`bdms.utils`#

Miscellaneous utilities needed by the rest of the package.

Module Contents#

A set-like data structure that supports random sampling with constant time

class bdms.utils.RandomizedSet(items=())#

A set-like data structure that supports random sampling with constant time complexity.

Example

>>> import bdms

Initialize with any iterable of hashable items.

>>> rs = bdms.utils.RandomizedSet("abc")
>>> rs
RandomizedSet('a', 'b', 'c')
>>> len(rs)
3

Add an item.

>>> rs.add('d')
>>> rs
RandomizedSet('a', 'b', 'c', 'd')
>>> len(rs)
4

Choose a random item.

>>> rs.choice(seed=0)
'd'

Remove an item.

>>> rs.remove('a')
>>> rs
RandomizedSet('d', 'b', 'c')

Iterate over the items.

>>> for item in rs:
...     print(item)
d
b
c

Reverse iterate over the items.

>>> for item in reversed(rs):
...     print(item)
c
b
d

Parameters:: items (Iterable[Hashable]) – Items to initialize the set with.

add(item)#

Add an item to the set.

remove(item)#

Remove an item from the set.

choice(seed=None)#

Randomly sample an item from the set.

Parameters:: seed (int | Generator | None) – A seed to initialize the random number generation. If None, then fresh, unpredictable entropy will be pulled from the OS. If an int, then it will be used to derive the initial state. If a numpy.random.Generator, then it will be used directly.
Returns:: The sampled item.
Return type:: Any