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    <p>However, there is a pitfall in both solutions. The reason is that it merges the values with the same hash. So, it depends on whether the used values may have the same hash. It is not that crazy comment as you may think (I was also surprised earlier), because Python hashes some values the special way. Try:</p> <pre><code>from collections import Counter def counter_way(x): return [k for k,v in Counter(x).iteritems() if v &gt; 1] def accepted_way(x): #accepted answer in the linked thread duplicates = set() found = set() for item in x: if item in found: duplicates.add(item) else: found.add(item) return duplicates a = ('x ', (1,), u'x') * 2 print 'The values:', a print 'Counter way duplicates:', counter_way(a) print 'Accepted way duplicates:', accepted_way(a) print '-' * 50 # Now the problematic values. a = 2 * (0, 1, True, False, 0.0, 1.0) print 'The values:', a print 'Counter way duplicates:', counter_way(a) print 'Accepted way duplicates:', accepted_way(a) </code></pre> <p>The 1, 1.0, and True have the same hash by definition, and similarly the 0, 0.0, and False. It prints the following on my console (think about the last two lines -- all the values should actually be duplicates):</p> <pre><code>c:\tmp\___python\hynekcer\so10247815&gt;python d.py The values: ('x ', (1,), u'x', 'x ', (1,), u'x') Counter way duplicates: [u'x', 'x ', (1,)] Accepted way duplicates: set([u'x', 'x ', (1,)]) -------------------------------------------------- The values: (0, 1, True, False, 0.0, 1.0, 0, 1, True, False, 0.0, 1.0) Counter way duplicates: [0, 1] Accepted way duplicates: set([False, True]) </code></pre>
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    1. POWhat is a good pythonic way of finding duplicate objects?
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    1. COThis is not a pitfal, this is how equality `==` is defined in Python: `assert 0 == 0.0 == False and 1 == 1.0 == True and 'a' == u'a'`. Even complex numbers can be equal `1 == 1.0 + 0.0j`. If you want to compare exactly and use also composed types like tuples, you should compare pickled representation as the only possible solution. You can verify that dictionary keys are unique even if they have the same hash. (Create a dictionary on 32 bit system with one million random tuples as keys. With probability more than 99% you find some the same hashes but different keys.)
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    2. COWell, expectations may differ. However, I can imagine the `[0, False]` be considered as the list of unique values.
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    3. COpepr: What is your method? How you test that `0` an `False` are different in *Python*?
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