Metadata-Version: 2.1
Name: apportionment
Version: 1.0
Summary: A Python implementation of common apportionment methods
Home-page: https://github.com/martinlackner/apportionment/
Author: Martin Lackner
Author-email: unexpected@sent.at
License: MIT License
Project-URL: Bug Tracker, https://github.com/martinlackner/apportionment/issues
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: License :: OSI Approved :: MIT License
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Classifier: Intended Audience :: Science/Research
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: numpy (>=1.20)
Provides-Extra: dev
Requires-Dist: pytest (>=6) ; extra == 'dev'
Requires-Dist: coverage[toml] (>=5.3) ; extra == 'dev'
Requires-Dist: black (==22.1.0) ; extra == 'dev'

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# A Python implementation of common apportionment methods

This is a collection of common apportionment methods. Apportionment has two main applications: 
to assign a fixed number of [parliamentary seats to parties](https://en.wikipedia.org/wiki/Party-list_proportional_representation) (proportionally to their vote count), and to assign
[representatives in a senate to states](https://en.wikipedia.org/wiki/United_States_congressional_apportionment) (proportionally to their population count). 
A recommendable overview of apportionment methods can be found in the book "Fair Representation" by Balinski and Young [2].

The following apportionment methods are implemented:
* the largest remainder method (or Hamilton method)
* the class of divisor methods including
   - D'Hondt (or Jefferson)
   - Sainte-Laguë (or Webster)
   - Modified Sainte-Laguë (as used e.g. in Norway) 
   - Huntington-Hill
   - Adams
* the quota method [1]

This module supports Python 3.7+.

## Installation

Using pip:

```bash
pip install apportionment
```

Latest development version from source:

```bash
git clone https://github.com/martinlackner/abcvoting/
python setup.py install
```

Requirements:
* Python 3.7+
* numpy

## A simple example

The following example calculates the seat distribution of Austrian representatives in the 
European Parliament based on the D'Hondt method and the [2019 election results](https://www.bmi.gv.at/412/Europawahlen/Europawahl_2019). Parties that received less than 4% are excluded from obtaining seats and are thus excluded in the calculation.

```python
import apportionment.methods as app
parties = ['OEVP', 'SPOE', 'FPOE', 'GRUENE', 'NEOS']
votes = [1305956, 903151, 650114, 532193, 319024]
seats = 18
app.compute("dhondt", votes, seats, parties, verbose=True)
```

The output is

```
D'Hondt (Jefferson) method
  OEVP: 7
  SPOE: 5
  FPOE: 3
  GRUENE: 2
  NEOS: 1
```

which is indeed the [official result](https://www.bmi.gv.at/412/Europawahlen/Europawahl_2019).

Another example can be found in [apportionment/examples/simple.py](apportionment/examples/simple.py).
We verify results from recent Austrian National Council elections in [apportionment/examples/austria.py](apportionment/examples/austria.py) and from recent elections of the Israeli Knesset in [apportionment/examples/israel.py](apportionment/examples/israel.py).

## References

[1] Balinski, M. L., & Young, H. P. (1975). The quota method of apportionment. The American Mathematical Monthly, 82(7), 701-730.

[2] Balinski, M. L., & Young, H. P. (1982). Fair Representation: Meeting the Ideal of One Man, One Vote. Yale University Press, 1982. (There is a second edition from 2001 by Brookings Institution Press.)


