https://github.com/timclicks/choices

for making random decisions
https://github.com/timclicks/choices

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for making random decisions

• Host: GitHub
• URL: https://github.com/timclicks/choices
• Owner: timClicks
• Created: 2012-02-25T06:46:02.000Z (almost 13 years ago)
• Default Branch: master
• Last Pushed: 2014-11-25T09:15:56.000Z (about 10 years ago)
• Last Synced: 2025-01-19T11:15:12.711Z (7 days ago)
• Language: Python
• Homepage:
• Size: 174 KB
• Stars: 21
• Watchers: 3
• Forks: 1
• Open Issues: 3
• Metadata Files:
  • Readme: README

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README

        
choices is designed to make it easy to make it easy to

make things happen in a probabilistic manner. Its main

API is the Choice class.

When called, a Choice object will return one of its keys

according to the proability it has been assigned.

Here's an example:

    >>> mood = Choice({'happy': 0.3, 'neutral': 0.6, 'sad': 0.1})

    >>> mood()

    'happy'

    >>> mood()

    'neutral'

    >>> mood()

    'neutral'

Creating a Choice object

========================

There are three main ways for creating a Choice object:

- a dict of keys and probabilities

- a list of (key, probability) pairs

- a list of (key, sample_count) pairs

Each of those options is explained below.

A dict of keys and probabilities

--------------------------------

Perhaps the simplest way to create a Choice is to

provide the keys and associated probability wrapped

up as a dict:

    >>> mood = Choice({'happy': 0.3, 'neutral': 0.6, 'sad': 0.1})

    >>> mood()

    'happy'

    >>> mood()

    'neutral'

A list of (key, probability) pairs

----------------------------------

As well as a dict assigning a probability to each key, you can

send in a list of (key,value) pairs as lists or tuples. This

allows for lots of flexibility, including non-hashable

types to be used. This means that you can provide objects such

as functions to be used as keys.

Let's say we wanted to create an NPC for a game and wanted

some scripted responses. Why not encode moods as functions

and then pass them togetheer as a Choice.

    >>> def grumpy(news):

    ... return ':/'

    >>> def happy(news):

    ... return ':)'

    >>> react = Choice([(grumpy, 0.7), (happy, 0.3)])

    >>> reaction = react()

    >>> reaction("We're getting married!")

    ':/'

A list of (key, sample_count) pairs

-----------------------------------

You are not restricted to adding p to 1. If you only have samples,

and wish to calculate a probablilty distribution, you can provide

those too:

    >>> birds_spotted = {'geese': 0, 'ducks': 12, 'sparrows': 4, 'other': 39}

    >>> birds = Choice(birds_spotted)

    >>> birds.distribution

    [('geese', 0.0), ('sparrows', 0.07272727272727272), ('ducks', 0.21818181818181817), ('other', 0.7090909090909091)]

Usage

=====

Making decisions

----------------

To return a new value, simply call the Choice object.

    >>> where_to_go = Choice({"Paris": 0.4, "London": 0.4, "Copenhagen": 0.1, "Barcelona": 0.1 })

    >>> where_to_go()

    'Copenhagen'

Finding probabilities

---------------------

You can retrieve the distribution of how those values are applied

by accessing the distribution attribute:

    >>> mood.distribution

    [('happy', 0.3), ('neutral', 0.6), ('sad', 0.1)]

    >>> where_to_go.distribution

    [('Paris': 0.4), ('London', 0.4), ('Copenhagen', 0.1), ('Barcelona', 0.1)]

Retrieving the probability of a particular key is supported:

    >>> birds['geese']

    0.0