I have the following Python 2.7 dictionary data structure (I do not control source data - comes from another system as is):
{112762853378: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'], 'alias': ['www.example.com'] }, 112762853385: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'], 'alias': ['www.example.com'] }, 112760496444: {'dst': ['10.121.4.136'], 'src': ['1.2.3.4'] }, 112760496502: {'dst': ['10.122.195.34'], 'src': ['4.3.2.1'] }, 112765083670: ... }
The dictionary keys will always be unique. Dst, src, and alias can be duplicates. All records will always have a dst and src but not every record will necessarily have an alias as seen in the third record.
In the sample data either of the first two records would be removed (doesn't matter to me which one). The third record would be considered unique since although dst and src are the same it is missing alias.
My goal is to remove all records where the dst, src, and alias have all been duplicated - regardless of the key.
How does this rookie accomplish this?
Also, my limited understanding of Python interprets the data structure as a dictionary with the values stored in dictionaries... a dict of dicts, is this correct?
I would just make a set of the list of keys then iterate over them into a new dict:
Since the way to find uniqueness in correspondences is exactly to use a dictionary, with the desired unique value being the key, the way to go is to create a reversed dict, where your values are composed as the key - then recreate a "de-reversed" dictionary using the intermediate result.