eryksun wrote:
> On Sun, Jul 29, 2012 at 7:21 AM, Peter Otten <__pete...@web.de> wrote:
>>
>> If you don't have to deal with large datasets many of its functions can
>> easily be emulated with lists and loops though. As an example here's the
>> grouping with a plain vanilla dict:
>>
>> groups = {}
>> for item in data:
>> groups.setdefault(item[:4], []).append(item[-2:])
>>
>> result = [key + tuple("{}/{}".format(*v) for v in values) for key, values
>> in groups.items()]
>
> Or use a defaultdict:
>
> from collections import defaultdict
Yes, I would have used that, but I wanted to show that there was a
reasonable solution that did not rely on any libraries.
> groups = defaultdict(list)
> for item in data:
> groups[item[:4]].append(item[4:])
>
> result = []
> for key in sorted(groups):
> groups[key].sort()
> result.append(key + tuple('%s/%s' % v[1:] for v in groups[key]))
If you have to sort your data anyway you can sort it first and then apply
itertools.groupby()...
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