

def 	__a     (      A__			:  list[list[float]]       ):
    SCREAMING_SNAKE_CASE										=   []
    for data in source_data:
        for i, el in enumerate(A__       ):
            if len(A__       ) < i + 1:
                data_lists.append([]       )
            data_lists[i].append(float(A__       )       )
    return data_lists





def 	__a     (      A__			:  list[list[float]]			,  A__			:  list[int]       ):
    SCREAMING_SNAKE_CASE										=   []
    for dlist, weight in zip(A__			,  A__       ):
        SCREAMING_SNAKE_CASE										=   min(A__       )
        SCREAMING_SNAKE_CASE										=   max(A__       )

        SCREAMING_SNAKE_CASE										=   []
        # for weight 0 score is 1 - actual score
        if weight == 0:
            for item in dlist:
                try:
                    score.append(1 - ((item - mind) / (maxd - mind))       )
                except ZeroDivisionError:
                    score.append(1       )

        elif weight == 1:
            for item in dlist:
                try:
                    score.append((item - mind) / (maxd - mind)       )
                except ZeroDivisionError:
                    score.append(0       )

        # weight not 0 or 1
        else:
            SCREAMING_SNAKE_CASE										=   F"Invalid weight of {weight:f} provided"
            raise ValueError(A__       )

        score_lists.append(A__       )

    return score_lists





def 	__a     (      A__			:  list[list[float]]       ):
    SCREAMING_SNAKE_CASE										=   [0 for i in range(len(score_lists[0]       )       )]

    for slist in score_lists:
        for j, ele in enumerate(A__       ):
            SCREAMING_SNAKE_CASE										=   final_scores[j] + ele

    return final_scores





def 	__a     (      A__			:  list[list[float]]			,  A__			:  list[int]       ):
    SCREAMING_SNAKE_CASE										=   get_data(A__       )
    SCREAMING_SNAKE_CASE										=   calculate_each_score(A__			,  A__       )
    SCREAMING_SNAKE_CASE										=   generate_final_scores(A__       )

    # append scores to source data
    for i, ele in enumerate(A__       ):
        source_data[i].append(A__       )

    return source_data


from __future__ import annotations





def 	__a     (      A__			:  list[int | str]       ):
    create_state_space_tree(A__			,  []			,  0			,  [0 for i in range(len(A__       )       )]       )





def 	__a     (      A__			:  list[int | str]			,  A__			:  list[int | str]			,  A__			:  int			,  A__			:  list[int]			,  ):

    if index == len(A__       ):
        print(A__       )
        return

    for i in range(len(A__       )       ):
        if not index_used[i]:
            current_sequence.append(sequence[i]       )
            SCREAMING_SNAKE_CASE										=   True
            create_state_space_tree(A__			,  A__			,  index + 1			,  A__       )
            current_sequence.pop()
            SCREAMING_SNAKE_CASE										=   False
__A			:					list[int | str]						=			[3, 1, 2, 4]
generate_all_permutations(sequence)

__A			:					list[int | str]						=			["A", "B", "C"]





generate_all_permutations(sequence_a)