# [Baypiggies] hello and returning unique elements

Tung Wai Yip tungwaiyip at yahoo.com
Fri Apr 8 20:16:58 CEST 2011

```I've put my previous suggestion into an example. It is similar to many
other suggestions except it is 2 lines of code (by using a newer tool in
the standard library).

>>> countdict = collections.Counter('abcdeabcxyz')
>>> [v for v,c in countdict.items() if c > 1]
['a', 'c', 'b']

This should be O(N).

Wai Yip

On Fri, 08 Apr 2011 10:49:23 -0700, Tim Hatch <tim at timhatch.com> wrote:

> By some quick experiments, it looks like you can double the speed from
> your version by not doing all the reversed/sorted stuff and just keeping
> track of it in a much less exciting way:
>
> def unique2(seq):
>   seen = set()
>   out = []
>   for i in seq:
>     if i not in seen:
>       out.append(i)
>   return out
>
> # yours
> \$ python -m timeit -s 'from demo import unique' 'sum(unique([1, 1, 2, 3,
> 4]))'
> 100000 loops, best of 3: 5.07 usec per loop
> # mine
> \$ python -m timeit -s 'from demo import unique2' 'sum(unique2([1, 1, 2,
> 3,
> 4]))'
> 100000 loops, best of 3: 2.65 usec per loop
>
> You can actually make it a smidge faster still by making it a generator,
> for at least this tiny case (as it becomes bigger, into the thousands of
> items, it's much more like unique2's timings):
>
> def unique3(seq):
>   seen = set()
>   for i in seq:
>     if i not in seen:
>       yield i
>
> \$ python -m timeit -s 'from demo import unique3' 'sum(unique3([1, 1, 2,
> 3,
> 4]))'
> 1000000 loops, best of 3: 1.99 usec per loop
>
> Tim
>
>> Erratum: the function I suggested is incomplete without this line
>> following the docstring.
>>
>> if seq is None: return None
>>
>>
>> On Thu, Apr 7, 2011 at 6:42 PM, Hy Carrinski <hcarrinski at gmail.com>
>> wrote:
>>> Dear BayPIGgies,
>>>
>>> Thank you for providing exceptional reading material over the past
>>> year for an avid conversation follower and occasional meeting
>>> attendee.
>>>
>>> I would like to join the conversation and contribute to the community
>>> beginning with this post. I will attend our meeting this month, and
>>> look forward to meeting at Noisebridge or elsewhere to watch PyCon
>>> 2011 videos together.
>>>
>>> While thinking about unique lists in the context of Vikram's recent
>>> question, I came across a related blog post at
>>> http://www.peterbe.com/plog/uniqifiers-benchmark
>>>
>>> The post emphasizes speed and maintaining original list order when
>>> removing duplicates from a list.
>>>
>>> Although the post is several years old, I thought of a solution to the
>>> question it poses that is different from the ones proposed by
>>> BayPIGgies either in the blog's comments or at a previous discussion
>>> (before reversed, sorted, and set were introduced in Python 2.4) at
>>> http://code.activestate.com/recipes/52560/
>>>
>>> I will be grateful for any comments on my ask forgiveness rather than
>>> permission implementation. It requires that all elements of the list
>>> be hashable and works for Python 2.x where x >= 4.
>>>
>>> def unique(seq):
>>> Â  Â """Return unique list of hashable objects while preserving
>>> order."""
>>> Â  Â seen = {}
>>> Â  Â for ix in reversed(xrange(len(seq))):
>>> Â  Â  Â  Â seen[seq[ix]] = ix
>>> Â  Â return sorted(seen,key=seen.__getitem__)
>>>
>>> For the case of hashable objects are there disadvantages to this
>>> implementation versus the ones referenced above? Is there a reason to
>>> prefer operator.itemgetter over __getitem__ in this limited context?
>>> Is there an advantage in clarity or performance to using
>>> collections.OrderedDict in Python 2.7 and above? For lists containing
>>> a great number of distinct objects the sort step will introduce a
>>> lower bound on speed for this implementation.
>>>
>>> I look forward to meeting more BayPIGgies in the coming months and
>>> years.
>>>
>>> Cheers,
>>> Hy
>>>
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>
>
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```