'''simple docstring'''





from random import randint
from tempfile import TemporaryFile

import numpy as np
def 						__A							(     UpperCAmelCase     ,UpperCAmelCase     ,UpperCAmelCase					)     ->			List[str]:




						'''simple docstring'''
						_UpperCamelCase			:			int   			=						0
						if start < end:
												_UpperCamelCase			:			List[str]   			=						randint(UpperCAmelCase     ,UpperCAmelCase					)
												_UpperCamelCase			:			str   			=						a[end]
												_UpperCamelCase			:			Dict   			=						a[pivot]
												_UpperCamelCase			:			str   			=						temp

												_UpperCamelCase			,       _UpperCamelCase			:			List[Any]   			=						_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							(     UpperCAmelCase     ,UpperCAmelCase     ,UpperCAmelCase					)     ->			Optional[int]:




						'''simple docstring'''
						_UpperCamelCase			:			Optional[Any]   			=						0
						_UpperCamelCase			:			Optional[int]   			=						randint(UpperCAmelCase     ,UpperCAmelCase					)
						_UpperCamelCase			:			Dict   			=						a[end]
						_UpperCamelCase			:			int   			=						a[pivot]
						_UpperCamelCase			:			str   			=						temp
						_UpperCamelCase			:			Any   			=						start - 1
						for index in range(UpperCAmelCase     ,UpperCAmelCase					):
												count += 1
												if a[index] < a[end]:  # check if current val is less than pivot value
																		_UpperCamelCase			:			List[Any]   			=						new_pivot_index + 1
																		_UpperCamelCase			:			str   			=						a[new_pivot_index]
																		_UpperCamelCase			:			List[Any]   			=						a[index]
																		_UpperCamelCase			:			Optional[Any]   			=						temp

						_UpperCamelCase			:			int   			=						a[new_pivot_index + 1]
						_UpperCamelCase			:			Any   			=						a[end]
						_UpperCamelCase			:			str   			=						temp
						return new_pivot_index + 1, count


lowerCAmelCase_	:		List[Any]			=     TemporaryFile()
lowerCAmelCase_	:		List[str]			=     100  # 1000 elements are to be sorted


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


outfile.seek(0)  # using the same array
lowerCAmelCase_	:		List[Any]			=     np.load(outfile)
lowerCAmelCase_	:		str			=     len(M) - 1
lowerCAmelCase_	:		str			=     _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'''





import requests
from bsa import BeautifulSoup
def 						__A							(     UpperCAmelCase     ,UpperCAmelCase					)     ->			str:




						'''simple docstring'''
						_UpperCamelCase			:			Dict   			=						BeautifulSoup(requests.get(UpperCAmelCase     ,params=UpperCAmelCase					).content     ,"html.parser"					)
						_UpperCamelCase			:			Union[str, Any]   			=						soup.find("div"     ,attrs={"class": "gs_ri"}					)
						_UpperCamelCase			:			Optional[Any]   			=						div.find("div"     ,attrs={"class": "gs_fl"}					).find_all("a"					)
						return anchors[2].get_text()


if __name__ == "__main__":
			lowerCAmelCase_	:		Optional[int]			=     {
			    """title""": (
			        """Precisely geometry controlled microsupercapacitors for ultrahigh areal """
			        """capacitance, volumetric capacitance, and energy density"""
			    ),
			    """journal""": """Chem. Mater.""",
			    """volume""": 30,
			    """pages""": """3979-3990""",
			    """year""": 2018,
			    """hl""": """en""",
			}
			print(get_citation("""https://scholar.google.com/scholar_lookup""", params=params))


