Metadata-Version: 2.1
Name: us-elections
Version: 0.1.1
Summary: U.S. election and government metadata
Home-page: https://github.com/The-Politico/us-elections/
Author: POLITICO Interactive News
Author-email: interactives@politico.com
License: MIT
Download-URL: https://github.com/The-Politico/us-elections/archive/0.1.1.tar.gz
Platform: any
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Topic :: Internet :: WWW/HTTP
Description-Content-Type: text/markdown
Requires-Dist: us
Provides-Extra: test
Requires-Dist: pytest ; extra == 'test'

![POLITICO](https://www.politico.com/interactives/cdn/images/badge.svg)

# us-elections 🇺🇸

A package for working with US elections metadata. Like [python-us](https://github.com/unitedstates/python-us), but for elections!

[![PyPI version](https://badge.fury.io/py/us-elections.svg)](https://badge.fury.io/py/us-elections)


### Quickstart

```
$ pip install us-elections
```


### Classes

#### `ElectionYear`

```python
from elections import ElectionYear


# GET A SPECIFIC YEAR'S ELECTIONS AND DATA:
election_year = ElectionYear(2018)
# <ElectionYear: 2020 (Presidential election cycle)>


# GET ELECTIONS IN THIS YEAR:
election_year.elections
# [<GeneralElection: Alabama Nov. 06, 2018>, ... ]

election_year.elections.general
election_year.elections.primary


# GET GOVERNMENTS BY LEVEL:
election_year.federal
# <FederalGovernment: United States of America>

election_year.states
# [<StateGovernment: Alabama>, <StateGovernment: Alaska>, ... ]

eyr.states.alabama
eyr.states.new_jersey


# GET A BRANCH WITHIN A GOVERNMENT:
election_year.federal.legislative
# <Branch: United States Federal Government legislative Branch>

election_year.states.alaska.executive
# <Executive Branch: Alaska State Government>


# GET SEATS UP FOR ELECTION:
election_year.federal.legislative.seats
# [<HouseSeat: Alaska U.S. House seat, at-large district>, ... ]

election_year.states.alaska.executive.seats
# [<ExecutiveSeat: Alaska Governor>, ... ]

election_year.seats.federal.senate
election_year.seats.federal.house


# FILTER BY STATE:
election_year.elections_for_state('TX')
# [<GeneralElection: Texas Nov. 06, 2018>, ... ]

election_year.federal.legislative.seats_for_state('TX')
# [<HouseSeat: Texas U.S. House seat, 1st district>, ... ]

election_year.federal.legislative.seats_for_state('TX').senate
# [<SenateSeat: Texas U.S. Senate seat, class I>]
```


#### `SenateSeat`

```python
from elections import ElectionYear

election_year = ElectionYear(2018)
seat = election_year.federal.legislative.seats.senate[0]

seat.state
# <State:Arizona>

seat.incumbent
# 'Flake, Jeff'

seat.incumbent_party
# <Party: Republican Party>

seat.senate_class
# 'I'

# etc.
```


#### `HouseSeat`

```python
from elections import ElectionYear

election_year = ElectionYear(2018)
seat = election_year.federal.legislative.seats.house[0]

seat.state
# <State:Alaska>

seat.district
#

seat.district_name
# 'at-large district'

seat.incumbent
# 'Young, Don'

seat.incumbent_party
# <Party: Republican Party>

# etc.
```


#### `GeneralElection`

```python
from elections import ElectionYear

election_year = ElectionYear(2018)
election = election_year.elections.general[0]

election.state
# <State:Alabama>

election.election_date
# datetime.datetime(2018, 11, 6, 0, 0)

election.registration_deadline
# datetime.datetime(2018, 10, 22, 0, 0)

# etc.
```


#### `PrimaryElection`

```python
from elections import ElectionYear

election_year = ElectionYear(2018)
election = election_year.elections.primary[0]

election.state
# <State:Alabama>

election.election_date
# datetime.datetime(2018, 6, 5, 0, 0)

election.gop_election_type
# 'open'

election.runoff_election_date
# datetime.datetime(2018, 7, 17, 0, 0)

# etc.
```


### Contributing data

1. Add data to one of the CSVs in the `db/` directory.
2. Build the package data files: `$ python build.py`
3. Submit a pull request!


### Influences

This project borrows most of its software design from [python-us](https://github.com/unitedstates/python-us).

Its data models are also heavily inspired by the [DNC election data project](https://github.com/democrats/data).


### Testing

```
$ pipenv install -d
$ pipenv run pytest
```


