



"""simple docstring"""






class 			A__   :




	'''simple docstring'''





	def __init__(     self:		List[Any]       ,			_SCREAMING_SNAKE_CASE:		int       ,			_SCREAMING_SNAKE_CASE:		Optional[int]       ,			_SCREAMING_SNAKE_CASE:		List[Any])				->       List[Any]:

				"""simple docstring"""

				__lowerCAmelCase      :  Tuple												=       None
				__lowerCAmelCase      :  List[str]												=       None
				__lowerCAmelCase      :  Union[str, Any]												=       graph

				self._normalize_graph(_SCREAMING_SNAKE_CASE       ,			_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase      :  List[Any]												=       len(_SCREAMING_SNAKE_CASE)
				__lowerCAmelCase      :  List[str]												=       None

	def 							_SCREAMING_SNAKE_CASE   (     self:		str       ,			_SCREAMING_SNAKE_CASE:		Dict       ,			_SCREAMING_SNAKE_CASE:		List[Any])				->       Any:

				"""simple docstring"""

				if sources is int:
							__lowerCAmelCase      :  List[Any]												=       [sources]
				if sinks is int:
							__lowerCAmelCase      :  List[Any]												=       [sinks]

				if len(_SCREAMING_SNAKE_CASE) == 0 or len(_SCREAMING_SNAKE_CASE) == 0:
							return

				__lowerCAmelCase      :  Optional[Any]												=       sources[0]
				__lowerCAmelCase      :  Union[str, Any]												=       sinks[0]

				# make fake vertex if there are more
				# than one source or sink
				if len(_SCREAMING_SNAKE_CASE) > 1 or len(_SCREAMING_SNAKE_CASE) > 1:
							__lowerCAmelCase      :  int												=       0
							for i in sources:
										max_input_flow += sum(self.graph[i])

							__lowerCAmelCase      :  Dict												=       len(self.graph) + 1
							for room in self.graph:
										room.insert(0       ,			0)
							self.graph.insert(0       ,			[0] * size)
							for i in sources:
										__lowerCAmelCase      :  Optional[Any]												=       max_input_flow
							__lowerCAmelCase      :  Optional[int]												=       0

							__lowerCAmelCase      :  Dict												=       len(self.graph) + 1
							for room in self.graph:
										room.append(0)
							self.graph.append([0] * size)
							for i in sinks:
										__lowerCAmelCase      :  List[str]												=       max_input_flow
							__lowerCAmelCase      :  Any												=       size - 1

	def 							_SCREAMING_SNAKE_CASE   (     self:		int)				->       Any:

				"""simple docstring"""

				if self.maximum_flow_algorithm is None:
							raise Exception("You need to set maximum flow algorithm before.")
				if self.source_index is None or self.sink_index is None:
							return 0

				self.maximum_flow_algorithm.execute()
				return self.maximum_flow_algorithm.getMaximumFlow()







	def 							_SCREAMING_SNAKE_CASE   (     self:		Any       ,			_SCREAMING_SNAKE_CASE:		Dict)				->       List[Any]:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[int]												=       algorithm(self)






class 			A__   :




	'''simple docstring'''





	def __init__(     self:		int       ,			_SCREAMING_SNAKE_CASE:		int)				->       Any:

				"""simple docstring"""

				__lowerCAmelCase      :  List[str]												=       flow_network
				__lowerCAmelCase      :  Optional[int]												=       flow_network.verticesCount
				__lowerCAmelCase      :  List[Any]												=       flow_network.sourceIndex
				__lowerCAmelCase      :  int												=       flow_network.sinkIndex
				# it's just a reference, so you shouldn't change
				# it in your algorithms, use deep copy before doing that
				__lowerCAmelCase      :  Any												=       flow_network.graph
				__lowerCAmelCase      :  List[str]												=       False

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple)				->       Any:

				"""simple docstring"""

				if not self.executed:
							self._algorithm()
							__lowerCAmelCase      :  Optional[Any]												=       True







	def 							_SCREAMING_SNAKE_CASE   (     self:		int)				->       List[str]:

				"""simple docstring"""

				pass






class 			A__   (  __SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	def __init__(     self:		str       ,			_SCREAMING_SNAKE_CASE:		str)				->       Optional[int]:

				"""simple docstring"""

				super().__init__(_SCREAMING_SNAKE_CASE)
				# use this to save your result
				__lowerCAmelCase      :  Optional[Any]												=       -1







	def 							_SCREAMING_SNAKE_CASE   (     self:		List[Any])				->       List[Any]:

				"""simple docstring"""

				if not self.executed:
							raise Exception("You should execute algorithm before using its result!")

				return self.maximum_flow






class 			A__   (  __SCREAMING_SNAKE_CASE							):




	'''simple docstring'''





	def __init__(     self:		Union[str, Any]       ,			_SCREAMING_SNAKE_CASE:		str)				->       List[str]:

				"""simple docstring"""

				super().__init__(_SCREAMING_SNAKE_CASE)

				__lowerCAmelCase      :  List[Any]												=       [[0] * self.verticies_count for i in range(self.verticies_count)]

				__lowerCAmelCase      :  Tuple												=       [0] * self.verticies_count
				__lowerCAmelCase      :  int												=       [0] * self.verticies_count

	def 							_SCREAMING_SNAKE_CASE   (     self:		Tuple)				->       Optional[int]:

				"""simple docstring"""

				__lowerCAmelCase      :  Optional[int]												=       self.verticies_count

				# push some substance to graph
				for nextvertex_index, bandwidth in enumerate(self.graph[self.source_index]):
							self.preflow[self.source_index][nextvertex_index] += bandwidth
							self.preflow[nextvertex_index][self.source_index] -= bandwidth
							self.excesses[nextvertex_index] += bandwidth

				# Relabel-to-front selection rule
				__lowerCAmelCase      :  Dict												=       [
				    i
				    for i in range(self.verticies_count)
				    if i != self.source_index and i != self.sink_index
				]

				# move through list
				__lowerCAmelCase      :  Tuple												=       0
				while i < len(_SCREAMING_SNAKE_CASE):
							__lowerCAmelCase      :  List[Any]												=       vertices_list[i]
							__lowerCAmelCase      :  Union[str, Any]												=       self.heights[vertex_index]
							self.process_vertex(_SCREAMING_SNAKE_CASE)
							if self.heights[vertex_index] > previous_height:
										# if it was relabeled, swap elements
										# and start from 0 index
										vertices_list.insert(0       ,			vertices_list.pop(_SCREAMING_SNAKE_CASE))
										__lowerCAmelCase      :  Dict												=       0
							else:
										i += 1

				__lowerCAmelCase      :  Tuple												=       sum(self.preflow[self.source_index])

	def 							_SCREAMING_SNAKE_CASE   (     self:		Dict       ,			_SCREAMING_SNAKE_CASE:		Union[str, Any])				->       Union[str, Any]:

				"""simple docstring"""

				while self.excesses[vertex_index] > 0:
							for neighbour_index in range(self.verticies_count):
										# if it's neighbour and current vertex is higher
										if (
										    self.graph[vertex_index][neighbour_index]
										    - self.preflow[vertex_index][neighbour_index]
										    > 0
										    and self.heights[vertex_index] > self.heights[neighbour_index]
										):
													self.push(_SCREAMING_SNAKE_CASE       ,			_SCREAMING_SNAKE_CASE)

							self.relabel(_SCREAMING_SNAKE_CASE)

	def 							_SCREAMING_SNAKE_CASE   (     self:		Optional[int]       ,			_SCREAMING_SNAKE_CASE:		Optional[int]       ,			_SCREAMING_SNAKE_CASE:		Tuple)				->       Dict:

				"""simple docstring"""

				__lowerCAmelCase      :  List[str]												=       min(
				    self.excesses[from_index]       ,			self.graph[from_index][to_index] - self.preflow[from_index][to_index]       ,			)
				self.preflow[from_index][to_index] += preflow_delta
				self.preflow[to_index][from_index] -= preflow_delta
				self.excesses[from_index] -= preflow_delta
				self.excesses[to_index] += preflow_delta







	def 							_SCREAMING_SNAKE_CASE   (     self:		List[Any]       ,			_SCREAMING_SNAKE_CASE:		List[Any])				->       int:

				"""simple docstring"""

				__lowerCAmelCase      :  List[Any]												=       None
				for to_index in range(self.verticies_count):
							if (
							    self.graph[vertex_index][to_index]
							    - self.preflow[vertex_index][to_index]
							    > 0
							) and (min_height is None or self.heights[to_index] < min_height):
										__lowerCAmelCase      :  Optional[int]												=       self.heights[to_index]

				if min_height is not None:
							__lowerCAmelCase      :  List[str]												=       min_height + 1


if __name__ == "__main__":
	__snake_case							:   Tuple      =    [0]
	__snake_case							:   Tuple      =    [3]
	# graph = [
	#     [0, 0, 4, 6, 0, 0],
	#     [0, 0, 5, 2, 0, 0],
	#     [0, 0, 0, 0, 4, 4],
	#     [0, 0, 0, 0, 6, 6],
	#     [0, 0, 0, 0, 0, 0],
	#     [0, 0, 0, 0, 0, 0],
	# ]
	__snake_case							:   int      =    [[0, 7, 0, 0], [0, 0, 6, 0], [0, 0, 0, 8], [9, 0, 0, 0]]

	# prepare our network
	__snake_case							:   List[Any]      =    FlowNetwork(graph, entrances, exits)
	# set algorithm
	flow_network.set_maximum_flow_algorithm(PushRelabelExecutor)
	# and calculate
	__snake_case							:   Any      =    flow_network.find_maximum_flow()

	print(F"""maximum flow is {maximum_flow}""")




"""simple docstring"""






from itertools import zip_longest

import requests
from bsa import BeautifulSoup
from pandas import DataFrame


def 			_lowercase				(  __snake_case = "laptop"	)						->   DataFrame:
			__lowerCAmelCase      :  str												=       F"""https://www.amazon.in/laptop/s?k={product}"""
			__lowerCAmelCase      :  Union[str, Any]												=       {
			    "User-Agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36\n        (KHTML, like Gecko)Chrome/44.0.2403.157 Safari/537.36",
			    "Accept-Language": "en-US, en;q=0.5",
			}
			__lowerCAmelCase      :  List[str]												=       BeautifulSoup(requests.get(__snake_case					,headers=__snake_case	).text	)
			# Initialize a Pandas dataframe with the column titles
			__lowerCAmelCase      :  Dict												=       DataFrame(
			    columns=[
			        "Product Title",
			        "Product Link",
			        "Current Price of the product",
			        "Product Rating",
			        "MRP of the product",
			        "Discount",
			    ]	)
			# Loop through each entry and store them in the dataframe
			for item, _ in zip_longest(
			    soup.find_all(
			        "div"					,attrs={"class": "s-result-item", "data-component-type": "s-search-result"}					,)					,soup.find_all("div"					,attrs={"class": "a-row a-size-base a-color-base"}	)					,):
						try:
									__lowerCAmelCase      :  Any												=       item.ha.text
									__lowerCAmelCase      :  Union[str, Any]												=       "https://www.amazon.in/" + item.ha.a["href"]
									__lowerCAmelCase      :  Any												=       item.find("span"					,attrs={"class": "a-offscreen"}	).text
									try:
												__lowerCAmelCase      :  Union[str, Any]												=       item.find("span"					,attrs={"class": "a-icon-alt"}	).text
									except AttributeError:
												__lowerCAmelCase      :  Optional[Any]												=       "Not available"
									try:
												__lowerCAmelCase      :  Union[str, Any]												=       (
												    "₹"
												    + item.find(
												        "span"					,attrs={"class": "a-price a-text-price"}	).text.split("₹"	)[1]
												)
									except AttributeError:
												__lowerCAmelCase      :  Dict												=       ""
									try:
												__lowerCAmelCase      :  str												=       float(
												    (
												        (
												            float(product_mrp.strip("₹"	).replace(","					,""	)	)
												            - float(product_price.strip("₹"	).replace(","					,""	)	)
												        )
												        / float(product_mrp.strip("₹"	).replace(","					,""	)	)
												    )
												    * 100	)
									except ValueError:
												__lowerCAmelCase      :  List[str]												=       float("nan"	)
						except AttributeError:
									pass
						__lowerCAmelCase      :  int												=       [
						    product_title,
						    product_link,
						    product_price,
						    product_rating,
						    product_mrp,
						    discount,
						]
			__lowerCAmelCase      :  Union[str, Any]												=       " "
			__lowerCAmelCase      :  Union[str, Any]												=       " "
			data_frame.index += 1
			return data_frame


if __name__ == "__main__":
	__snake_case							:   Any      =    'headphones'
	get_amazon_product_data(product).to_csv(F"""Amazon Product Data for {product}.csv""")