from aocd.models import Puzzle
from aocd import submit


def find_overlaps(sets: list) -> int:
    overlaps = [1 if set.intersection(*pair) else 0 for pair in sets]
    return sum(overlaps)


def find_subsets(sets: list) -> int:
    """
    count the number of sets that fully contain each other
    """
    subsets = [
        1 if pair[0].issubset(pair[1]) or pair[1].issubset(pair[0]) else 0
        for pair in sets
    ]
    return sum(subsets)


def parse_input(data: list) -> list:
    """
    parses the input data and generates a list of set tuples
    """
    # get a list of section pairs
    sections = [sections.split(",") for sections in data.split("\n")]

    # generate a list of section set pairs
    sets = list()
    for pair in sections:
        a, b = pair[0].split("-")
        c, d = pair[1].split("-")
        a, b, c, d = int(a), int(b), int(c), int(d)
        sets.append([set(range(a, b + 1)), set(range(c, d + 1))])
    return sets


if __name__ == "__main__":
    # get puzzle and parse data
    puzzle = Puzzle(year=2022, day=4)
    sections = parse_input(puzzle.input_data)

    # part a: find the number of sections that fully contain each other
    answer_a = find_subsets(sections)
    print(f"sum of priorities of all common items amongst compartments: {answer_a}")
    submit(answer_a, part="a", day=4, year=2022)

    # part b: determine the priority of common items in groups of three and create a priority summary
    answer_b = find_overlaps(sections)
    print(f"sum of priorities of all common items amongst groups of three: {answer_b}")
    submit(answer_b, part="b", day=4, year=2022)