Metadata-Version: 2.1
Name: dmfrbloom
Version: 0.0.7
Summary: Bloom filters with the standard library
Home-page: https://github.com/droberson/dmfrbloom
Author: Daniel Roberson
Author-email: daniel@planethacker.net
License: UNKNOWN
Description: # dmfrbloom
        Bloom filters with Python standard library.
        
        ## Examples
        Normal bloom filter. Expects 10,000 elements with 99.99% accuracy:
        ```
        >>> from dmfrbloom.bloomfilter import BloomFilter
        >>> bf = BloomFilter(10000, 0.01)
        >>> bf.add("test")
        >>> bf.lookup("test")
        True
        >>> bf.lookup("not in filter")
        False
        >>> bf.save("/home/daniel/filter")
        >>> bf2 = BloomFilter(1, 0.1)
        >>> bf2.load("/home/daniel/filter")
        >>> bf2.lookup("test")
        True
        >>> bf2.lookup("also not in filter")
        False
        ```
        
        Time-based filter. 10k elements, 99.99% accuracy, results decay after
        60 seconds:
        ```
        >>> from dmfrbloom.timefilter import TimeFilter
        >>> tf = TimeFilter(10000, 0.01, 60)
        >>> tf.add("asdf")
        >>> tf.lookup("asdf")
        True
        >>> import time
        >>> time.sleep(60)
        >>> tf.lookup("asdf")
        False
        ```
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
