



class 		_lowercase		:

   def __init__(      self			:       Dict							,   __lowerCAmelCase			:       Union[str, Any]							,   __lowerCAmelCase			:       Union[str, Any]							,   __lowerCAmelCase			:       int							)       ->				int:


    """simple docstring"""






    a						=		None
    a						=		None
    a						=		graph

    self._normalize_graph(__lowerCAmelCase							,   __lowerCAmelCase							)
    a						=		len(__lowerCAmelCase							)
    a						=		None

   def 		A							(      self			:       Tuple							,   __lowerCAmelCase			:       Union[str, Any]							,   __lowerCAmelCase			:       List[str]							)       ->				List[Any]:


    """simple docstring"""






    if sources is int:
     a						=		[sources]
    if sinks is int:
     a						=		[sinks]

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

    a						=		sources[0]
    a						=		sinks[0]

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

     a						=		len(self.graph							) + 1
     for room in self.graph:
      room.insert(0							,   0							)
     self.graph.insert(0							,   [0] * size							)
     for i in sources:
      a						=		max_input_flow
     a						=		0

     a						=		len(self.graph							) + 1
     for room in self.graph:
      room.append(0							)
     self.graph.append([0] * size							)
     for i in sinks:
      a						=		max_input_flow
     a						=		size - 1

   def 		A							(      self			:       Any							)       ->				Tuple:


    """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 		A							(      self			:       Optional[int]							,   __lowerCAmelCase			:       int							)       ->				int:


    """simple docstring"""






    a						=		algorithm(self							)



class 		_lowercase		:

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


    """simple docstring"""






    a						=		flow_network
    a						=		flow_network.verticesCount
    a						=		flow_network.sourceIndex
    a						=		flow_network.sinkIndex
    # it's just a reference, so you shouldn't change
    # it in your algorithms, use deep copy before doing that
    a						=		flow_network.graph
    a						=		False

   def 		A							(      self			:       Any							)       ->				Dict:


    """simple docstring"""






    if not self.executed:
     self._algorithm()
     a						=		True




   def 		A							(      self			:       Any							)       ->				Tuple:


    """simple docstring"""






    pass



class 		_lowercase		(       UpperCAmelCase__	):

   def __init__(      self			:       Dict							,   __lowerCAmelCase			:       List[str]							)       ->				Optional[int]:


    """simple docstring"""






    super().__init__(__lowerCAmelCase							)
    # use this to save your result
    a						=		-1




   def 		A							(      self			:       Any							)       ->				List[str]:


    """simple docstring"""






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

    return self.maximum_flow



class 		_lowercase		(       UpperCAmelCase__	):

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


    """simple docstring"""






    super().__init__(__lowerCAmelCase							)

    a						=		[[0] * self.verticies_count for i in range(self.verticies_count							)]

    a						=		[0] * self.verticies_count
    a						=		[0] * self.verticies_count

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


    """simple docstring"""






    a						=		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
    a						=		[
        i
        for i in range(self.verticies_count							)
        if i != self.source_index and i != self.sink_index
    ]

    # move through list
    a						=		0
    while i < len(__lowerCAmelCase							):
     a						=		vertices_list[i]
     a						=		self.heights[vertex_index]
     self.process_vertex(__lowerCAmelCase							)
     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(__lowerCAmelCase							)							)
      a						=		0
     else:
      i += 1

    a						=		sum(self.preflow[self.source_index]							)

   def 		A							(      self			:       int							,   __lowerCAmelCase			:       Union[str, Any]							)       ->				Optional[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(__lowerCAmelCase							,   __lowerCAmelCase							)

     self.relabel(__lowerCAmelCase							)

   def 		A							(      self			:       List[Any]							,   __lowerCAmelCase			:       Optional[int]							,   __lowerCAmelCase			:       Any							)       ->				List[str]:


    """simple docstring"""






    a						=		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 		A							(      self			:       Any							,   __lowerCAmelCase			:       str							)       ->				int:


    """simple docstring"""






    a						=		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):
      a						=		self.heights[to_index]

    if min_height is not None:
     a						=		min_height + 1


if __name__ == "__main__":
     A_		:     str        =     [0]
     A_		:     Union[str, Any]        =     [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],
     # ]
     A_		:     Union[str, Any]        =     [[0, 7, 0, 0], [0, 0, 6, 0], [0, 0, 0, 8], [9, 0, 0, 0]]

     # prepare our network
     A_		:     int        =     FlowNetwork(graph, entrances, exits)
     # set algorithm
     flow_network.set_maximum_flow_algorithm(PushRelabelExecutor)
     # and calculate
     A_		:     Any        =     flow_network.find_maximum_flow()

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






import re
from pathlib import Path
from unittest import TestCase

import pytest



@pytest.mark.integration
class 		_lowercase		(       UpperCAmelCase__	):

   def 		A							(      self			:       Optional[int]							,   __lowerCAmelCase			:       str							)       ->				Union[str, Any]:


    """simple docstring"""






    with open(__lowerCAmelCase							,   encoding="utf-8"							) as input_file:
     a						=		re.compile(R"(?!.*\b(?:encoding|rb|w|wb|w+|wb+|ab|ab+)\b)(?<=\s)(open)\((.*)\)"							)
     a						=		input_file.read()
     a						=		regexp.search(__lowerCAmelCase							)

    return match

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


    """simple docstring"""






    with open(__lowerCAmelCase							,   encoding="utf-8"							) as input_file:
     a						=		re.compile(R"#[^\r\n]*print\(|\"[^\r\n]*print\(|\"\"\".*?print\(.*?\"\"\"|(print\()"							,   re.DOTALL							)
     a						=		input_file.read()
     # use `re.finditer` to handle the case where the ignored groups would be matched first by `re.search`
     a						=		regexp.finditer(__lowerCAmelCase							)

    a						=		[match for match in matches if match is not None and match.group(1							) is not None]
    return matches[0] if matches else None

   def 		A							(      self			:       List[str]							)       ->				List[Any]:


    """simple docstring"""






    a						=		Path("./datasets"							)
    a						=		list(dataset_paths.absolute().glob("**/*.py"							)							)

    for dataset in dataset_files:
     if self._no_encoding_on_file_open(str(__lowerCAmelCase							)							):
      raise AssertionError(f"""open(...) must use utf-8 encoding in {dataset}"""							)




   def 		A							(      self			:       Tuple							)       ->				Union[str, Any]:


    """simple docstring"""






    a						=		Path("./datasets"							)
    a						=		list(dataset_paths.absolute().glob("**/*.py"							)							)

    for dataset in dataset_files:
     if self._no_print_statements(str(__lowerCAmelCase							)							):
      raise AssertionError(f"""print statement found in {dataset}. Use datasets.logger/logging instead."""							)

