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

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。


这可能更清楚:

from datetime import date, timedelta

start_date = date(2019, 1, 1)
end_date = date(2020, 1, 1)
delta = timedelta(days=1)
while start_date <= end_date:
    print(start_date.strftime("%Y-%m-%d"))
    start_date += delta

import datetime

def daterange(start, stop, step=datetime.timedelta(days=1), inclusive=False):
  # inclusive=False to behave like range by default
  if step.days > 0:
    while start < stop:
      yield start
      start = start + step
      # not +=! don't modify object passed in if it's mutable
      # since this function is not restricted to
      # only types from datetime module
  elif step.days < 0:
    while start > stop:
      yield start
      start = start + step
  if inclusive and start == stop:
    yield start

# ...

for date in daterange(start_date, end_date, inclusive=True):
  print strftime("%Y-%m-%d", date.timetuple())

此函数通过支持负步长等功能,可以实现超出严格要求的功能。只要分解了范围逻辑,就不需要单独的day_count,最重要的是,当从多个地方调用函数时,代码变得更容易阅读。


使用dateutil库:

from datetime import date
from dateutil.rrule import rrule, DAILY

a = date(2009, 5, 30)
b = date(2009, 6, 9)

for dt in rrule(DAILY, dtstart=a, until=b):
    print dt.strftime("%Y-%m-%d")

这个python库有许多更高级的特性,其中一些非常有用,比如相对增量,并且被实现为单个文件(模块),很容易包含到项目中。


import datetime

def daterange(start, stop, step_days=1):
    current = start
    step = datetime.timedelta(step_days)
    if step_days > 0:
        while current < stop:
            yield current
            current += step
    elif step_days < 0:
        while current > stop:
            yield current
            current += step
    else:
        raise ValueError("daterange() step_days argument must not be zero")

if __name__ == "__main__":
    from pprint import pprint as pp
    lo = datetime.date(2008, 12, 27)
    hi = datetime.date(2009, 1, 5)
    pp(list(daterange(lo, hi)))
    pp(list(daterange(hi, lo, -1)))
    pp(list(daterange(lo, hi, 7)))
    pp(list(daterange(hi, lo, -7))) 
    assert not list(daterange(lo, hi, -1))
    assert not list(daterange(hi, lo))
    assert not list(daterange(lo, hi, -7))
    assert not list(daterange(hi, lo, 7)) 

for i in range(16):
    print datetime.date.today() + datetime.timedelta(days=i)

下面做一个按天递增的范围怎么样:

for d in map( lambda x: startDate+datetime.timedelta(days=x), xrange( (stopDate-startDate).days ) ):
  # Do stuff here

startDate和stopDate是datetime。日期对象

对于通用版本:

for d in map( lambda x: startTime+x*stepTime, xrange( (stopTime-startTime).total_seconds() / stepTime.total_seconds() ) ):
  # Do stuff here

startTime和stopTime是datetime。日期或datetime。datetime对象 (两者应是同一类型) stepTime是一个timedelta对象

注意.total_seconds()只在python 2.7之后才被支持。如果你被早期版本困住了,你可以写自己的函数:

def total_seconds( td ):
  return float(td.microseconds + (td.seconds + td.days * 24 * 3600) * 10**6) / 10**6

为什么不试试呢:

import datetime as dt

start_date = dt.datetime(2012, 12,1)
end_date = dt.datetime(2012, 12,5)

total_days = (end_date - start_date).days + 1 #inclusive 5 days

for day_number in range(total_days):
    current_date = (start_date + dt.timedelta(days = day_number)).date()
    print current_date

一般来说,Pandas非常适合时间序列,并直接支持日期范围。

import pandas as pd
daterange = pd.date_range(start_date, end_date)

然后你可以循环daterrange来打印日期:

for single_date in daterange:
    print (single_date.strftime("%Y-%m-%d"))

它也有很多选择,让生活更轻松。例如,如果您只想要工作日,您只需交换bdate_range。看到http://pandas.pydata.org/pandas-docs/stable/timeseries.html generating-ranges-of-timestamps

Pandas的强大之处在于它的数据框架,它支持向量化操作(很像numpy),使得跨大量数据的操作非常快速和简单。

编辑: 你也可以完全跳过for循环,直接打印出来,这样更简单、更高效:

print(daterange)

这个函数有一些额外的特性:

can pass a string matching the DATE_FORMAT for start or end and it is converted to a date object can pass a date object for start or end error checking in case the end is older than the start import datetime from datetime import timedelta DATE_FORMAT = '%Y/%m/%d' def daterange(start, end): def convert(date): try: date = datetime.datetime.strptime(date, DATE_FORMAT) return date.date() except TypeError: return date def get_date(n): return datetime.datetime.strftime(convert(start) + timedelta(days=n), DATE_FORMAT) days = (convert(end) - convert(start)).days if days <= 0: raise ValueError('The start date must be before the end date.') for n in range(0, days): yield get_date(n) start = '2014/12/1' end = '2014/12/31' print list(daterange(start, end)) start_ = datetime.date.today() end = '2015/12/1' print list(daterange(start, end))


显示从今天开始的最后n天:

import datetime
for i in range(0, 100):
    print((datetime.date.today() + datetime.timedelta(i)).isoformat())

输出:

2016-06-29
2016-06-30
2016-07-01
2016-07-02
2016-07-03
2016-07-04

Numpy的arange函数可以应用于日期:

import numpy as np
from datetime import datetime, timedelta
d0 = datetime(2009, 1,1)
d1 = datetime(2010, 1,1)
dt = timedelta(days = 1)
dates = np.arange(d0, d1, dt).astype(datetime)

astype的用途是从numpy转换。Datetime64到datetime数组。datetime对象。


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'.")

这是我能想到的最适合人类阅读的解决方案。

import datetime

def daterange(start, end, step=datetime.timedelta(1)):
    curr = start
    while curr < end:
        yield curr
        curr += step

我也有类似的问题,但我需要每月而不是每天迭代一次。

这就是我的解

import calendar
from datetime import datetime, timedelta

def days_in_month(dt):
    return calendar.monthrange(dt.year, dt.month)[1]

def monthly_range(dt_start, dt_end):
    forward = dt_end >= dt_start
    finish = False
    dt = dt_start

    while not finish:
        yield dt.date()
        if forward:
            days = days_in_month(dt)
            dt = dt + timedelta(days=days)            
            finish = dt > dt_end
        else:
            _tmp_dt = dt.replace(day=1) - timedelta(days=1)
            dt = (_tmp_dt.replace(day=dt.day))
            finish = dt < dt_end

示例# 1

date_start = datetime(2016, 6, 1)
date_end = datetime(2017, 1, 1)

for p in monthly_range(date_start, date_end):
    print(p)

输出

2016-06-01
2016-07-01
2016-08-01
2016-09-01
2016-10-01
2016-11-01
2016-12-01
2017-01-01

例# 2

date_start = datetime(2017, 1, 1)
date_end = datetime(2016, 6, 1)

for p in monthly_range(date_start, date_end):
    print(p)

输出

2017-01-01
2016-12-01
2016-11-01
2016-10-01
2016-09-01
2016-08-01
2016-07-01
2016-06-01

您可以简单而可靠地使用pandas库在两个日期之间生成一系列日期

import pandas as pd

print pd.date_range(start='1/1/2010', end='1/08/2018', freq='M')

您可以通过设置“freq”为D, M, Q, Y来改变生成日期的频率 (每天,每月,每季,每年 )


> 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)

为了完整起见,Pandas还有一个period_range函数用于时间戳越界:

import pandas as pd

pd.period_range(start='1/1/1626', end='1/08/1627', freq='D')

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

from datetime import date,timedelta
delta = timedelta(days=1)
start = date(2020,1,1)
end=date(2020,9,1)
loop_date = start
while loop_date<=end:
    print(loop_date)
    loop_date+=delta

使用pendulum.period:

import pendulum

start = pendulum.from_format('2020-05-01', 'YYYY-MM-DD', formatter='alternative')
end = pendulum.from_format('2020-05-02', 'YYYY-MM-DD', formatter='alternative')

period = pendulum.period(start, end)

for dt in period:
    print(dt.to_date_string())

对于那些对python函数方式感兴趣的人:

from datetime import date, timedelta
from itertools import count, takewhile

for d in takewhile(lambda x: x<=date(2009,6,9), map(lambda x:date(2009,5,30)+timedelta(days=x), count())):
    print(d)

你可以使用箭头:

这是一个来自文档的例子,在几个小时内迭代:

from arrow import Arrow

>>> start = datetime(2013, 5, 5, 12, 30)
>>> end = datetime(2013, 5, 5, 17, 15)
>>> for r in Arrow.range('hour', start, end):
...     print repr(r)
...
<Arrow [2013-05-05T12:30:00+00:00]>
<Arrow [2013-05-05T13:30:00+00:00]>
<Arrow [2013-05-05T14:30:00+00:00]>
<Arrow [2013-05-05T15:30:00+00:00]>
<Arrow [2013-05-05T16:30:00+00:00]>

要在几天内迭代,你可以这样使用:

>>> start = Arrow(2013, 5, 5)
>>> end = Arrow(2013, 5, 5)
>>> for r in Arrow.range('day', start, end):
...     print repr(r)

(没有检查你是否能通过datetime。日期对象,但无论如何箭头对象通常更容易)


如果你打算使用动态timedelta,那么你可以使用:

1. 使用while循环

def datetime_range(start: datetime, end: datetime, delta: timedelta) -> Generator[datetime, None, None]:
    while start <= end:
        yield start
        start += delta

2. 使用for循环

from datetime import datetime, timedelta
from typing import Generator


def datetime_range(start: datetime, end: datetime, delta: timedelta) -> Generator[datetime, None, None]:
    delta_units = int((end - start) / delta)

    for _ in range(delta_units + 1):
        yield start
        start += delta

3.如果你正在使用async/await

async def datetime_range(start: datetime, end: datetime, delta: timedelta) -> AsyncGenerator[datetime, None]:
    delta_units = int((end - start) / delta)

    for _ in range(delta_units + 1):
        yield start
        start += delta

4. 列表理解

def datetime_range(start: datetime, end: datetime, delta: timedelta) -> List[datetime]:
    delta_units = int((end - start) / delta)
    return [start + (delta * index) for index in range(delta_units + 1)]

那么1和2解可以简单地像这样使用

start = datetime(2020, 10, 10, 10, 00)
end = datetime(2022, 10, 10, 18, 00)
delta = timedelta(minutes=30)

result = [time_part for time_part in datetime_range(start, end, delta)]
# or 
for time_part in datetime_range(start, end, delta):
    print(time_part)

3- 3 / 3解决方案可以在异步上下文中使用。因为它运行一个异步生成器对象,该对象只能在异步上下文中使用

start = datetime(2020, 10, 10, 10, 00)
end = datetime(2022, 10, 10, 18, 00)
delta = timedelta(minutes=30)

result = [time_part async for time_part in datetime_range(start, end, delta)]

async for time_part in datetime_range(start, end, delta):
    print(time_part)

这些解决方案的优点是它们都使用了动态的timedelta。这在你不知道你将得到哪个时间增量的情况下非常有用。