一是先判断一下 key 是否存在,用 in 操作符: 二是使用dict本身提供的一个 get 方法,在Key不存在的时候,返回None: print d.get('Bart') #59 print d.get('Paul') #None 7、在字典中增添一个新元素的方法: d = { 'Adam': 95, 'Lisa': 85, ...
schedule.every().hour.do(greet,'John').tag('hourly-tasks','friend') schedule.every().hour.do(greet,'Monica').tag('hourly-tasks','customer') schedule.every().day.do(greet,'Derek').tag('daily-tasks','guest') friends = schedule.get_jobs...
"dayNum":"","contactHbPerplr":"无接触","toWh":"未去过/路过武汉","familySymptom":"无症状","remarks":"","otherDesc":"","backDate":"2020-02-12","jtgj":"自驾/步行","bc":"","addressOther":"","hbOther":"","familyOther":None,"lj":"是","ljOther":"","workStatus"...
like Gecko) Chrome/119.0.0.0 Safari/537.36',38}39response = requests.get(start_url,headers=headers).text40tree =etree.HTML(response)41datas = tree.xpath("/html/body/div[@class='main clearfix']/div[@class='main_left inleft']/div[@class='tian_...
from datetime import datetime class CountFee(APIView): def get(self, request, *args, **kwargs): # 获取当前时间的年月日,然后使用聚合函数添加fee字段的值 year = datetime.now().year month = datetime.now().month day = datetime.now().day count_fees = FeeDetail.objects.filter(addtime__year...
第3 节:用于 Web 开发的不同深度学习 API 入门 本节将说明 API 在软件开发中的一般用法,并说明如何使用不同的最新深度学习 API 来构建智能 Web 应用。 我们将涵盖自然语言处理(NLP)和计算机视觉等领域。 本节包括以下章节: “第 5 章”,“通过 API 进行深度学习” “第 6 章”,“使用 Python 在 Google...
checkTime 函数定义如下：defcheckTime(inputtime, day):try: intime = datetime.datetime.strptime("2019-" + inputtime, '%Y-%m-%d')except:return"时间转换失败" now = datetime.datetime.now() n_days = now - intime days = n_days.daysif days < day:returnTrueelse:returnFalse定义这个...
s = "农历:%d年%s%d月%d日" % (day.getLunarYear(False), '闰' if day.isLunarLeap() else '', day.getLunarMonth(), day.getLunarDay()) print(s) 1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 农历转阳历 import sxtwl # 如果查的是闰月,只要在第四个参数加一个true 如sxtwl.fromLunar(2020...
print('您的生日为:'+year+'年'+moon+'月'+day+'日') getbirth(ID_birth) def getsex(a): if int(a)%2==0: print('您的性别为:女') else : print('您的性别为:男') getsex(ID_sex) 3结语 针对使用函数实现解析身份证号码出生日期、性别问...
000 a day"] print("%-20s %s" % ("Query", "Best Match")) print("-" * 50) for query in ("feel good story", "climate change", "health", "war", "wildlife", "asia", "north america", "dishonest junk"): # Get index of best section that best matches query uid = ...