
"""simple docstring"""





from random import randint
from tempfile import TemporaryFile

import numpy as np



def 		_lowerCAmelCase							(							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_							):
		__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 		_lowerCAmelCase							(							UpperCamelCase_    ,							UpperCamelCase_    ,							UpperCamelCase_							):
		__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


__magic_name__			=     TemporaryFile()
__magic_name__			=     100  # 1000 elements are to be sorted


__magic_name__,				__magic_name__			=     0, 1  # mean and standard deviation
__magic_name__			=     np.random.normal(mu, sigma, p)
np.save(outfile, X)
print("The array is")
print(X)


outfile.seek(0)  # using the same array
__magic_name__			=     np.load(outfile)
__magic_name__			=     len(M) - 1
__magic_name__			=     _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"""
from __future__ import annotations

from collections.abc import Generator





def 				lowercase__		(					):
				_SCREAMING_SNAKE_CASE   :		dict[int, int]       		=    {}
				_SCREAMING_SNAKE_CASE   :		List[Any]       		=    2
				while True:
								_SCREAMING_SNAKE_CASE   :		List[Any]       		=    factor_map.pop(lowerCamelCase,						lowerCamelCase       )
								if factor:
												_SCREAMING_SNAKE_CASE   :		str       		=    factor + prime
												while x in factor_map:
																x += factor
												_SCREAMING_SNAKE_CASE   :		Union[str, Any]       		=    factor
								else:
												_SCREAMING_SNAKE_CASE   :		Optional[int]       		=    prime
												yield prime
								prime += 1





def 				lowercase__		(					lowerCamelCase = 1E10       ):
				_SCREAMING_SNAKE_CASE   :		Dict       		=    sieve()

				_SCREAMING_SNAKE_CASE   :		Dict       		=    1
				while True:
								_SCREAMING_SNAKE_CASE   :		int       		=    next(lowerCamelCase       )
								if (2 * prime * n) > limit:
												return n
								# Ignore the next prime as the reminder will be 2.
								next(lowerCamelCase       )
								n += 2


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

