applied black autoformatting

Author: Hasenn

ciphers/enigma_machine2.py

@@ -124,9 +124,7 @@ def _plugboard(pbstring: str) -> dict:
     # a) is type string
     # b) has even length (so pairs can be made)
     if not isinstance(pbstring, str):
-        raise TypeError(
-            f"Plugboard setting isn't type string ({type(pbstring)})"
-        )
+        raise TypeError(f"Plugboard setting isn't type string ({type(pbstring)})")
     elif len(pbstring) % 2 != 0:
         raise Exception(f"Odd number of symbols ({len(pbstring)})")
     elif pbstring == "":

graphs/directed_and_undirected_(weighted)_graph.py

@@ -227,8 +227,7 @@ def has_cycle(self):
                             else:
                                 return True
                                 # TODO:The following code is unreachable.
-                                anticipating_nodes.add(
-                                    stack[len_stack_minus_one])
+                                anticipating_nodes.add(stack[len_stack_minus_one])
                                 len_stack_minus_one -= 1
                     if visited.count(node[1]) < 1:
                         stack.append(node[1])
@@ -457,8 +456,7 @@ def has_cycle(self):
                                 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])
+                                anticipating_nodes.add(stack[len_stack_minus_one])
                                 len_stack_minus_one -= 1
                     if visited.count(node[1]) < 1:
                         stack.append(node[1])

maths/chudnovsky_algorithm.py

@@ -48,8 +48,7 @@ def pi(precision: int) -> str:
     linear_term = 13591409
     partial_sum = Decimal(linear_term)
     for k in range(1, num_iterations):
-        multinomial_term = factorial(
-            6 * k) // (factorial(3 * k) * factorial(k) ** 3)
+        multinomial_term = factorial(6 * k) // (factorial(3 * k) * factorial(k) ** 3)
         linear_term += 545140134
         exponential_term *= -262537412640768000
         partial_sum += Decimal(multinomial_term * linear_term) / exponential_term

scheduling/shortest_job_first.py

@@ -111,8 +111,7 @@ def calculate_average_times(
     for i in range(no_of_processes):
         total_waiting_time = total_waiting_time + waiting_time[i]
         total_turn_around_time = total_turn_around_time + turn_around_time[i]
-    print("Average waiting time = %.5f" %
-          (total_waiting_time / no_of_processes))
+    print("Average waiting time = %.5f" % (total_waiting_time / no_of_processes))
     print("Average turn around time =", total_turn_around_time / no_of_processes)
 
 
@@ -127,8 +126,7 @@ def calculate_average_times(
         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)
+    waiting_time = calculate_waitingtime(arrival_time, burst_time, no_of_processes)
 
     bt = burst_time
     n = no_of_processes
@@ -138,8 +136,7 @@ def calculate_average_times(
     calculate_average_times(waiting_time, turn_around_time, no_of_processes)
 
     fcfs = pd.DataFrame(
-        list(zip(processes, burst_time, arrival_time,
-                 waiting_time, turn_around_time)),
+        list(zip(processes, burst_time, arrival_time, waiting_time, turn_around_time)),
         columns=[
             "Process",
             "BurstTime",