

'''simple docstring'''



from random import randint
from tempfile import TemporaryFile

import numpy as np







def   a__			(    a__ ,       a__ ,       a__		):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE      = 0
     if start < end:
          __SCREAMING_SNAKE_CASE      = randint(UpperCAmelCase_ ,       UpperCAmelCase_		)
          __SCREAMING_SNAKE_CASE      = a[end]
          __SCREAMING_SNAKE_CASE      = a[pivot]
          __SCREAMING_SNAKE_CASE      = temp

          __SCREAMING_SNAKE_CASE      = _in_place_partition(UpperCAmelCase_ ,       UpperCAmelCase_ ,       UpperCAmelCase_		)
          count += _in_place_quick_sort(UpperCAmelCase_ ,       UpperCAmelCase_ ,       p - 1		)
          count += _in_place_quick_sort(UpperCAmelCase_ ,       p + 1 ,       UpperCAmelCase_		)
     return count







def   a__			(    a__ ,       a__ ,       a__		):




     """simple docstring"""


     __SCREAMING_SNAKE_CASE      = 0
     __SCREAMING_SNAKE_CASE      = randint(UpperCAmelCase_ ,       UpperCAmelCase_		)
     __SCREAMING_SNAKE_CASE      = a[end]
     __SCREAMING_SNAKE_CASE      = a[pivot]
     __SCREAMING_SNAKE_CASE      = temp
     __SCREAMING_SNAKE_CASE      = start - 1
     for index in range(UpperCAmelCase_ ,       UpperCAmelCase_		):
          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


UpperCAmelCase					:			Union[str, Any]       =	TemporaryFile()
UpperCAmelCase					:			Tuple       =	1_0_0  # 1000 elements are to be sorted


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


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

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



print(z)











'''simple docstring'''
def A__       (	UpperCAmelCase_ = 6_0_0_8_5_1_4_7_5_1_4_3				):

						try:
												_UpperCamelCase   :						str												=  int(UpperCAmelCase_				)
						except (TypeError, ValueError):
												raise TypeError('Parameter n must be int or castable to int.'				)
						if n <= 0:
												raise ValueError('Parameter n must be greater than or equal to one.'				)
						_UpperCamelCase   :						int												=  1
						_UpperCamelCase   :						Optional[Any]												=  2
						while i * i <= n:
												while n % i == 0:
																		_UpperCamelCase   :						Union[str, Any]												=  i
																		n //= i
												i += 1
						if n > 1:
												_UpperCamelCase   :						Dict												=  n
						return int(UpperCAmelCase_				)


if __name__ == "__main__":
					print(F"""{solution() = }""")


