '3', '南风', '微风', '18:37'], 'day': ['1', '多云', '15', '南风', '微风', '06:09']}, 'week': '二', 'date': '2017-03-28'}, {'nongli': '三月初二', 'info': {'night': ['0', '晴', '3', '北风', '微风', '18:39'], 'dawn': ['0', '晴', '3', '南风', '微风', '18:38'], 'day': ['0', '晴', '18', '南风', '微风', '06:08']}, 'week': '三', 'date': '2017-03-29'}, {'nongli': '三月初三', 'info': {'night': ['0', '晴', '3', '北风', '微风', '18:40'], 'dawn': ['0', '晴', '3', '北风', '微风', '18:39'], 'day': ['0', '晴', '17', '北风', '微风', '06:06']}, 'week': '四', 'date': '2017-03-30'}]
接着取元组里的字典，逐步拆分即可获得想要的数据。 
