Maintaining the order of the elements in a frozen set

落爺英雄遲暮 提交于 2019-12-03 19:43:46

Instead of operating on the set of frozensets directly you could use that only as a helper data-structure - like in the unique_everseen recipe in the itertools section (copied verbatim):

from itertools import filterfalse

def unique_everseen(iterable, key=None):
    "List unique elements, preserving order. Remember all elements ever seen."
    # unique_everseen('AAAABBBCCDAABBB') --> A B C D
    # unique_everseen('ABBCcAD', str.lower) --> A B C D
    seen = set()
    seen_add = seen.add
    if key is None:
        for element in filterfalse(seen.__contains__, iterable):
            seen_add(element)
            yield element
    else:
        for element in iterable:
            k = key(element)
            if k not in seen:
                seen_add(k)
                yield element

Basically this would solve the issue when you use key=frozenset:

>>> x = [('a',1,2), ('b',3,4), ('x',5,6), ('a',2,1)]

>>> list(unique_everseen(x, key=frozenset))
[('a', 1, 2), ('b', 3, 4), ('x', 5, 6)]

This returns the elements as-is and it also maintains the relative order between the elements.

No ordering with frozensets. You can instead create sorted tuples to check for the existence of an item, adding the original if the tuple does not exist in the set:

y = set()
lst = []
for i in x:
    t = tuple(sorted(i, key=str)
    if t not in y:
         y.add(t)
         lst.append(i)
print(lst)
# [('a', 1, 2), ('b', 3, 4), ('x', 5, 6)]

The first entry gets preserved.

There are some quite useful functions in NumPy which can help you to solve this problem.

import numpy as np
chrs, indices = np.unique(list(map(lambda x:x[0], x)), return_index=True)
chrs, indices
>> (array(['a', 'b', 'x'], 
   dtype='<U1'), array([0, 1, 2]))
[x[indices[i]] for i in range(indices.size)]
>> [('a', 1, 2), ('b', 3, 4), ('x', 5, 6)]
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