Metadata-Version: 1.1
Name: recordinality
Version: 0.0.2
Summary: A Python implementation of the Recordinality sketch
Home-page: https://github.com/zacharyvoase/recordinality
Author: Zachary Voase
Author-email: zack@meat.io
License: Unlicense
Description: Recordinality.py
        ================
        
        A Python implementation of the
        `Recordinality <http://www-apr.lip6.fr/%7Elumbroso/Publications/HeLuMaVi12.pdf>`__
        sketch for cardinality estimation and stream sampling. Inspired by C.
        Scott Andreas's
        `implementation <https://github.com/cscotta/recordinality>`__, but
        powered by SipHash-2-4 rather than MurmurHash3. In particular, this
        project uses two other libraries of mine:
        `csiphash <https://github.com/zacharyvoase/python-csiphash>`__ and
        `cskipdict <https://github.com/zacharyvoase/python-cskipdict>`__.
        
        Installation
        ------------
        
        ::
        
            pip install recordinality
        
        Usage
        -----
        
        You can use the command-line application, which will read lines of text
        incrementally from stdin, printing the stream's cardinality (or a random
        sample) once the pipe is closed:
        
        ::
        
            $ recordinality -k <sketch-size> [-h|--hash-key <hash-key>] [-s|--sample] < input-lines.txt
            3574
            $ cat input-lines.txt | sort -u | wc -l
            3556
        
        SipHash allows the specification of a 'secret key' (used here as more of
        a hash seed); if provided it should be either a 16-char ASCII string or
        32-char hexadecimal string.
        
        You can also import the ``Recordinality`` class in Python:
        
        .. code:: python
        
            >>> from recordinality import Recordinality
            >>> sketch = Recordinality(size=512)
            >>> for observation in input_observations:
            ...     sketch.add(observation)
            >>> print(sketch.cardinality())
            3574
            >>> print(sketch.k_sample)
            ['strife', 'bragging', 'knight?', ...]
        
        Unlicense
        ---------
        
        This is free and unencumbered software released into the public domain.
        
        Anyone is free to copy, modify, publish, use, compile, sell, or
        distribute this software, either in source code form or as a compiled
        binary, for any purpose, commercial or non-commercial, and by any means.
        
        In jurisdictions that recognize copyright laws, the author or authors of
        this software dedicate any and all copyright interest in the software to
        the public domain. We make this dedication for the benefit of the public
        at large and to the detriment of our heirs and successors. We intend
        this dedication to be an overt act of relinquishment in perpetuity of
        all present and future rights to this software under copyright law.
        
        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS
        OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF
        MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.
        IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
        FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
        DEALINGS IN THE SOFTWARE.
        
        For more information, please refer to http://unlicense.org/
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: Public Domain
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
