

from random import randint
from tempfile import TemporaryFile

import numpy as np





def 	__a     (      A__			:  str			,  A__			:  List[Any]			,  A__			:  List[Any]       ):
    SCREAMING_SNAKE_CASE										=   0
    if start < end:
        SCREAMING_SNAKE_CASE										=   randint(A__			,  A__       )
        SCREAMING_SNAKE_CASE										=   a[end]
        SCREAMING_SNAKE_CASE										=   a[pivot]
        SCREAMING_SNAKE_CASE										=   temp

        SCREAMING_SNAKE_CASE							,	SCREAMING_SNAKE_CASE										=   _in_place_partition(A__			,  A__			,  A__       )
        count += _in_place_quick_sort(A__			,  A__			,  p - 1       )
        count += _in_place_quick_sort(A__			,  p + 1			,  A__       )
    return count





def 	__a     (      A__			:  Optional[Any]			,  A__			:  List[str]			,  A__			:  List[str]       ):
    SCREAMING_SNAKE_CASE										=   0
    SCREAMING_SNAKE_CASE										=   randint(A__			,  A__       )
    SCREAMING_SNAKE_CASE										=   a[end]
    SCREAMING_SNAKE_CASE										=   a[pivot]
    SCREAMING_SNAKE_CASE										=   temp
    SCREAMING_SNAKE_CASE										=   start - 1
    for index in range(A__			,  A__       ):
        count += 1
        if a[index] < a[end]:  # check if current val is less than pivot value
            SCREAMING_SNAKE_CASE										=   new_pivot_index + 1
            SCREAMING_SNAKE_CASE										=   a[new_pivot_index]
            SCREAMING_SNAKE_CASE										=   a[index]
            SCREAMING_SNAKE_CASE										=   temp

    SCREAMING_SNAKE_CASE										=   a[new_pivot_index + 1]
    SCREAMING_SNAKE_CASE										=   a[end]
    SCREAMING_SNAKE_CASE										=   temp
    return new_pivot_index + 1, count


__A			:					Optional[int]						=			TemporaryFile()
__A			:					Dict						=			1_0_0  # 1000 elements are to be sorted


__A			, __A			:					Optional[int]						=			0, 1  # mean and standard deviation
__A			:					Dict						=			np.random.normal(mu, sigma, p)
np.save(outfile, X)
print('The array is')
print(X)


outfile.seek(0)  # using the same array
__A			:					Union[str, Any]						=			np.load(outfile)
__A			:					Any						=			len(M) - 1
__A			:					Optional[Any]						=			_in_place_quick_sort(M, 0, r)

print(
    'No of Comparisons for 100 elements selected from a standard normal distribution'
    'is :'
)





print(z)


import os





def 	__a     (      ):
    SCREAMING_SNAKE_CASE										=   os.path.join(os.path.dirname(A__       )			,  "num.txt"       )
    with open(A__       ) as file_hand:
        return str(sum(int(A__       ) for line in file_hand       )       )[:10]


if __name__ == "__main__":
    print(solution())