Choose pseudorandom first solution in local search

src/processing.py

@@ -1,6 +1,7 @@
 from preprocessing import parse_file
 from pandas import DataFrame
 from sys import argv
+from random import seed, randint
 
 
 def get_first_solution(n, data):
@@ -44,9 +45,19 @@ def greedy_algorithm(n, m, data):
     return solutions
 
 
+def get_pseudorandom_solution(n, data):
+    seed(42)
+    return data.iloc[randint(a=0, b=n)]
+
+
 # NOTE In each step, switch to the element that gives the least amount
 def local_search(n, m, data):
-    pass
+    solutions = DataFrame(columns=["point", "distance"])
+    first_solution = get_pseudorandom_solution(n=n, data=data)
+    solutions = solutions.append(first_solution, ignore_index=True)
+    for _ in range(m):
+        pass
+    return solutions
 
 
 def execute_algorithm(choice, n, m, data):