def query_weather(code): # 模板网页 html = f'http:///weather_mini?citykey={code}' # 向网页发起请求 try: info = requests.get(html) info.encoding = 'utf-8' # 捕获 ConnectinError 异常 except requests.ConnectionError: raise # 将获取的数据转换为 json 格式 try: info_json = info.json(...
weather_dict.get('data').get('wendu')+'℃ ')print('感冒:',weather_dict.get('data').get('ganmao'))print('风向:',forecast[0].get('fengxiang'))print('风级:',forecast[0].get('fengli'))print('高温:',forecast[0].get('high'))print('低温...
citycode = city[cityname] url = 'http://wthrcdn.etouch.cn/weather_mini?citykey=%s'%citycode # print('城市:{},编号:{}'.format(cityname,citycode)) # print(url) res = requests.get(url) info = res.json() # print(info) data = info['data'] weatherItems = data['forecast'] today...
1#打印各项数据2print('城市:',weather['city'])3print('当前温度',weather['wendu'] +'℃')4print('提示',weather['ganmao'])56forxinweather['forecast']:7print(x['date'],x['type'],x['high'],x['low'],x['fengxiang']) 整个运行下,得到的结果就是: 完成。其实里面还有一项数据我没有打...
weather_forecast = soup.find('span', class_='phrase').text print(f"Weather forecast for {city}: {weather_forecast}") else: print("Error:", response.status_code, response.text) city = "Shanghai" get_weather(city) 详细解释 安装必要的库:使用pip install requests beautifulsoup4命令安装requests...
#https://wis.qq.com/weather/common?source=pc&weather_type=observe%7Cforecast_1h%7Cforecast_24h%7Cindex%7Calarm%7Climit%7Ctips%7Crise&province=江苏省&city=徐州市 我们所用到的库有: import requests # http请求库 import re # 正则表达式库 ...
为查询按钮设置快捷键: def keyPressEvent(self, e): # 设置快捷键 if e.key() == Qt.Key_Return: self.queryWeather() 最后,我们可以使用 pyinstaller -w weather.py 打包应用程序,但是要记得打包完,将 city_code.txt 复制到 dist/weather 文件夹下,否则程序无法运行。 以上便是本文的全部内容了。编辑...
def get_weather(url):r=requests.get(url)data=json.loads(r.text)city = data['cityInfo']['city']weather=data['data']['forecast']return city,weather def get_content_send(city,weather):all_day=[]content_send=""for i in range(0,6,1):content=weather[i]every_day=[]every_day.append(...
Forecasting weather conditions is important for, e.g., operation of hydro power plants and for flood management. Mechanistic models are known to be computationally demanding. Hence, it is of interest to develop models that can predict weather conditions faster than traditional meteorological models. ...
File "C:\Users\Denver\Desktop\Plot_weather_Temp.py", line 73, in ax.xaxis.label.set_color(labelColor)NameError: name 'labelColor' is not defined[Finished in 10.1s with exit code 1][shell_cmd: python -u "C:\Users\Denver\Desktop\Plot_weather_Temp.py"][dir: C:\Users\Denver\Deskto...