Fix some warnings from LGTM (TheAlgorithms#2420)

* fix assignment of a variable to itself

* Fix unnecessary 'else' clause in loop

* formatting and redundant reasignment fix

* mark unreachable code with a TODO comment

* fix variable defined multiple times

* fix static method without static decorator

* revert unintended autoformatting

Co-authored-by: Christian Clauss <[email protected]>

* revert autoformatting issue

* applied black autoformatting

Co-authored-by: Christian Clauss <[email protected]>

Author: Hasenn

ciphers/enigma_machine2.py

@@ -218,7 +218,6 @@ def enigma(
     rotorpos1 -= 1
     rotorpos2 -= 1
     rotorpos3 -= 1
-    plugboard = plugboard
 
     result = []
 

graphs/directed_and_undirected_(weighted)_graph.py

@@ -226,6 +226,7 @@ def has_cycle(self):
                                 break
                             else:
                                 return True
+                                # TODO:The following code is unreachable.
                                 anticipating_nodes.add(stack[len_stack_minus_one])
                                 len_stack_minus_one -= 1
                     if visited.count(node[1]) < 1:
@@ -453,6 +454,8 @@ def has_cycle(self):
                                 break
                             else:
                                 return True
+                                # TODO: the following code is unreachable
+                                # is this meant to be called in the else ?
                                 anticipating_nodes.add(stack[len_stack_minus_one])
                                 len_stack_minus_one -= 1
                     if visited.count(node[1]) < 1:

graphs/minimum_spanning_tree_boruvka.py

@@ -146,6 +146,7 @@ def union(self, item1, item2):
                 self.parent[root2] = root1
                 return root1
 
+    @staticmethod
     def boruvka_mst(graph):
         """
         Implementation of Boruvka's algorithm

maths/chudnovsky_algorithm.py

@@ -44,7 +44,6 @@ def pi(precision: int) -> str:
     getcontext().prec = precision
     num_iterations = ceil(precision / 14)
     constant_term = 426880 * Decimal(10005).sqrt()
-    multinomial_term = 1
     exponential_term = 1
     linear_term = 13591409
     partial_sum = Decimal(linear_term)

other/triplet_sum.py

@@ -61,8 +61,7 @@ def triplet_sum2(arr: List[int], target: int) -> Tuple[int, int, int]:
                 left += 1
             elif arr[i] + arr[left] + arr[right] > target:
                 right -= 1
-    else:
-        return (0, 0, 0)
+    return (0, 0, 0)
 
 
 def solution_times() -> Tuple[float, float]:

scheduling/shortest_job_first.py

@@ -11,7 +11,6 @@
 def calculate_waitingtime(
     arrival_time: List[int], burst_time: List[int], no_of_processes: int
 ) -> List[int]:
-
     """
     Calculate the waiting time of each processes
     Return: list of waiting times.
@@ -126,13 +125,16 @@ def calculate_average_times(
     for i in range(no_of_processes):
         print("Enter the arrival time and brust time for process:--" + str(i + 1))
         arrival_time[i], burst_time[i] = map(int, input().split())
+
     waiting_time = calculate_waitingtime(arrival_time, burst_time, no_of_processes)
+
     bt = burst_time
     n = no_of_processes
     wt = waiting_time
     turn_around_time = calculate_turnaroundtime(bt, n, wt)
+
     calculate_average_times(waiting_time, turn_around_time, no_of_processes)
-    processes = list(range(1, no_of_processes + 1))
+
     fcfs = pd.DataFrame(
         list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
         columns=[