我有以下代码来做到这一点，但我如何能做得更好?现在我认为它比嵌套循环更好，但是当您在列表理解中使用生成器时，它开始变得像perl一行程序。
day_count = (end_date - start_date).days + 1
for single_date in [d for d in (start_date + timedelta(n) for n in range(day_count)) if d <= end_date]:
print strftime("%Y-%m-%d", single_date.timetuple())
笔记
我不是用这个来打印的。这只是为了演示。
start_date和end_date变量是datetime。date对象，因为我不需要时间戳。(它们将用于生成报告)。
样例输出
开始日期为2009-05-30，结束日期为2009-06-09:
2009-05-30
2009-05-31
2009-06-01
2009-06-02
2009-06-03
2009-06-04
2009-06-05
2009-06-06
2009-06-07
2009-06-08
2009-06-09
下面是一个通用日期范围函数的代码，类似于Ber的答案，但更灵活:
def count_timedelta(delta, step, seconds_in_interval):
"""Helper function for iterate. Finds the number of intervals in the timedelta."""
return int(delta.total_seconds() / (seconds_in_interval * step))
def range_dt(start, end, step=1, interval='day'):
"""Iterate over datetimes or dates, similar to builtin range."""
intervals = functools.partial(count_timedelta, (end - start), step)
if interval == 'week':
for i in range(intervals(3600 * 24 * 7)):
yield start + datetime.timedelta(weeks=i) * step
elif interval == 'day':
for i in range(intervals(3600 * 24)):
yield start + datetime.timedelta(days=i) * step
elif interval == 'hour':
for i in range(intervals(3600)):
yield start + datetime.timedelta(hours=i) * step
elif interval == 'minute':
for i in range(intervals(60)):
yield start + datetime.timedelta(minutes=i) * step
elif interval == 'second':
for i in range(intervals(1)):
yield start + datetime.timedelta(seconds=i) * step
elif interval == 'millisecond':
for i in range(intervals(1 / 1000)):
yield start + datetime.timedelta(milliseconds=i) * step
elif interval == 'microsecond':
for i in range(intervals(1e-6)):
yield start + datetime.timedelta(microseconds=i) * step
else:
raise AttributeError("Interval must be 'week', 'day', 'hour' 'second', \
'microsecond' or 'millisecond'.")
> pip install DateTimeRange
from datetimerange import DateTimeRange
def dateRange(start, end, step):
rangeList = []
time_range = DateTimeRange(start, end)
for value in time_range.range(datetime.timedelta(days=step)):
rangeList.append(value.strftime('%m/%d/%Y'))
return rangeList
dateRange("2018-09-07", "2018-12-25", 7)
Out[92]:
['09/07/2018',
'09/14/2018',
'09/21/2018',
'09/28/2018',
'10/05/2018',
'10/12/2018',
'10/19/2018',
'10/26/2018',
'11/02/2018',
'11/09/2018',
'11/16/2018',
'11/23/2018',
'11/30/2018',
'12/07/2018',
'12/14/2018',
'12/21/2018']
在元组中存储范围参数的可逆步骤略有不同。
def date_range(start, stop, step=1, inclusive=False):
day_count = (stop - start).days
if inclusive:
day_count += 1
if step > 0:
range_args = (0, day_count, step)
elif step < 0:
range_args = (day_count - 1, -1, step)
else:
raise ValueError("date_range(): step arg must be non-zero")
for i in range(*range_args):
yield start + timedelta(days=i)
为什么有两个嵌套迭代?对我来说，它只用一次迭代就产生了相同的数据列表:
for single_date in (start_date + timedelta(n) for n in range(day_count)):
print ...
没有列表被存储，只有一个生成器被迭代。此外，生成器中的“if”似乎是不必要的。
毕竟，线性序列应该只需要一个迭代器，而不是两个。
与John Machin讨论后更新:
也许最优雅的解决方案是使用生成器函数来完全隐藏/抽象日期范围内的迭代:
from datetime import date, timedelta
def daterange(start_date, end_date):
for n in range(int((end_date - start_date).days)):
yield start_date + timedelta(n)
start_date = date(2013, 1, 1)
end_date = date(2015, 6, 2)
for single_date in daterange(start_date, end_date):
print(single_date.strftime("%Y-%m-%d"))
注意:为了与内置的range()函数保持一致，此迭代在到达end_date之前停止。因此，对于包容性迭代使用第二天，就像使用range()一样。
import datetime
from dateutil.rrule import DAILY,rrule
date=datetime.datetime(2019,1,10)
date1=datetime.datetime(2019,2,2)
for i in rrule(DAILY , dtstart=date,until=date1):
print(i.strftime('%Y%b%d'),sep='\n')
输出:
2019Jan10
2019Jan11
2019Jan12
2019Jan13
2019Jan14
2019Jan15
2019Jan16
2019Jan17
2019Jan18
2019Jan19
2019Jan20
2019Jan21
2019Jan22
2019Jan23
2019Jan24
2019Jan25
2019Jan26
2019Jan27
2019Jan28
2019Jan29
2019Jan30
2019Jan31
2019Feb01
2019Feb02
