dynamic_programming.subset_generation

Functions

subset_combinations(→ list)

Compute n-element combinations from a given list using dynamic programming.

Module Contents

dynamic_programming.subset_generation.subset_combinations(elements: list[int], n: int) → list

Compute n-element combinations from a given list using dynamic programming.

Args:

• elements: The list of elements from which combinations will be generated.

• n: The number of elements in each combination.

Returns:

A list of tuples, each representing a combination of n elements.

>>> subset_combinations(elements=[10, 20, 30, 40], n=2)
[(10, 20), (10, 30), (10, 40), (20, 30), (20, 40), (30, 40)]
>>> subset_combinations(elements=[1, 2, 3], n=1)
[(1,), (2,), (3,)]
>>> subset_combinations(elements=[1, 2, 3], n=3)
[(1, 2, 3)]
>>> subset_combinations(elements=[42], n=1)
[(42,)]
>>> subset_combinations(elements=[6, 7, 8, 9], n=4)
[(6, 7, 8, 9)]
>>> subset_combinations(elements=[10, 20, 30, 40, 50], n=0)
[()]
>>> subset_combinations(elements=[1, 2, 3, 4], n=2)
[(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]
>>> subset_combinations(elements=[1, 'apple', 3.14], n=2)
[(1, 'apple'), (1, 3.14), ('apple', 3.14)]
>>> subset_combinations(elements=['single'], n=0)
[()]
>>> subset_combinations(elements=[], n=9)
[]
>>> from itertools import combinations
>>> all(subset_combinations(items, n) == list(combinations(items, n))
...     for items, n in (
...         ([10, 20, 30, 40], 2), ([1, 2, 3], 1), ([1, 2, 3], 3), ([42], 1),
...         ([6, 7, 8, 9], 4), ([10, 20, 30, 40, 50], 1), ([1, 2, 3, 4], 2),
...         ([1, 'apple', 3.14], 2), (['single'], 0), ([], 9)))
True