将在任意时间范围内的任意日期对象组合在一起 [英] Group together arbitrary date objects that are within a time range of each other

问题描述

我想将日历分为两个星期，从 2008-May-5 或任意起点开始。

I want to split the calendar into two-week intervals starting at 2008-May-5, or any arbitrary starting point.

所以我从几个日期对象开始：

So I start with several date objects:

import datetime as DT

raw = ("2010-08-01",
       "2010-06-25",
       "2010-07-01",
       "2010-07-08")

transactions = [(DT.datetime.strptime(datestring, "%Y-%m-%d").date(),
                 "Some data here") for datestring in raw]
transactions.sort()

通过手动分析日期，我很清楚日期在相同的两周间隔内。我想得到类似于这样的分组：

By manually analyzing the dates, I am quite able to figure out which dates fall within the same fortnight interval. I want to get grouping that's similar to this one:

# Fortnight interval 1
(datetime.date(2010, 6, 25), 'Some data here')
(datetime.date(2010, 7, 1), 'Some data here')
(datetime.date(2010, 7, 8), 'Some data here')

# Fortnight interval 2
(datetime.date(2010, 8, 1), 'Some data here')

推荐答案

import datetime as DT
import itertools

start_date=DT.date(2008,5,5)

def mkdate(datestring):
    return DT.datetime.strptime(datestring, "%Y-%m-%d").date()

def fortnight(date):
    return (date-start_date).days //14

raw = ("2010-08-01",
       "2010-06-25",
       "2010-07-01",
       "2010-07-08")
transactions=[(date,"Some data") for date in map(mkdate,raw)]
transactions.sort(key=lambda (date,data):date)

for key,grp in itertools.groupby(transactions,key=lambda (date,data):fortnight(date)):
    print(key,list(grp))

< （55，[（datetime.date（2010，6，25），'Some data'）]

yields

# (55, [(datetime.date(2010, 6, 25), 'Some data')])
# (56, [(datetime.date(2010, 7, 1), 'Some data'), (datetime.date(2010, 7, 8), 'Some data')])
# (58, [(datetime.date(2010, 8, 1), 'Some data')])

$ b $请注意，2010-6-25是2008-5-5第55周，而2010-7-1是第56。如果您希望将它们分组在一起，只需更改 start_date （如2008-5-16）。

Note that 2010-6-25 is in the 55th fortnight from 2008-5-5, while 2010-7-1 is in the 56th. If you want them grouped together, simply change start_date (to something like 2008-5-16).

PS 。上面使用的关键工具是 itertools.groupby ，详细说明 here 。

PS. The key tool used above is itertools.groupby, which is explained in detail here.

编辑： lambda 匿名功能的方法。 （他们是匿名的，因为他们没有给出名称，例如由 def 定义的功能）。任何地方你看到一个lambda，也可以使用 def 创建一个等效的功能。例如，您可以这样做：

The lambdas are simply a way to make "anonymous" functions. (They are anonymous in the sense that they are not given names like functions defined by def). Anywhere you see a lambda, it is also possible to use a def to create an equivalent function. For example, you could do this:

import operator
transactions.sort(key=operator.itemgetter(0))

def transaction_fortnight(transaction):
    date,data=transaction
    return fortnight(date)

for key,grp in itertools.groupby(transactions,key=transaction_fortnight):
    print(key,list(grp))

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