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。

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

> 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']

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'.")

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