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README.rst
voting
======
|travis| |rtd| |codecov| |pypi| |pyversions|
.. |travis| image:: https://img.shields.io/travis/crflynn/voting.svg
:target: https://travis-ci.org/crflynn/voting
.. |rtd| image:: https://img.shields.io/readthedocs/voting.svg
:target: http://voting.readthedocs.io/en/latest/
.. |codecov| image:: https://codecov.io/gh/crflynn/voting/branch/master/graphs/badge.svg
:target: https://codecov.io/gh/crflynn/voting
.. |pypi| image:: https://img.shields.io/pypi/v/voting.svg
:target: https://pypi.python.org/pypi/voting
.. |pyversions| image:: https://img.shields.io/pypi/pyversions/voting.svg
:target: https://pypi.python.org/pypi/voting
A pure Python module for election quotas, voting measures, and apportionment
methods.
Installation
------------
The ``voting`` package works in Python 2.7, 3.5, 3.6 and 3.7. It is available on
pypi and can be installed using pip.
.. code-block:: shell
pip install voting
Package structure
-----------------
* voting
* apportionment
* adams
* dhondt
* hagenbach_bischoff
* hamilton
* huntington_hill
* jefferson
* sainte_lague
* vinton
* webster
* diversity
* berger_parker
* general
* gini_simpson
* golosov
* inverse_simpson
* laakso_taagepera
* renyi
* shannon
* simpson
* proportion
* adjusted_loosemore_hanby
* dhondt
* gallagher
* grofman
* least_square
* lijphart
* loosemore_hanby
* rae
* regression
* rose
* sainte_lague
* quota
* droop
* hagenbach_bischoff
* hare
* imperiali
Examples
--------
Apportioning seats using the Huntington-Hill method.
.. code-block:: python
from voting import apportionment
votes = [2560, 3315, 995, 5012]
seats = 20
assignments = apportionment.huntington_hill(votes, seats)
Calculating the effective number of parties using Golosov's measure.
.. code-block:: python
from voting import diversity
parties = [750, 150, 50, 50]
effective_parties = diversity.golosov(parties)
Measuring the disproportionality of democratic representation using the
Sainte-Lague measure.
.. code-block:: python
from voting import proportion
votes = [750, 150, 50, 50]
seats = [80, 16, 2, 2]
disproportionality = proportion.sainte_lague(votes, seats)
Determining the Droop quota
.. code-block:: python
from voting import quota
votes = 1000
seats = 20
election_quota = quota.droop(votes, seats)