Metadata-Version: 2.1
Name: fastBloomFilter
Version: 0.0.8
Summary: A fast and simple probabilistic bloom filter that supports compression
Home-page: http://github.com/daedalus/bloomfilter
Author: Dario Clavijo
Author-email: dclavijo@protonmail.com
License: UNKNOWN
Download-URL: http://github.com/daedalus/bloomfilter/tarball/0.0.8
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: Programming Language :: Python
Classifier: Operating System :: OS Independent
Classifier: License :: OSI Approved :: GNU General Public License (GPL)
Description-Content-Type: text/markdown
Requires-Dist: bitarray
Requires-Dist: python-lzo
Requires-Dist: lz4
Requires-Dist: pylzma
Requires-Dist: sha3

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# Simple and fast pythonic bloomfilter

From wikipedia: "A Bloom filter is a space-efficient probabilistic data structure, conceived by Burton Howard Bloom in 1970, that is used to test whether an element is a member of a set. False positive matches are possible, but false negatives are not – in other words, a query returns either "possibly in set" or "definitely not in set". Elements can be added to the set, but not removed (though this can be addressed with a "counting" filter); the more elements that are added to the set, the larger the probability of false positives."


### This filter supports: ###

```
- Saving, reloading, compressed bloomfilter file lrzip like
        for compression: lz4>lzo>zlib>bz2>lzma
        for decompression: lzma>bz2>zlib>lzo>lz4
- Stats
- Entropy analysis
- Internal and external hashing of data.
- raw filter merging
```


### Installing: ###

```
sudo pip install fastbloomfilter
```

### External creating of the bloom filter file: ###

```
python mkbloom.py /tmp/filter.blf
```

### Importing: ###

```
from fastBloomFilter import bloom
bf = bloom.BloomFilter(filename='/tmp/filter.blf')
```

### Adding data to it: ###

```
bf.add('30000')
bf.add('1230213')
bf.add('1')
```

### Adding data and at the same time querying it: ###

```
print bf.update('1') # True
print bf.update('1') # True
print bf.update('2') # False
print bf.update('2') # True
```

### Printing stats: ###

```
bf.stat()
```

Or:

```
bf.info()
```

### Querying data: ###

```
print bf.query('1') # True
print bf.query('1230213') # True
print bf.query('12') # False
```   

```
Contributons:
    Are welcome!
```


