Created two python packages. One for algorithms implementations of the master thesis and the other for methods, classes and structures meant to help with the use of those algorithms.

README.md

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+dijkstry:<br>
+https://pl.wikipedia.org/wiki/Algorytm_Dijkstry
+
+kopce:<br>
+https://ufkapano.github.io/algorytmy/lekcja09/heap.html
+https://docs.python.org/3/library/heapq.html

algorithms/dijkstra.py

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+def dijkstra_algorithm(graph, s ):
+    print()
+
+
+if __name__ == "__main__":
+    print()

main.py

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-def read_graph_from_file(path, separator=",", read_first_line=False, is_directed=False, has_weight=False):
+import tools.file_service as op_file
-    edges = dict()
-    with open(path, 'r') as file:
-        read_line = read_first_line
-        line = file.readline()
-        while line != '':
-            if read_line:
-                if line[0] != "#":
-                    split = line.split(separator)
-                    node1 = int(split[0])
-                    node2 = int(split[1])
-                    if not is_directed:
-                        if not has_weight:
-                            edges[(node1, node2)] = 1
-            else:
-                read_line = True
-            line = file.readline()
-    return edges
-
 
 if __name__ == '__main__':
-    e = read_graph_from_file("dataset/deezer_clean_data/HR_edges.csv")
+    e = op_file.read_graph_from_file("dataset/deezer_clean_data/HR_edges.csv")
-    print(e)
+    op_file.add_weight_to_file(e, "dataset/deezer_clean_data/HR_edges", ".csv")
-

tools/file_service.py

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+import random as rand
+
+
+def read_graph_from_file(path, separator=",", read_first_line=False, is_directed=False, has_weight=False):
+    edges = dict()
+    with open(path, 'r') as file:
+        read_line = read_first_line
+        line = file.readline()
+        while line != '':
+            if read_line:
+                if line[0] != "#":
+                    split = line.split(separator)
+                    node1 = int(split[0])
+                    node2 = int(split[1])
+                    if not is_directed:
+                        if not has_weight:
+                            edges[(node1, node2)] = 1
+                        else:
+                            edges[(node1, node2)] = split[2]
+            else:
+                read_line = True
+            line = file.readline()
+    return edges
+
+
+def add_weight_to_file(graph, path, extension, separator=",", weight_scale=(1, 100)):
+    with open(path + "with_weight" + extension, 'w') as file:
+        for key in graph.keys():
+            file.write(str(key[0]) + separator + str(key[1]) + separator + str(rand.randint(weight_scale[0],
+                                                                                            weight_scale[1])) + "\n")