# Source code for baseplate.lib.random

```
"""Extensions to the standard library `random` module."""
import bisect
import random
import typing
from typing import Callable
from typing import Generic
from typing import Iterable
from typing import List
from typing import Optional
from typing import Set
from typing import TypeVar
T = TypeVar("T")
[docs]class WeightedLottery(Generic[T]):
"""A lottery where items can have different chances of selection.
Items will be picked with chance proportional to their weight relative to
the sum of all weights, so the higher the weight, the higher the chance of
being picked.
:param items: Items to choose from.
:param weight_key: A function that takes an
item in ``items`` and returns a non-negative integer
weight for that item.
:raises: :py:exc:`ValueError` if any weights are negative or there are no
items.
.. testsetup::
import random
from baseplate.lib.random import WeightedLottery
random.seed(12345)
An example of usage:
.. doctest::
>>> words = ["apple", "banana", "cantelope"]
>>> lottery = WeightedLottery(words, weight_key=len)
>>> lottery.pick()
'banana'
>>> lottery.sample(2)
['apple', 'cantelope']
"""
def __init__(self, items: Iterable[T], weight_key: Callable[[T], int]):
self.weights: List[int] = []
self.items = list(items)
if not self.items:
raise ValueError("items must not be empty")
# Build a running list of current total weight. This allows us to do a
# binary search for a random weight to get a choice quickly.
accumulated_weight = 0
for item in self.items:
weight = weight_key(item)
if weight < 0:
raise ValueError(f"weight for {item!r} must be non-negative")
accumulated_weight += weight
self.weights.append(accumulated_weight)
if accumulated_weight <= 0:
raise ValueError("at least one item must have weight")
def _pick_index(self) -> int:
winning_ticket = random.random() * self.weights[-1]
return bisect.bisect(self.weights, winning_ticket)
[docs] def pick(self) -> T:
"""Pick a random element from the lottery."""
winning_idx = self._pick_index()
return self.items[winning_idx]
[docs] def sample(self, sample_size: int) -> Iterable[T]:
"""Sample elements from the lottery without replacement.
:param sample_size: The number of items to sample from the lottery.
"""
if not 0 <= sample_size < len(self.items):
raise ValueError("sample size is negative or larger than the population")
already_picked: Set[int] = set()
results: List[Optional[T]] = [None] * sample_size
# we use indexes in the set so we don't add a hashability requirement
# to the items in the population.
for i in range(sample_size):
picked_index = self._pick_index()
while picked_index in already_picked:
picked_index = self._pick_index()
results[i] = self.items[picked_index]
already_picked.add(picked_index)
return typing.cast(List[T], results)
```