Metadata-Version: 2.1
Name: bloomf
Version: 0.2
Summary: Simple Bloom Filter implmentation in Python
Home-page: https://github.com/sambhav2612/karumanchi/tree/master/bloom-filter
Author: Sambhav Jain
Author-email: sambhavjain2612@gmail.com
License: UNKNOWN
Description: # Bloom Filter
        
        Implemented in Python.
        
        - The price we pay for efficiency through bloom filters is that it is probabilistic in nature that means, there might be some **_False Positive_** results. False positive means, it might tell that given username is already taken but actually itâ€™s not.
        - Not being **_False Negative_** such that telling that username doesn't exist while it is there, i.e., if exists it reports it's existenece in terms of maybe, else if not present it is 100% confident to report the same.
        - Deleting elements from filter is not possible because, if we delete a single element by clearing bits at indices generated by k hash functions, it might cause deletion of few other elements.
        
        Distributed as a [PyPi](https://pypi.org/project/bloomf/) Package.
        
        ## Dependencies
        
        - Twine
        - bitarray
        - setuptools
        - wheel
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
