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У меня проблема с получением файла из входного html и передачей его в качестве входного в алгоритме python для отображения графиков, я использую flask, и алгоритмы, которые я хочу запустить, находятся в algo_kruskal_final и algo_prim_final, это мой каталог под названием интерфейс.

Это мое app.py:

 from flask import Flask, render_template, request, url_for, redirect from flask_bootstrap import Bootstrap import os import datetime import time from algo_prim_final import * from algo_kruskal_final import * from werkzeug.utils import secure_filename import networkx as nx import matplotlib.pyplot as plt    # files = '/files' # ALLOWED_EXTENSIONS = {'txt'} app = Flask (__name__)  @app.route('/', methods=['GET']) def hello_world():  return render_template('index.html')  @app.route('/',methods=['POST']) def reskruskal():  textfile = request.form.get("textfile")  textfile= request.files['textfile']  textfile_path="./files/"   textfile.filename  textfile.save(textfile_path)  return render_template('index.html', textfile=textfile) def submit(textfile):   if request.method == "POST":  if request.form.get("run_krus"):  algo_kruskal_final.run()  elif request.form.get("run_prim"):  algo_prim_final.run()   # return '''  #lt;!doctype htmlgt;  #lt;titlegt;Upload new Filelt;/titlegt;  #lt;h1gt;Upload new Filelt;/h1gt;  #lt;form method=post enctype=multipart/form-datagt;  #lt;input type=file name=textfilegt;  #lt;input type=submit value=Uploadgt;  #lt;/formgt;  #''' bootstrap = Bootstrap(app)   if __name__ =='__main__':   app.run(debug=True)   

Это мое algo_kruskal_final.py:

 import networkx as nx import matplotlib.pyplot as plt from app import textfile_path,file_content,textfile  with open(textfile_path, 'r') as f:  file_content = f.read() g=nx.read_weighted_edgelist(file_content,create_using=nx.Graph(), delimiter=' ', nodetype=int) print(nx.info(g)) print (g.number_of_nodes()) nx.draw(g, with_labels=True) plt.title('AVANT KRUSKAL') plt.show() V= g.number_of_nodes() a_file = open(file_content, "r")  list_of_tuples = [] for line in a_file:  stripped_line = line.strip()  line_list = tuple (stripped_line.split())  list_of_tuples.append(line_list)  a_file.close() print(list_of_tuples)  def kruskal(edges: list) -gt; list:  """  kruskal - fonction pour déterminer le plus cout chemin   :paramétre: List des noeuds sous forme d'un tuple(a, b, valeur de l'arc)  :résultat: List des noeuds /arcs qui représente le plus court chemin.  """  # Sorting input edges by weight  edges = sorted(edges, key=lambda item: item[2])  # Adding first edge (with smallest weight) to result list and deleting it from input edges.  result = [edges.pop(0)]  # Adding to array first set of expanded points.  array = [{result[0][0], result[0][1]}]   # For each edge in sorted list (without deleted first)  for edge in edges:  # Looking for start point occurrences in expanded points sets and trying to get set index.  start_connection = next(iter([i for i in range(len(array)) if edge[0] in array[i]]), None)  # Looking for end point occurrences in expanded points sets and trying to get set index.  end_connection = next(iter([i for i in range(len(array)) if edge[1] in array[i]]), None)   # If edge makes cycle - skip it.  if start_connection is not None and start_connection == end_connection:  continue   # Adding edge to result list.  result.append(edge)  # If edge first point found in expanded points set - add second edge point.  if start_connection is not None:  array[start_connection].add(edge[1])  # If edge second point found in expanded points set - add first edge point.  if end_connection is not None:  array[end_connection].add(edge[0])   # If edge is not connected with any chains - add new set of expanded points. (new chain)  if start_connection is None and end_connection is None:  array.append({edge[0], edge[1]})   # If edge connects two chains - merge these chains. (union from two expanded points sets)  if start_connection is not None and end_connection is not None:  array.append(array[start_connection].union(array[end_connection]))  array = [array[i] for i in range(len(array)) if i != start_connection and i != end_connection]   return result  EDGES = list_of_tuples print(EDGES) print(kruskal(EDGES)) G_kruskal = nx.Graph() G_kruskal.add_weighted_edges_from(kruskal(EDGES)) nx.draw(G_kruskal, with_labels=True) plt.title('APRES KRUSKAL') plt.show()    

And this is my algo_prim_final.py:

 import networkx as nx import matplotlib.pyplot as plt from app import textfile_path,file_content,textfile  with open(textfile_path, 'r') as f:  file_content = f.read() G=nx.read_weighted_edgelist('file_content',create_using=nx.Graph(), delimiter=' ', nodetype=int) nx.draw(G, with_labels=True) plt.title('AVANT PRIM') plt.show() noeuds= G.number_of_nodes() print(noeuds) listofedges = [[int(v) for v in line.split()] for line in open(file_content)] print(listofedges)  def createAdjMatrix(V, G):  adjMatrix = []  #create N x N matrix filled with 0 edge weights between all vertices  for i in range(0, V):  adjMatrix.append([])  for j in range(0, V):  adjMatrix[i].append(0)  #populate adjacency matrix with correct edge weights  for i in range(0, len(G)):  adjMatrix[G[i][0]][G[i][1]] = G[i][2]  adjMatrix[G[i][1]][G[i][0]] = G[i][2]  return adjMatrix def prims(V, G):  # create adj matrix from graph  adjMatrix = createAdjMatrix(V, G)  #arbitrarily choose initial vertex from graph  vertex = 0  #initialize empty edges array and empty MST  MST = []  edges = []  visited = []  minEdge = [None,None,float('inf')]  #run prims algorithm until we create an MST  #that contains every vertex from the graph  while len(MST) != V-1:  #mark this vertex as visited  visited.append(vertex)  #add each edge to list of potential edges  for r in range(0, V):  if adjMatrix[vertex][r] != 0:  edges.append([vertex,r,adjMatrix[vertex][r]])  #find edge with the smallest weight to a vertex  #that has not yet been visited  for e in range(0, len(edges)):  if edges[e][2] lt; minEdge[2] and edges[e][1] not in visited:  minEdge = edges[e]  #remove min weight edge from list of edges  edges.remove(minEdge)  #push min edge to MST  MST.append(minEdge)  #start at new vertex and reset min edge  vertex = minEdge[1]  minEdge = [None,None,float('inf')]  return MST  #graph vertices are actually represented as numbers  #like so: 0, 1, 2, ... V-1 #a, b, c, d, e, f = 0, 1, 2, 3, 4, 5  #graph edges with weights  #diagram of graph is shown above graph = listofedges  #pass the # of vertices and the graph to run prims algorithm  print(prims(noeuds, graph)) g_prim=nx.Graph() g_prim.add_weighted_edges_from((prims(noeuds, graph))) nx.draw(g_prim, with_labels=True) plt.title('APRES PRIM') plt.show()  

And finally index.html:

 lt;h1 class="text-center"gt;Algorithme KRUSKAL/PRIM lt;/h1gt;  lt;form class="p-3 text-center" action='/', method="post" enctype="multipart/form-data"gt;  lt;input class="form-control col-xs-4" type="file" name="textfile" accept=".txt"gt;  lt;br/gt;lt;br/gt;lt;br/gt;  lt;divgt;  lt;div class="d-grid gap-2 d-md-block"gt;  lt;button class="btn btn-primary" type="submit" name="run_Krus"gt;Kruskallt;/buttongt;  lt;button class="btn btn-primary" type="submit" name="run_prim"gt;Primlt;/buttongt;  lt;/divgt;  lt;/divgt;  lt;/formgt;  

So the idea is passing a file from an html input and run it in a webpage, show the plots as well.

Thank you.