1. 原因：使用dateutil的rrule時，計算速度比較慢
def axx():
from dateutil import rrule
received_time = datetime.datetime.strptime('2019-04-21 23:00:00', '%y-%m-%d %h:%m:%s')
complete_time = datetime.datetime.strptime('2019-04-22 01:00:00', '%y-%m-%d %h:%m:%s')
workdays = [x for x in range(7) if x not in [5, 6]]
time_period = rrule.rrule(rrule.minutely, dtstart=received_time, until=complete_time, byweekday=workdays).count()
print(time_period)
def xxa():
import pandas as pd
date = pd.bdate_range('2019-04-21 23:00:00', '2019-04-22 01:00:00', freq='min')
minutes = len(date)
print(minutes)
print(minutes/(60*60))
def xax():
from business_duration import businessduration
import pandas as pd
received_time = pd.to_datetime('2019-04-21 23:00:00')
complete_time = pd.to_datetime('2019-04-22 01:15:00')
period = businessduration(received_time, complete_time, unit='min')
print(period)
def aaa():
import pandas as pd
# test case 1
# received_time = '2019-04-21 23:00:00'
# complete_time = '2019-04-22 01:00:00'
# received_time = '2019-04-19 23:00:00'
# complete_time = '2019-04-20 01:00:00'
# test case 2
# received_time = '2019-04-18 23:00:00'
# complete_time = '2019-04-20 01:00:00'
# received_time = '2019-04-21 23:00:00'
# complete_time = '2019-04-23 01:00:00'
# test case 3
# received_time = '2019-04-21 23:00:00'
# complete_time = '2019-04-24 01:00:00'
# received_time = '2019-04-18 23:00:00'
# complete_time = '2019-04-20 01:00:00'
# test case 5
received_time = '2019-04-19 23:00:00'
complete_time = '2019-04-22 01:00:00'
received_date = pd.to_datetime(received_time)
complete_date = pd.to_datetime(complete_time)
date_period = pd.bdate_range(received_time, complete_time)
if date_period[0] == date_period[-1]:
if date_period[0] > received_date:
start = date_period[0]
end = complete_date
else:
start = received_date
end = date_period[0] + datetime.timedelta(days=1)
day_time = len(pd.date_range(start, end, freq='min')) - 1
print('workdays:' + str(day_time) + ' minutes')
else:
if (complete_date - date_period[-1]).days > 0:
end = date_period[-1] + datetime.timedelta(days=1)
else:
end = complete_date
if received_date < date_period[0]:
start = date_period[0]
else:
start = received_date
received_per = pd.date_range(start, date_period[0] + datetime.timedelta(days=1), freq='min')
complete_per = pd.date_range(date_period[-1], end, freq='min')
middle_time = (len(date_period) - 2) * 1440
days_time = len(received_per) + middle_time + len(complete_per) - 2
print('workdays:' + str(days_time) + ' minutes')
近兩日工作
將xhtml樹進行了簡單修改做成了乙個展示頁面，沒有摸索連線資料庫的功能，打算以後將其自帶的php mysql例子改造成 jsp的。有關資料庫的設計看到cl和gm如此嫻熟的進行設計，真是感慨如潮啊，需要思考的東西和模式有很多，乙個硬幣可以看成n面的啊！今天下午去聽了css講座，收穫頗多，這種培訓果然...
Python計算兩個日期之間天數
有的時候要統計兩個日期之間的相距天數，可能有很多種方法，但使用datetime模組的datetime方法無疑是裡面比較簡單的，具體 如下 import datetime d1 datetime.datetime 2018,10,31 第乙個日期 d2 datetime.datetime 2019,0...
計算兩個日期之間的工作日數
計算兩個日期之間的工作日數,星期6，星期天，不算工作日 dt1和dt2之間相隔多少工作日，其中dt3 dt4的時間為公休日，這裡公休日可以用以個陣列，或者從乙個xml表裡面讀取，以便扣除 要計算的起始時間 要計算的結束時間 公休起始時間 公休結束時間 intreturn private int di...