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You are given information about users of your website. The information includes username, a phone number and/or an email. Write a program that takes in a list of tuples where each tuple represents information for a particular user and returns a list of lists where each sublist contains the indices of tuples containing information about the same person. For example:

Input:

[("MLGuy42", "andrew@gmail.com", "123-4567"),
("CS229DungeonMaster", "123-4567", "ml@stanford.edu"),
("Doomguy", "john@oculus.com", "carmack@gmail.com"),
("andrew26", "andrew@gmail.com", "mlguy@gmail.com")]

Output:

[[0, 1, 3], [2]]

Since "MLGuy42", "CS229DungeonMaster" and "andrew26" are all the same person.

Each sublist in the output should be sorted and the outer list should be sorted by the first element in the sublist.

Below is the code snippet that I did for this problem. It seems to work fine, but I'm wondering if there is a better/optimized solution.

def find_duplicates(user_info):
    results = list()
    seen = dict()
    for i, user in enumerate(user_info):
        first_seen = True
        key_info = None
        for info in user:
            if info in seen:
                first_seen = False
                key_info = info
                break
        if first_seen:
            results.append([i])
            pos = len(results) - 1
        else:
            index = seen[key_info]
            results[index].append(i)
            pos = index
        for info in user:
            seen[info] = pos
    return results
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  • \$\begingroup\$ By the way, this is a thinly disguised union-find problem. \$\endgroup\$ – 200_success Nov 21 '17 at 22:31
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def find_duplicates(user_info):
    results = list()
    seen = dict()
    for i, user in enumerate(user_info):
        for info in user:
            if info in seen:
                index = seen[info]
                results[index].append(i)
                pos = index
                break
        else:
            results.append([i])
            pos = len(results) - 1
        for info in user:
            seen[info] = pos
    return results

How I tested speeds

Your code, as it currently stands, will work exactly the same with integers. So, I just randomly generated large data sets this way (and played along with MAXVALUE and range a bit.

from random import randrange
from timeit import timeit
MAXVALUE = 1000

for a in range(5): #I wanted to make sure I checked 5 to make sure I don't get a outlier data set that effects my ability to use timeit reasonably.
    user_info = [[randrange(MAXVALUE) for i in range(3)] for _ in range(1000)]
    print(timeit(lambda: find_duplicates(user_info), number=10000))

Credit for improving code: Maarten Fabré

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  • \$\begingroup\$ I think your second if info in seen: should be if info not in seen: \$\endgroup\$ – Maarten Fabré Nov 21 '17 at 15:59
  • \$\begingroup\$ @MaartenFabré You're right. When I looked at it I found that it wasn't faster checking that, so I removed it all together. Thanks. \$\endgroup\$ – Neil Nov 21 '17 at 18:49
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A good day starts with a test

import unittest
#import or paste your function here

a = ('a', 'a@a', '1')
b = ('b', 'b@b', '2')
c = ('c', 'c@c', '3')
ab = ('a', 'b@b', '12')

tests = [
    ([a, b], [[0], [1]]),
    ([a, b, c], [[0], [1], [2]]),
    ([a, b], [[0], [1]]),
    ([a, ab, b], [[0, 1, 2]]),
    ([a, ab, b, c], [[0, 1, 2],[3]]),
    ([a, ab, c, b], [[0, 1, 3],[2]]),
    ([c, a, ab, b], [[0],[1, 2, 3]]),
    ([a, b, ab], [[0, 1, 2]]),
    ]

class Test(unittest.TestCase):

    def test_some(self):
        for n, t in enumerate(tests):
            ud = t[0]
            ref = t[1]
            res = find_duplicates(ud)
            assert ref==res, "n:{}, ud:{}, ref:{}, res:{}".format(n, ud, ref, res)

if __name__ == "__main__":
    unittest.main()

gives

======================================================================
FAIL: test_some (user_info.Test)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "C:\Users\Verena\workspace\user_info\src\user_info.py", line xx, in test_some
    assert ref==res, "n:{}, ud:{}, ref:{}, res:{}".format(n, ud, ref, res)
AssertionError: n:7, ud:[('a', 'a@a', '1'), ('b', 'b@b', '2'), ('a', 'b@b', '12')], ref:[[0, 1, 2]], res:[[0, 2], [1]]

----------------------------------------------------------------------
Ran 1 test in 0.001s
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1
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I was toying with this thinking a defaultdict would also work for this instead of a list of lists

I had a solution I found rather elegant with getting an intersection of seen.keys() and set(user), but that was prohibitively slow. This solution is about as fast as nfn neil's

def find_duplicates_defaultdict(user_info):
    results = collections.defaultdict(list)
    seen = dict()
    for i, user in enumerate(user_info):
        for info in user:
            try:
                pos = seen[info]
                break
            except KeyError:
                pass
        else:
            pos = len(results)
        results[pos].append(i)
        for info in user:
            if info not in seen:
                seen[info] = pos

    return results.values() # expects ordered defaultdict older versions of python might need something like
    return [results[key] for key in sorted(results.keys())]

Order of iteration

These results depend on the order of iteration. For a list like this

info = [
    ("MLGuy42", "andrew@gmail.com", "123-4567"),
    ("CS229DungeonMaster", "123-4567", "ml@stanford.edu"),
    ("Doomguy", "john@oculus.com", "carmack@gmail.com"),
    ("andrew26", "another_andrew@gmail.com", "mlguy@gmail.com"),
    ("andrew26", "andrew@gmail.com", "yet_another_andrew@gmail.com")
       ]

it returns [[0, 1], [2], [3, 4]] instead of [[0, 1, 3, 4], [2]], which would have been the result if line 4 was before line 3

To solve this, I found a different implementation. This requires a double iteration over the results, so it is slower, but more complete

def find_duplicates_set(user_info):
    subsets = collections.defaultdict(set)
    subsets[0] = set(user_info[0])

    for user in user_info:
        indices = {i for i, subset in subsets.items() if not subset.isdisjoint(user)}
        if not indices:
            subsets[max(subsets.keys()) + 1] = set(user)
        elif len(indices) == 1:
            subsets[indices.pop()].update(user)
        else:
            indices = sorted(indices)
            i0 = indices.pop(0)
            subsets[i0].update(user)
            for i in indices:
                subset = subsets.pop(i)
                subsets[i0].update(subset)
    results = collections.defaultdict(list)        
    for i, user in enumerate(user_info):
        for index, subset in subsets.items():
            if not subset.isdisjoint(user):
                results[index].append(i)
                break
    return results.values()

Execution speed

MAXVALUE = 1000
for a in range(3):
    user_info = [[randrange(MAXVALUE) for i in range(3)] for _ in range(10 * MAXVALUE)]
    print('original: ', timeit(lambda: find_duplicates(user_info), number=1000))
    print('nfn_neil: ', timeit(lambda: find_duplicates_nfn(user_info), number=1000))
    print('defaultdict: ', timeit(lambda: find_duplicates_defaultdict(user_info), number=1000))
    print('set: ', timeit(lambda: find_duplicates_set(user_info), number=1000))
original:  6.129232463274093
nfn_neil:  4.994730664504459
defaultdict:  4.738290764427802
set:  18.66864765893115
original:  5.425038123095874
nfn_neil:  4.78540134785726
defaultdict:  4.616922919762146
set:  19.058994075487135
original:  5.55867017791752
nfn_neil:  4.920460685316357
defaultdict:  4.8429226022271905
set:  19.008669542017742
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