Add an example to the random docs.

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Raymond Hettinger 2010-12-02 02:41:33 +00:00
parent c74d518e73
commit 2fdc7b1f75
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@ -295,3 +295,29 @@ change across Python versions, but two aspects are guaranteed not to change:
* The generator's :meth:`random` method will continue to produce the same
sequence when the compatible seeder is given the same seed.
.. _random-examples:
Examples and Recipes
====================
A common task is to make a :func:`random.choice` with weighted probababilites.
If the weights are small integer ratios, a simple technique is to build a sample
population with repeats::
>>> weighted_choices = [('Red', 3), ('Blue', 2), ('Yellow', 1), ('Green', 4)]
>>> population = [val for val, cnt in weighted_choices for i in range(cnt)]
>>> random.choice(population)
'Green'
A more general approach is to arrange the weights in a cumulative probability
distribution with :func:`itertools.accumulate`, and then locate the random value
with :func:`bisect.bisect`::
>>> choices, weights = zip(*weighted_choices)
>>> cumdist = list(itertools.accumulate(weights))
>>> x = random.random() * cumdist[-1]
>>> choices[bisect.bisect(cumdist, x)]
'Blue'