DIRECTORY.md

@@ -236,8 +236,8 @@
     * [Double Ended Queue](data_structures/queue/double_ended_queue.py)
     * [Linked Queue](data_structures/queue/linked_queue.py)
     * [Priority Queue Using List](data_structures/queue/priority_queue_using_list.py)
-    * [Queue By List](data_structures/queue/queue_by_list.py)
     * [Queue By Two Stacks](data_structures/queue/queue_by_two_stacks.py)
+    * [Queue On List](data_structures/queue/queue_on_list.py)
     * [Queue On Pseudo Stack](data_structures/queue/queue_on_pseudo_stack.py)
   * Stacks
     * [Balanced Parentheses](data_structures/stacks/balanced_parentheses.py)

cellular_automata/game_of_life.py

@@ -10,7 +10,7 @@ Python:
   - 3.5
 
 Usage:
-  - $python3 game_of_life <canvas_size:int>
+  - $python3 game_o_life <canvas_size:int>
 
 Game-Of-Life Rules:
 
@@ -52,8 +52,7 @@ def seed(canvas: list[list[bool]]) -> None:
 
 
 def run(canvas: list[list[bool]]) -> list[list[bool]]:
-    """
-    This function runs the rules of game through all points, and changes their
+    """This  function runs the rules of game through all points, and changes their
     status accordingly.(in the same canvas)
     @Args:
     --
@@ -61,7 +60,7 @@ def run(canvas: list[list[bool]]) -> list[list[bool]]:
 
     @returns:
     --
-    canvas of population after one step
+    None
     """
     current_canvas = np.array(canvas)
     next_gen_canvas = np.array(create_canvas(current_canvas.shape[0]))
@@ -71,7 +70,10 @@ def run(canvas: list[list[bool]]) -> list[list[bool]]:
                 pt, current_canvas[r - 1 : r + 2, c - 1 : c + 2]
             )
 
-    return next_gen_canvas.tolist()
+    current_canvas = next_gen_canvas
+    del next_gen_canvas  # cleaning memory as we move on.
+    return_canvas: list[list[bool]] = current_canvas.tolist()
+    return return_canvas
 
 
 def __judge_point(pt: bool, neighbours: list[list[bool]]) -> bool:

data_structures/binary_tree/segment_tree.py

@@ -7,8 +7,7 @@ class SegmentTree:
         self.st = [0] * (
             4 * self.N
         )  # approximate the overall size of segment tree with array N
-        if self.N:
-            self.build(1, 0, self.N - 1)
+        self.build(1, 0, self.N - 1)
 
     def left(self, idx):
         return idx * 2

graphs/eulerian_path_and_circuit_for_undirected_graph.py

@@ -20,7 +20,7 @@ def check_circuit_or_path(graph, max_node):
     odd_degree_nodes = 0
     odd_node = -1
     for i in range(max_node):
-        if i not in graph:
+        if i not in graph.keys():
             continue
         if len(graph[i]) % 2 == 1:
             odd_degree_nodes += 1

physics/newtons_second_law_of_motion.py

@@ -60,7 +60,7 @@ def newtons_second_law_of_motion(mass: float, acceleration: float) -> float:
     >>> newtons_second_law_of_motion(2.0, 1)
     2.0
     """
-    force = 0.0
+    force = float()
     try:
         force = mass * acceleration
     except Exception:

sorts/bubble_sort.py

@@ -1,7 +1,4 @@
-from typing import Any
-
-
-def bubble_sort(collection: list[Any]) -> list[Any]:
+def bubble_sort(collection):
     """Pure implementation of bubble sort algorithm in Python
 
     :param collection: some mutable ordered collection with heterogeneous
@@ -31,9 +28,9 @@ def bubble_sort(collection: list[Any]) -> list[Any]:
     True
     """
     length = len(collection)
-    for i in reversed(range(length)):
+    for i in range(length - 1):
         swapped = False
-        for j in range(i):
+        for j in range(length - 1 - i):
             if collection[j] > collection[j + 1]:
                 swapped = True
                 collection[j], collection[j + 1] = collection[j + 1], collection[j]