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

当前回答

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。

其他回答

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')

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

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)

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'.")

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