def query_list_to_table(queries,
maxqlen=120,
output=False,
normalise_numbers=True,
**outputoptions):
"""Convert a django query list (list of dict with keys time and sql) into a table3
If output is non-False, output the table with the given options
Specify print, "print", or a stream for output to be printed immediately
"""
time = collections.defaultdict(list)
for q in queries:
query = q["sql"]
if normalise_numbers:
query = re.sub(r"\d+", "#", query)
# print(query)
time[query].append(float(q["time"]))
t = ObjectTable(rows=time.items())
t.add_column(lambda kv: len(kv[1]), "N")
t.add_column(lambda kv: kv[0][:maxqlen], "Query")
t.add_column(lambda kv: "%1.4f" % sum(kv[1]), "Cum.")
t.add_column(lambda kv: "%1.4f" % (sum(kv[1]) / len(kv[1])), "Avg.")
t = SortedTable(t, key=lambda row: row[2])
if output:
if "stream" not in outputoptions and output is not True:
if output in (print, "print"):
import sys
outputoptions["stream"] = sys.stdout
else:
outputoptions["stream"] = output
t.output(**outputoptions)
return t
def position_continuity(request):
time = {}
i = 0
positions = Position.objects.filter(
date__gte="2010-06-01").order_by("date")
while i < len(positions) - 1:
if positions[i].club_1 == positions[i + 1].club_1:
if positions[i].club_1 not in time:
time[positions[i].
club_1] = positions[i + 1].date - positions[i].date
else:
time[positions[i].
club_1] += positions[i + 1].date - positions[i].date
else:
if positions[i].club_1 not in time:
time[positions[i].club_1] = positions[
i +
1].date - positions[i].date - datetime.timedelta(days=1)
else:
time[positions[i].club_1] += positions[
i +
1].date - positions[i].date - datetime.timedelta(days=1)
i += 1
time_sorted = sorted(time.items(), key=lambda kv: -kv[1])
return render(request, "EloMain/old/top_places.html", locals())
def get_ave(time, ave_time):
for k, v in time.items():
length2 = len(v)
sum = 0
#print("length2:%d" % length2)
#print("v:%s" % v)
#v = [int(x) for x in v]
for a in v:
sum = sum + int(a[0]) * 600 + int(a[1]) * 60 + int(
a[2]) * 10 + int(a[3])
#print("sum:%d" % sum)
ave = int(sum / length2)
n1 = int(ave / 600)
#print("n1:%d" % n1)
s1 = ave % 600
#print("s1:%d" % s1)
n2 = int(s1 / 60)
#print("n2:%d" % n2)
s2 = s1 % 60
#print("s2:%d" % s2)
n3 = int(s2 / 10)
#print("n3:%d" % n3)
s3 = s2 % 10
#print("s3:%d" % s3)
last = str(n1) + str(n2) + str(n3) + str(s3)
#print("last:%s" % last)
ave_time[k] = last
def postreqtimejson(time):
for (k,v) in time.items():
tags = 'lua_reqt>1s:domain=' + k
value = v
counterType = 'GAUGE'
outdictdata.append(simpleMetric(ip,metric,ts,step,value,counterType,tags))
return outreqtimedata
def query_list_to_table(queries, maxqlen=120, output=False, normalise_numbers=True,
**outputoptions):
"""Convert a django query list (list of dict with keys time and sql) into a table3
If output is non-False, output the table with the given options
Specify print, "print", or a stream for output to be printed immediately
"""
time = collections.defaultdict(list)
for q in queries:
query = q["sql"]
if normalise_numbers:
query = re.sub(r"\d+", "#", query)
# print(query)
time[query].append(float(q["time"]))
t = ObjectTable(rows=time.items())
t.add_column(lambda kv: len(kv[1]), "N")
t.add_column(lambda kv: kv[0][:maxqlen], "Query")
t.add_column(lambda kv: "%1.4f" % sum(kv[1]), "Cum.")
t.add_column(lambda kv: "%1.4f" % (sum(kv[1]) / len(kv[1])), "Avg.")
t = SortedTable(t, key=lambda row: row[2])
if output:
if "stream" not in outputoptions and output is not True:
if output in (print, "print"):
import sys
outputoptions["stream"] = sys.stdout
else:
outputoptions["stream"] = output
t.output(**outputoptions)
return t
def get_continue_launch_count(strs, parm):
time = strs.split(":")
time = dict(Counter(time))
time = sorted(time.items(), key=lambda x: x[0], reverse=False)
key_list = []
value_list = []
if len(time) == 1:
return -2
for key, value in dict(time).items():
key_list.append(int(key))
value_list.append(int(value))
if np.mean(np.diff(key_list, 1)) == 1:
if parm == '1':
return np.mean(value_list)
elif parm == '2':
return np.max(value_list)
elif parm == '3':
return np.min(value_list)
elif parm == '4':
return np.sum(value_list)
elif parm == '5':
return np.std(value_list)
else:
return -1
def cur_day_repeat_count(strs):
time = strs.split(":")
time = dict(Counter(time))
time = sorted(time.items(), key=lambda x: x[1], reverse=False)
# 一天一次启动
if (len(time) == 1) & (time[0][1] == 1):
return 0
# 一天多次启动
elif (len(time) == 1) & (time[0][1] > 1):
return 1
# 多天多次启动
elif (len(time) > 1) & (time[0][1] >= 2):
return 2
else:
return 3
def Duration(duration):
time = re.compile('P'
'(?:(?P<years>\d+)Y)?'
'(?:(?P<months>\d+)M)?'
'(?:(?P<weeks>\d+)W)?'
'(?:(?P<days>\d+)D)?'
'(?:T'
'(?:(?P<hours>\d+)H)?'
'(?:(?P<minutes>\d+)M)?'
'(?:(?P<seconds>\d+)S)?'
')?').match(duration).groupdict()
for key in time.items():
time[key[0]] = 0 if key[1] is None else time[key[0]]
return (int(time["weeks"]) * 7 * 24 * 60 * 60) + (int(
time["days"]) * 24 * 60 * 60) + (int(time["hours"]) * 60 * 60) + (
int(time["minutes"]) * 60) + (int(time["seconds"]) - 1)
def read_from_str():
from web_flask.caculate.fetchduration import fetch
str_file = '/home/bf/Documents/Projects/helpplay/wait_time.data'
write_file = 'origin_data/disney_data_2'
with open(str_file,'r') as f:
with open(write_file,'a') as fw:
for line in f:
# python解析json的时候，只能解析双引号，false，true，null，必须注意json字符串的格式。
line = line.replace("'",'"').replace("False","false").replace("True","true").replace("None","null")
line_dict = json.loads(line)
time = fetch.get_now_data(raw_json = line_dict)
for key,value in time.items():
fw.write(key+','+str(value)+'\n')
def gettime_with_folders():
time = {}
res = all_comp_folders_from_db()
other_folders = []
for folder in res:
all_files=get_all_files(folder)
time[folder] = gettime(all_files)
tmp = 0
result_folder = ''
for item in time.items():
if item[1] > tmp:
tmp = item[1]
result_folder = item[0]
for item in time.keys():
if item != result_folder:
other_folders.append(item)
return (result_folder, tmp, other_folders)
def calculate_time(time):
'''
calculates average, maximum and minimum time elapsed.
Sends all these data to generate_report function
:param time: dictionary of commands as keys and elapsed time as values.
'''
total_time = 0
for k, v in time.items():
print(k, v)
total_time = total_time + v # calculate total time elapsed
key_max = max(time.keys(), key=(lambda k: time[
k])) # find the command which took maximum amount of time to execute
key_min = min(time.keys(), key=(lambda k: time[
k])) # find the command which took minimum amount of time to execute
avg = total_time / 8 # Calculate average amount of time
generate_report(time, key_max, key_min, avg, total_time)
def get_time(S, S2, squence):
time = {}
length = len(squence)
#print("squence:%s" % squence)
#print("length:%d" % length)
for i in range(length):
time[i] = []
#print("time:%s" % time)
for s1 in S:
#print("s1:%s" % s1)
count = 0
temp_time = {}
for s2 in s1:
#print("s2:%s" % s2)
#print("s2[0][0]:%s" % s2[0][0])
'''if s2[0][0] == squence[count][0]:####s2[0][0]解决原序列中有多个
temp_time[count]= s2[0][1:]
count += 1'''
for s3 in s2:
if s3[0] == squence[count][0]:
temp_time[count] = s3[1:]
count += 1
#print("count:%d" % count)
break
if count == length: ###全部符合就记录
for k, v in temp_time.items():
time[k].append(v)
#print("done")
#print("time:%s" % time)
break
#print("temp_time:%s" % temp_time)
for k, v in time.items():
time[k].sort() ##########排序
#print("time:%s" % time)
#S2.write("time:%s\n" % time)
ave_time = {}
get_ave(time, ave_time)
# print("ave_time:%s" % ave_time)
npprefix.prefix2.append(ave_time)
#S2.write("ave_time:%s\n" % ave_time)
recommend_time(time, ave_time) #np4.5
#print("time:%s" % time)
#S2.write("time:%s\n" % time)
###########################新时间
new_time = {}
for i in range(len(time)):
if (len(time[i]) >= 2):
#print((time[i][0]))
new_time[i] = []
new_time[i].append(time[i][0])
if (time[i][-1] != time[i][0]):
new_time[i].append(time[i][-1])
elif (len(time[i]) == 1):
new_time[i] = []
new_time[i].append(time[i][0][0] + time[i][0][1] + ':' +
time[i][0][2] + time[i][0][3])
else:
new_time[i] = ['无合适时间']
#############################新时间2
new_time2 = {}
for i in range(len(new_time)):
if (len(new_time[i]) == 2):
new_time2[i] = []
new_time2[i].append(new_time[i][0][0] + new_time[i][0][1] + ':' +
new_time[i][0][2] + new_time[i][0][3] + '-' +
new_time[i][1][0] + new_time[i][1][1] + ':' +
new_time[i][1][2] + new_time[i][1][3])
else:
new_time2[i] = new_time[i]
#new_time2[i] = []
#new_time2[i].append(new_time[i][0][0]+new_time[i][0][1]+':'+new_time[i][0][2]+new_time[i][0][3])
#print("推荐时间:%s" % new_time2)
S2.write("推荐时间:%s\n" % new_time2)
###################################
#print("____________________________________________")
S2.write("____________________________________________\n")
def rest_overtime(contract, datetime_day):
weekday = datetime_day.strftime("%w")
if weekday == "0":
weekday = str(6)
else:
weekday = str(int(weekday) - 1)
res = 0
active = 0
date_day = datetime.strftime(datetime_day,
DEFAULT_SERVER_DATE_FORMAT)
day = datetime_day.strftime(DEFAULT_SERVER_DATE_FORMAT)
holiday_ids = self.env['hr.holidays'].search([
('state', '=', 'validate'),
('employee_id', '=', contract.employee_id.id),
('type', '=', 'remove'), ('date_from', '<=', day),
('date_to', '>=', day)
])
if not holiday_ids:
sday = datetime.strftime(datetime_day, "%Y-%m-%d 00:00:00")
eday = datetime.strftime(datetime_day, "%Y-%m-%d 23:59:59")
attendance_ids = self.env['hr.attendance'].search(
[('employee_id', '=', contract.employee_id.id),
('check_in', '>=', sday), ('check_out', '<=', eday)],
order='check_in ASC')
time = {}
for work in contract.resource_calendar_id.attendance_ids:
if work.dayofweek == weekday and (
work.date_from == False or work.date_from <
date_day) and (work.date_to == False
or work.date_to > date_day):
if str(datetime_day +
timedelta(hours=work.hour_from)) not in time:
time[str(datetime_day +
timedelta(hours=work.hour_from))] = {
'start':
(datetime_day +
timedelta(hours=work.hour_from)),
'end': (datetime_day +
timedelta(hours=work.hour_to))
}
if time:
for attendance_id in attendance_ids:
attend = attendance_id
if attend.check_out:
y = 0.0
now = datetime.strptime(
attend.check_out,
DEFAULT_SERVER_DATETIME_FORMAT) + timedelta(
hours=3)
for key, value in sorted(time.items()):
start = value['start']
end = value['end']
for policy in contract.policy_id.line_ids:
starttime = (
day + " " + str(policy.starttime)
).strftime(DEFAULT_SERVER_DATETIME_FORMAT)
endtime = (
day + " " + str(policy.endtime)
).strftime(DEFAULT_SERVER_DATETIME_FORMAT)
if policy.type == 'restday':
active = policy.active_after
overtime = True
worked_hours = 0
if attend.check_in >= starttime and attend.check_in < start and attend.check_in <= endtime:
worked_hours += (
start -
attend.check_in).seconds / 60
if attend.check_out <= endtime and attend.check_out >= starttime and attend.check_out > end:
worked_hours += (attend.check_out -
end).seconds / 60
if worked_hours >= active:
res += worked_hours
return res
def execute(self, context):
time = readFile(self.filepath, self.dump_textures)
for k, v in time.items():
self.report({'INFO'},
'Time for ' + k + ': ' + str(v) + ' seconds.')
return {'FINISHED'}
def cvtDataForAPCA(sns_dict,
disp_sns_num,
trainig_range,
tmp_sns_num,
anomal_occur=0,
anomal_disp=0):
"""
Args :
sns_dict (dictionary) :
disp_sns_num (string or list) : sensor num where displacement data to be imported
training_range (int or float) : num of data to be used for training.
Ininitial count starts from the first idx
tmp_sns_num (string) : sensor num where temperature data to be imported
anomal_occur (int or float) : datetime when anomaly occurs
if not occur, it is set to zero.
anomal_disp (int or float) : displacement amount to be shifted from the original displacement
if it is set to None, the displacement will be fixed at anomal_occur
Returns :
op (dictionary) : Python data dictionary prepared for APCA
"""
disp_data_list = []
temp_data_list = []
ite = 0
for date, time in sns_dict[tmp_sns_num]['data'].items():
for time_, dir_ in time.items():
if ite > anomal_occur:
anomal_disp_ = anomal_disp
else:
anomal_disp_ = 0
try:
temp = dir_['temp']
except:
temp = None
try:
disp_list = []
for idx, sns_num in enumerate(disp_sns_num):
if sns_dict[sns_num]['disp_dir'] == 'Forward':
disp_list.append(-(
sns_dict[sns_num]['data'][date][time_]['x_disp'] +
anomal_disp_))
else:
disp_list.append(
sns_dict[sns_num]['data'][date][time_]['x_disp'] +
anomal_disp_)
except:
disp_list = None
if temp and disp_list:
ite += 1
temp_data_list.append(temp)
disp_data_list.append(disp_list)
op = {}
op['t'] = np.array(temp_data_list,
dtype=np.float32).squeeze()[:, np.newaxis].T
op['f'] = np.array(disp_data_list, dtype=np.float32).squeeze()
op['IND_x0'] = np.arange(0, trainig_range)
op['IND_x1'] = np.arange(trainig_range, len(disp_data_list))
return op
def get_time_with_zeros(time):
for key, value in time.items():
if value < 10:
time[key] = '0' + str(value)
return time
