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copied!<pre><code>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)) </code></pre> <p>yields</p> <pre><code># (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')]) </code></pre> <p>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 <code>start_date</code> (to something like 2008-5-16).</p> <p>PS. The key tool used above is <code>itertools.groupby</code>, which is explained in detail <a href="http://docs.python.org/library/itertools.html#itertools.groupby" rel="noreferrer">here</a>.</p> <p>Edit: The <code>lambda</code>s are simply a way to make <a href="http://docs.python.org/reference/expressions.html#lambda" rel="noreferrer">"anonymous" functions</a>. (They are anonymous in the sense that they are not given names like functions defined by <code>def</code>). Anywhere you see a lambda, it is also possible to use a <code>def</code> to create an equivalent function. For example, you could do this:</p> <pre><code>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)) </code></pre>

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