Metadata-Version: 1.1
Name: simplebloomfilter
Version: 1.0.0
Summary: A simple implementation of Bloom Filter and Scalable Bloom Filter for Python 3.
Home-page: https://github.com/dnanhkhoa/simple-bloom-filter
Author: Khoa Duong
Author-email: dnanhkhoa@live.com
License: MIT
Description: # simple-bloom-filter
        
        [![PyPI](https://img.shields.io/pypi/v/simplebloomfilter.svg)]()
        [![PyPI - Python Version](https://img.shields.io/pypi/pyversions/simplebloomfilter.svg)]()
        
        A simple implementation of Bloom Filter and Scalable Bloom Filter for Python 3.
        
        ## Installation
        
        You can install this package from PyPI using [pip](http://www.pip-installer.org):
        
        ```
        $ [sudo] pip install simplebloomfilter
        ```
        
        ## Example Usage
        
        ```python
        #!/usr/bin/python
        # -*- coding: utf-8 -*-
        from bloomfilter import BloomFilter, ScalableBloomFilter, SizeGrowthRate
        
        animals = [
            "dog",
            "cat",
            "giraffe",
            "fly",
            "mosquito",
            "horse",
            "eagle",
            "bird",
            "bison",
            "boar",
            "butterfly",
            "ant",
            "anaconda",
            "bear",
            "chicken",
            "dolphin",
            "donkey",
            "crow",
            "crocodile",
        ]
        
        other_animals = [
            "badger",
            "cow",
            "pig",
            "sheep",
            "bee",
            "wolf",
            "fox",
            "whale",
            "shark",
            "fish",
            "turkey",
            "duck",
            "dove",
            "deer",
            "elephant",
            "frog",
            "falcon",
            "goat",
            "gorilla",
            "hawk",
        ]
        
        
        def bloom_filter_example():
            print("========== Bloom Filter Example ==========")
            bloom_filter = BloomFilter(size=1000, fp_prob=1e-6)
        
            # Insert items into Bloom filter
            for animal in animals:
                bloom_filter.add(animal)
        
            # Print several statistics of the filter
            print(
                "+ Capacity: {} item(s)".format(bloom_filter.size),
                "+ Number of inserted items: {}".format(len(bloom_filter)),
                "+ Filter size: {} bit(s)".format(bloom_filter.filter_size),
                "+ False Positive probability: {}".format(bloom_filter.fp_prob),
                "+ Number of hash functions: {}".format(bloom_filter.num_hashes),
                sep="\n",
                end="\n\n",
            )
        
            # Check whether an item is in the filter or not
            for animal in animals + other_animals:
                if animal in bloom_filter:
                    if animal in other_animals:
                        print(
                            f'"{animal}" is a FALSE POSITIVE case (please adjust fp_prob to a smaller value).'
                        )
                    else:
                        print(f'"{animal}" is PROBABLY IN the filter.')
                else:
                    print(f'"{animal}" is DEFINITELY NOT IN the filter as expected.')
        
            # Save to file
            with open("bloom_filter.bin", "wb") as fp:
                bloom_filter.save(fp)
        
            # Load from file
            with open("bloom_filter.bin", "rb") as fp:
                bloom_filter = BloomFilter.load(fp)
        
        
        def scalable_bloom_filter_example():
            print("========== Bloom Filter Example ==========")
            scalable_bloom_filter = ScalableBloomFilter(
                initial_size=100,
                initial_fp_prob=1e-7,
                size_growth_rate=SizeGrowthRate.LARGE,
                fp_prob_rate=0.9,
            )
            # Insert items into Bloom filter
            for animal in animals:
                scalable_bloom_filter.add(animal)
        
            # Print several statistics of the filter
            print(
                "+ Capacity: {} item(s)".format(scalable_bloom_filter.size),
                "+ Number of inserted items: {}".format(len(scalable_bloom_filter)),
                "+ Number of Bloom filters: {}".format(scalable_bloom_filter.num_filters),
                "+ Total size of filters: {} bit(s)".format(scalable_bloom_filter.filter_size),
                "+ False Positive probability: {}".format(scalable_bloom_filter.fp_prob),
                sep="\n",
                end="\n\n",
            )
        
            # Check whether an item is in the filter or not
            for animal in animals + other_animals:
                if animal in scalable_bloom_filter:
                    if animal in other_animals:
                        print(
                            f'"{animal}" is a FALSE POSITIVE case (please adjust fp_prob to a smaller value).'
                        )
                    else:
                        print(f'"{animal}" is PROBABLY IN the filter.')
                else:
                    print(f'"{animal}" is DEFINITELY NOT IN the filter as expected.')
        
            # Save to file
            with open("scalable_bloom_filter.bin", "wb") as fp:
                scalable_bloom_filter.save(fp)
        
            # Load from file
            with open("scalable_bloom_filter.bin", "rb") as fp:
                scalable_bloom_filter = ScalableBloomFilter.load(fp)
        
        
        if __name__ == "__main__":
            bloom_filter_example()
            scalable_bloom_filter_example()
        ```
        ```
        ========== Bloom Filter Example ==========
        + Capacity: 1000 item(s)
        + Number of inserted items: 19
        + Filter size: 28756 bit(s)
        + False Positive probability: 1e-06
        + Number of hash functions: 20
        
        "dog" is PROBABLY IN the filter.
        "cat" is PROBABLY IN the filter.
        "giraffe" is PROBABLY IN the filter.
        "fly" is PROBABLY IN the filter.
        "mosquito" is PROBABLY IN the filter.
        "horse" is PROBABLY IN the filter.
        "eagle" is PROBABLY IN the filter.
        "bird" is PROBABLY IN the filter.
        "bison" is PROBABLY IN the filter.
        "boar" is PROBABLY IN the filter.
        "butterfly" is PROBABLY IN the filter.
        "ant" is PROBABLY IN the filter.
        "anaconda" is PROBABLY IN the filter.
        "bear" is PROBABLY IN the filter.
        "chicken" is PROBABLY IN the filter.
        "dolphin" is PROBABLY IN the filter.
        "donkey" is PROBABLY IN the filter.
        "crow" is PROBABLY IN the filter.
        "crocodile" is PROBABLY IN the filter.
        "badger" is DEFINITELY NOT IN the filter as expected.
        "cow" is DEFINITELY NOT IN the filter as expected.
        "pig" is DEFINITELY NOT IN the filter as expected.
        "sheep" is DEFINITELY NOT IN the filter as expected.
        "bee" is DEFINITELY NOT IN the filter as expected.
        "wolf" is DEFINITELY NOT IN the filter as expected.
        "fox" is DEFINITELY NOT IN the filter as expected.
        "whale" is DEFINITELY NOT IN the filter as expected.
        "shark" is DEFINITELY NOT IN the filter as expected.
        "fish" is DEFINITELY NOT IN the filter as expected.
        "turkey" is DEFINITELY NOT IN the filter as expected.
        "duck" is DEFINITELY NOT IN the filter as expected.
        "dove" is DEFINITELY NOT IN the filter as expected.
        "deer" is DEFINITELY NOT IN the filter as expected.
        "elephant" is DEFINITELY NOT IN the filter as expected.
        "frog" is DEFINITELY NOT IN the filter as expected.
        "falcon" is DEFINITELY NOT IN the filter as expected.
        "goat" is DEFINITELY NOT IN the filter as expected.
        "gorilla" is DEFINITELY NOT IN the filter as expected.
        "hawk" is DEFINITELY NOT IN the filter as expected.
        
        
        ========== Bloom Filter Example ==========
        + Capacity: 100 item(s)
        + Number of inserted items: 19
        + Number of Bloom filters: 1
        + Total size of filters: 3355 bit(s)
        + False Positive probability: 9.999999994736442e-08
        
        "dog" is PROBABLY IN the filter.
        "cat" is PROBABLY IN the filter.
        "giraffe" is PROBABLY IN the filter.
        "fly" is PROBABLY IN the filter.
        "mosquito" is PROBABLY IN the filter.
        "horse" is PROBABLY IN the filter.
        "eagle" is PROBABLY IN the filter.
        "bird" is PROBABLY IN the filter.
        "bison" is PROBABLY IN the filter.
        "boar" is PROBABLY IN the filter.
        "butterfly" is PROBABLY IN the filter.
        "ant" is PROBABLY IN the filter.
        "anaconda" is PROBABLY IN the filter.
        "bear" is PROBABLY IN the filter.
        "chicken" is PROBABLY IN the filter.
        "dolphin" is PROBABLY IN the filter.
        "donkey" is PROBABLY IN the filter.
        "crow" is PROBABLY IN the filter.
        "crocodile" is PROBABLY IN the filter.
        "badger" is DEFINITELY NOT IN the filter as expected.
        "cow" is DEFINITELY NOT IN the filter as expected.
        "pig" is DEFINITELY NOT IN the filter as expected.
        "sheep" is DEFINITELY NOT IN the filter as expected.
        "bee" is DEFINITELY NOT IN the filter as expected.
        "wolf" is DEFINITELY NOT IN the filter as expected.
        "fox" is DEFINITELY NOT IN the filter as expected.
        "whale" is DEFINITELY NOT IN the filter as expected.
        "shark" is DEFINITELY NOT IN the filter as expected.
        "fish" is DEFINITELY NOT IN the filter as expected.
        "turkey" is DEFINITELY NOT IN the filter as expected.
        "duck" is DEFINITELY NOT IN the filter as expected.
        "dove" is DEFINITELY NOT IN the filter as expected.
        "deer" is DEFINITELY NOT IN the filter as expected.
        "elephant" is DEFINITELY NOT IN the filter as expected.
        "frog" is DEFINITELY NOT IN the filter as expected.
        "falcon" is DEFINITELY NOT IN the filter as expected.
        "goat" is DEFINITELY NOT IN the filter as expected.
        "gorilla" is DEFINITELY NOT IN the filter as expected.
        "hawk" is DEFINITELY NOT IN the filter as expected.
        ```
        
        ## License
        
        MIT
        
Keywords: bloom-filter scalable-bloom-filter bloomfilter python-3 hashing algorithm data-structure
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
