Probabilistic Structures
========================
``Probstructs`` is easy to use Python wrapper for C++ library `probstructs`_ . It supports Exponential Histograms, Count Min Sketch (CM-Sketch), and Exponential Count Min Sketch (ECM-Sketch).
.. _probstructs: https://github.com/martin-majlis/probstructs
|build-status| |docs| |version| |pyversions| |github-stars-flat|
Installation
------------
With pip:
.. code-block:: bash
pip install probstructs
From source:
.. code-block:: bash
pip install .
Classes
-------
CountMinSketch
^^^^^^^^^^^^^^
Count–min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data. It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space, at the expense of overcounting some events due to collisions.
C++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#countminsketch
.. code-block:: python
from probstructs import CountMinSketch
cm_sketch = CountMinSketch(100, 4)
cm_sketch.inc("aaa", 1)
cm_sketch.inc("bbb", 5)
cm_sketch.inc("aaa", 2)
print(cm_sketch.get("aaa"))
# 3
print(cm_sketch.get("bbb"))
# 5
print(cm_sketch.get("ccc"))
# 0
cm_sketch = CountMinSketch(width=100, depth=4)
cm_sketch.inc(key="bbb", delta=5)
print(cm_sketch.get(key="bbb"))
# 5
ExponentialHistorgram
^^^^^^^^^^^^^^^^^^^^^
Exponential histogram (EH) is a probabilistic data structure that serves as a frequency counter for specific elements in the last N elements from stream..
C++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#exponentialhistorgram
.. code-block:: python
from probstructs import ExponentialHistorgram
eh = ExponentialHistorgram(1)
eh.inc(1, 1)
print(eh.get(1, 1))
# 1
eh.inc(1, 1)
print(eh.get(1, 1))
# 2
eh.inc(2, 1)
print(eh.get(1, 2))
# 1
eh = ExponentialHistorgram(window=1)
eh.inc(tick=1, delta=1)
print(eh.get(window=1, tick=1))
# 1
eh.inc(tick=1, delta=1)
print(eh.get(window=1, tick=1))
# 2
eh.inc(tick=2, delta=1)
print(eh.get(window=1, tick=2))
# 1
ExponentialCountMinSketch
^^^^^^^^^^^^^^^^^^^^^^^^^
Exponential count-min sketch (ECM-Sketch) combines CM-Sketch with EH to count number of different elements in the last N elements in the stream.
C++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#exponentialcountminsketch
.. code-block:: python
from probstructs import ExponentialCountMinSketch
ecm_sketch = ExponentialCountMinSketch(100, 4, 8)
ts = 0
ecm_sketch.inc("aaa", ts, 1)
ecm_sketch.inc("bbb", ts, 4)
ecm_sketch.inc("ccc", ts, 8)
print(ecm_sketch.get("aaa", 4, ts))
# 1
print(ecm_sketch.get("bbb", 4, ts))
# 4
print(ecm_sketch.get("ccc", 4, ts))
# 8
print(ecm_sketch.get("ddd", 4, ts))
# 0
ecm_sketch = ExponentialCountMinSketch(width=100, depth=4, window=8)
ts = 0
ecm_sketch.inc(key="aaa", tick=ts, delta=1)
ecm_sketch.inc(key="bbb", tick=ts, delta=4)
ecm_sketch.inc(key="ccc", tick=ts, delta=8)
print(ecm_sketch.get(key="aaa", window=4, tick=ts))
# 1
print(ecm_sketch.get(key="bbb", window=4, tick=ts))
# 4
print(ecm_sketch.get(key="ccc", window=4, tick=ts))
# 8
print(ecm_sketch.get(key="ddd", window=4, tick=ts))
# 0
.. |build-status| image:: https://travis-ci.org/martin-majlis/py-probstructs.svg?branch=master
:alt: build status
:target: https://travis-ci.org/martin-majlis/py-probstructs
.. |docs| image:: https://readthedocs.org/projects/py-probstructs/badge/?version=latest
:target: http://py-probstructs.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
.. |version| image:: https://img.shields.io/pypi/v/probstructs.svg?style=flat
:target: https://pypi.python.org/pypi/probstructs
:alt: Version
.. |pyversions| image:: https://img.shields.io/pypi/pyversions/probstructs.svg?style=flat
:target: https://pypi.python.org/pypi/probstructs
:alt: Py Versions
.. |github-stars-flat| image:: https://img.shields.io/github/stars/martin-majlis/py-probstructs.svg?style=flat&label=Stars
:target: https://github.com/martin-majlis/py-probstructs/
:alt: GitHub stars
Changelog
=========
0.2.0
-----
* Introduce named parameters
* Update documentation to contain examples
0.1.0
-----
* Initial version
Raw data
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"description": "Probabilistic Structures\n========================\n\n``Probstructs`` is easy to use Python wrapper for C++ library `probstructs`_ . It supports Exponential Histograms, Count Min Sketch (CM-Sketch), and Exponential Count Min Sketch (ECM-Sketch).\n\n.. _probstructs: https://github.com/martin-majlis/probstructs\n\n|build-status| |docs| |version| |pyversions| |github-stars-flat|\n\nInstallation\n------------\n\nWith pip:\n\n.. code-block:: bash\n\n pip install probstructs\n\nFrom source:\n\n.. code-block:: bash\n\n pip install .\n\nClasses\n-------\n\nCountMinSketch\n^^^^^^^^^^^^^^\n\nCount\u2013min sketch (CM sketch) is a probabilistic data structure that serves as a frequency table of events in a stream of data. It uses hash functions to map events to frequencies, but unlike a hash table uses only sub-linear space, at the expense of overcounting some events due to collisions.\n\nC++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#countminsketch\n\n.. code-block:: python\n\n from probstructs import CountMinSketch\n\n cm_sketch = CountMinSketch(100, 4)\n cm_sketch.inc(\"aaa\", 1)\n cm_sketch.inc(\"bbb\", 5)\n cm_sketch.inc(\"aaa\", 2)\n\n print(cm_sketch.get(\"aaa\"))\n # 3\n print(cm_sketch.get(\"bbb\"))\n # 5\n print(cm_sketch.get(\"ccc\"))\n # 0\n\n\n cm_sketch = CountMinSketch(width=100, depth=4)\n cm_sketch.inc(key=\"bbb\", delta=5)\n print(cm_sketch.get(key=\"bbb\"))\n # 5\n\nExponentialHistorgram\n^^^^^^^^^^^^^^^^^^^^^\n\nExponential histogram (EH) is a probabilistic data structure that serves as a frequency counter for specific elements in the last N elements from stream..\n\nC++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#exponentialhistorgram\n\n.. code-block:: python\n\n from probstructs import ExponentialHistorgram\n\n\n eh = ExponentialHistorgram(1)\n eh.inc(1, 1)\n print(eh.get(1, 1))\n # 1\n eh.inc(1, 1)\n print(eh.get(1, 1))\n # 2\n eh.inc(2, 1)\n print(eh.get(1, 2))\n # 1\n\n eh = ExponentialHistorgram(window=1)\n eh.inc(tick=1, delta=1)\n print(eh.get(window=1, tick=1))\n # 1\n eh.inc(tick=1, delta=1)\n print(eh.get(window=1, tick=1))\n # 2\n eh.inc(tick=2, delta=1)\n print(eh.get(window=1, tick=2))\n # 1\n\nExponentialCountMinSketch\n^^^^^^^^^^^^^^^^^^^^^^^^^\n\nExponential count-min sketch (ECM-Sketch) combines CM-Sketch with EH to count number of different elements in the last N elements in the stream.\n\nC++ documentation: https://probstructs.readthedocs.io/en/latest/classes.html#exponentialcountminsketch\n\n.. code-block:: python\n\n from probstructs import ExponentialCountMinSketch\n\n\n ecm_sketch = ExponentialCountMinSketch(100, 4, 8)\n\n ts = 0\n ecm_sketch.inc(\"aaa\", ts, 1)\n ecm_sketch.inc(\"bbb\", ts, 4)\n ecm_sketch.inc(\"ccc\", ts, 8)\n\n print(ecm_sketch.get(\"aaa\", 4, ts))\n # 1\n print(ecm_sketch.get(\"bbb\", 4, ts))\n # 4\n print(ecm_sketch.get(\"ccc\", 4, ts))\n # 8\n print(ecm_sketch.get(\"ddd\", 4, ts))\n # 0\n\n ecm_sketch = ExponentialCountMinSketch(width=100, depth=4, window=8)\n\n ts = 0\n ecm_sketch.inc(key=\"aaa\", tick=ts, delta=1)\n ecm_sketch.inc(key=\"bbb\", tick=ts, delta=4)\n ecm_sketch.inc(key=\"ccc\", tick=ts, delta=8)\n\n print(ecm_sketch.get(key=\"aaa\", window=4, tick=ts))\n # 1\n print(ecm_sketch.get(key=\"bbb\", window=4, tick=ts))\n # 4\n print(ecm_sketch.get(key=\"ccc\", window=4, tick=ts))\n # 8\n print(ecm_sketch.get(key=\"ddd\", window=4, tick=ts))\n # 0\n\n\n\n\n\n\n.. |build-status| image:: https://travis-ci.org/martin-majlis/py-probstructs.svg?branch=master\n :alt: build status\n :target: https://travis-ci.org/martin-majlis/py-probstructs\n\n.. |docs| image:: https://readthedocs.org/projects/py-probstructs/badge/?version=latest\n :target: http://py-probstructs.readthedocs.io/en/latest/?badge=latest\n :alt: Documentation Status\n\n.. |version| image:: https://img.shields.io/pypi/v/probstructs.svg?style=flat\n\t:target: https://pypi.python.org/pypi/probstructs\n\t:alt: Version\n\n.. |pyversions| image:: https://img.shields.io/pypi/pyversions/probstructs.svg?style=flat\n\t:target: https://pypi.python.org/pypi/probstructs\n\t:alt: Py Versions\n\n.. |github-stars-flat| image:: https://img.shields.io/github/stars/martin-majlis/py-probstructs.svg?style=flat&label=Stars\n\t:target: https://github.com/martin-majlis/py-probstructs/\n\t:alt: GitHub stars\n\nChangelog\n=========\n\n0.2.0\n-----\n\n* Introduce named parameters\n* Update documentation to contain examples\n\n0.1.0\n-----\n* Initial version\n",
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