def Quary_one(self,city,startdate):
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
onedata = dc.QuaryWeaData(city, startdate)
dc.closeDB()
if onedata == -1:
return 0
# 数据库无此数据
else:
list=[]
for index, item in enumerate(onedata):
dlist=[]
dlist.append(item[1][11:])
dlist.append(item[5])
dlist.append(str(item[2]))
dlist.append(item[3])
if item[4] == '-1' or item[4] == '0':
dlist.append('暂无数据')
else:
dlist.append(item[4])
dlist.append(item[6])
dlist.append(item[7])
list.append(dlist)
return list
else:
return -1
def Year_contrast(self, city):
today = datetime.datetime.now().strftime('%Y-%m-%d')
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
datam1 = dc.QuaryWeaDataSE(city, '2019-01-01', '2019-12-31')
datam2 = dc.QuaryWeaDataSE(city, '2020-01-01', '2020-12-31')
datam3 = dc.QuaryWeaDataSE(city, '2021-01-01', today)
list1 = []
list2 = []
list3 = []
for index, value in datam1.items():
dict = {}
dict['date'] = index
dict['max'] = value[0]
dict['min'] = value[1]
list1.append(dict)
for index, value in datam2.items():
dict = {}
dict['date'] = index
dict['max'] = value[0]
dict['min'] = value[1]
list2.append(dict)
for index, value in datam3.items():
dict = {}
dict['date'] = index
dict['max'] = value[0]
dict['min'] = value[1]
list3.append(dict)
list = []
list.append(list1)
list.append(list2)
list.append(list3)
dc.closeDB()
# not none
if list != []:
return list
else:
return 0
# 数据库无此数据
else:
return -1 # 数据库连接异常
def AverageTemp_Month(self, city):
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
yearlist = [2019, 2020, 2021]
monthlist = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]
today = datetime.datetime.now().strftime('%Y-%m-%d')
datelist = []
for y in yearlist:
datelist_y = []
for m in monthlist:
d = '-30'
#闰年
if ((y % 4 == 0 and y % 100 != 0) or
(y % 400 == 0)) and m == 2:
d = '-29'
elif m == 2:
d = '-28'
if m == 1 or m == 3 or m == 5 or m == 7 or m == 8 or m == 10 or m == 12:
d = '-31'
datelist_m = dc.getDatesByTimes(
str(y) + '-' + str(m) + '-01',
str(y) + '-' + str(m) + d)
datelist_y.append(datelist_m)
datelist.append(datelist_y)
avetemp_y = []
for y in datelist: #每年
avetemp_m = []
for m in y: #每月
datam = dc.QuaryWeaDataSETemp(city, m[0], m[-1])
if datam != -1:
average_a = np.mean(datam)
else:
average_a = 0
avetemp = round(average_a, 2)
avetemp_m.append(avetemp)
avetemp_y.append(avetemp_m)
dc.closeDB()
if avetemp_y != []:
return avetemp_y
else:
return 0
else:
return -1 # 数据库连接异常
# da = Data_Analyse()
# da.AverageTemp_Month('311')
def Login(self, id, pwd):
if id == '' or pwd == '':
return 0 # 帐号或密码不能为空
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
f = dc.login(id, pwd)
if f == 1:
return 1
elif f == -1:
return -1
# 密码错误
else:
return 2
#账户不存在
else:
return -2
def Quary_many(self,city, startdate, enddate):
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
datelist = dc.getDatesByTimes(startdate, enddate)
list = []
for time in datelist:
data = dc.QuaryWeaData(city, time)
dict = {}
if data != -1: # not none
temp = [t[2] for t in data]
temp.sort(reverse=True)
max = temp[0]
min = temp[len(temp) - 1]
wea = [w[5] for w in data]
wea = np.array(wea)
key = np.unique(wea)
result = {}
for k in key:#统计一天中各个天气类型的数量
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] = v
d_order = sorted(result.items(), key=lambda x: x[1], reverse=True)#排序
wea_1 = d_order[0][0]#一天中发生最多的天气状况
# 通过以下方法，确定一天的天气是什么：通过雨雪的权重大于雾霾大于晴阴多云实现
if len(d_order) > 1 and (d_order[0][0].find('晴') != -1 or d_order[0][0].find('多云') != -1 or d_order[0][0].find('阴') != -1):
if (d_order[1][0].find('雨') != -1 or d_order[1][0].find('雪') != -1) and d_order[1][1] > 3:
wea_1 = d_order[1][0]
elif (d_order[1][0].find('霾') != -1 or d_order[1][0].find('雾') != -1) and d_order[1][1] > 5:
wea_1 = d_order[1][0]
dict['date'] = str(time)
dict['weather'] = wea_1
dict['max'] = str(max)
dict['min'] = str(min)
list.append(dict)
dc.closeDB()
if list != []:# not none
return list
else:
return 0# 数据库无此数据
else:
return -1 # 数据库连接异常
def GetData(self):
print("开始获取数据集")
today = datetime.datetime.now().strftime('%Y-%m-%d')
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
self.list = []
# datelist = dc.getDatesByTimes('2019-01-01', today)
data = dc.QuaryWeaDataSE(self.city, '2019-01-01', today)
if data != -1:
for index, value in data.items():
list_one = []
list_one.append(value[0])
list_one.append(value[1])
list_one.append(value[2])
# print(list_one)
self.list.append(list_one)
dc.closeDB()
else:
return -1
def Quary_many(self, city, flag):
timelist = [30, 60]
today = datetime.datetime.now().strftime('%Y-%m-%d')
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
datelist = dc.date_add(today, timelist[flag - 1])
start = datelist[0]
datam = dc.QuaryWeaDataSE(city, start, today)
list = []
for index, value in datam.items():
dict = {}
dict['date'] = index
dict['max'] = value[0]
dict['min'] = value[1]
list.append(dict)
dc.closeDB()
# not none
if list != []:
return list
else:
return 0 # 数据库无此数据
else:
return -1 # 数据库连接异常
def Weather_type_days(self, city, flag):
timelist = [30, 60]
today = datetime.datetime.now().strftime('%Y-%m-%d')
today_last1 = today[:3] + '0' + today[4:]
today_last2 = today[:2] + '19' + today[4:]
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
datelist1 = dc.date_add(today, timelist[flag - 1])
datelist2 = dc.date_add(today_last1, timelist[flag - 1])
datelist3 = dc.date_add(today_last2, timelist[flag - 1])
weatype = dc.wealist
weatype = np.array(weatype)
key = np.unique(weatype)
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, datelist1[0], today)
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order1 = result
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, datelist2[0], today_last1)
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order2 = result
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, datelist3[0], today_last2)
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order3 = result
resultlist = []
resultlist.append(d_order1)
resultlist.append(d_order2)
resultlist.append(d_order3)
dc.closeDB()
# not none
if resultlist != []:
return resultlist
else:
return 0
else:
return -1 # 数据库连接异常
def Weather_type_year(self, city):
today = datetime.datetime.now().strftime('%Y-%m-%d')
dc = oper_database.ConnectDB()
if dc.Error_flag == 0:
datelist3 = dc.getDatesByTimes('2019-01-01', '2019-12-31')
datelist2 = dc.getDatesByTimes('2020-01-01', '2020-12-31')
datelist1 = dc.getDatesByTimes('2021-01-01', today)
weatype = dc.wealist
weatype = np.array(weatype)
key = np.unique(weatype)
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, '2021-01-01', today)
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order1 = result
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, '2020-01-01', '2020-12-31')
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order2 = result
result = {}
for k in key:
result[k] = 0
data1 = dc.QuaryWeaDataSEType(city, '2019-01-01', '2019-12-31')
if data1 != -1:
wea = np.array(data1)
for k in key:
mask = (wea == k)
list_new = wea[mask]
v = list_new.size
result[k] += v
d_order3 = result
resultlist = []
resultlist.append(d_order1)
resultlist.append(d_order2)
resultlist.append(d_order3)
dc.closeDB()
# not none
if resultlist != []:
return resultlist
else:
return 0
# 数据库无此数据
else:
return -1 # 数据库连接异常