Set the Python file maximum line length to 88 characters (#2122)

* flake8 --max-line-length=88

* fixup! Format Python code with psf/black push

Co-authored-by: github-actions <${GITHUB_ACTOR}@users.noreply.github.com>

data_structures/data_structures/heap/heap_generic.py

@@ -1,5 +1,7 @@
 class Heap:
-    """A generic Heap class, can be used as min or max by passing the key function accordingly.
+    """
+    A generic Heap class, can be used as min or max by passing the key function
+    accordingly.
     """
 
     def __init__(self, key=None):
@@ -9,7 +11,8 @@ class Heap:
         self.pos_map = {}
         # Stores current size of heap.
         self.size = 0
-        # Stores function used to evaluate the score of an item on which basis ordering will be done.
+        # Stores function used to evaluate the score of an item on which basis ordering
+        # will be done.
         self.key = key or (lambda x: x)
 
     def _parent(self, i):
@@ -41,7 +44,10 @@ class Heap:
         return self.arr[i][1] < self.arr[j][1]
 
     def _get_valid_parent(self, i):
-        """Returns index of valid parent as per desired ordering among given index and both it's children"""
+        """
+        Returns index of valid parent as per desired ordering among given index and
+        both it's children
+        """
         left = self._left(i)
         right = self._right(i)
         valid_parent = i
@@ -87,8 +93,8 @@ class Heap:
         self.arr[index] = self.arr[self.size - 1]
         self.pos_map[self.arr[self.size - 1][0]] = index
         self.size -= 1
-        # Make sure heap is right in both up and down direction.
-        # Ideally only one of them will make any change- so no performance loss in calling both.
+        # Make sure heap is right in both up and down direction. Ideally only one
+        # of them will make any change- so no performance loss in calling both.
         if self.size > index:
             self._heapify_up(index)
             self._heapify_down(index)
@@ -109,7 +115,10 @@ class Heap:
         return self.arr[0] if self.size else None
 
     def extract_top(self):
-        """Returns top item tuple (Calculated value, item) from heap and removes it as well if present"""
+        """
+        Return top item tuple (Calculated value, item) from heap and removes it as well
+        if present
+        """
         top_item_tuple = self.get_top()
         if top_item_tuple:
             self.delete_item(top_item_tuple[0])

data_structures/linked_list/skip_list.py

@@ -126,7 +126,8 @@ class SkipList(Generic[KT, VT]):
         """
         :param key: Searched key,
         :return: Tuple with searched node (or None if given key is not present)
-                 and list of nodes that refer (if key is present) of should refer to given node.
+                 and list of nodes that refer (if key is present) of should refer to
+                 given node.
         """
 
         # Nodes with refer or should refer to output node
@@ -141,7 +142,8 @@ class SkipList(Generic[KT, VT]):
             #                             in skipping searched key.
             while i < node.level and node.forward[i].key < key:
                 node = node.forward[i]
-            # Each leftmost node (relative to searched node) will potentially have to be updated.
+            # Each leftmost node (relative to searched node) will potentially have to
+            # be updated.
             update_vector.append(node)
 
         update_vector.reverse()  # Note that we were inserting values in reverse order.

data_structures/stacks/infix_to_prefix_conversion.py

@@ -49,10 +49,8 @@ def infix_2_postfix(Infix):
         else:
             if len(Stack) == 0:
                 Stack.append(x)  # If stack is empty, push x to stack
-            else:
-                while (
-                    len(Stack) > 0 and priority[x] <= priority[Stack[-1]]
-                ):  # while priority of x is not greater than priority of element in the stack
+            else:  # while priority of x is not > priority of element in the stack
+                while len(Stack) > 0 and priority[x] <= priority[Stack[-1]]:
                     Postfix.append(Stack.pop())  # pop stack & add to Postfix
                 Stack.append(x)  # push x to stack
 

data_structures/trie/trie.py

@@ -1,8 +1,8 @@
 """
 A Trie/Prefix Tree is a kind of search tree used to provide quick lookup
 of words/patterns in a set of words. A basic Trie however has O(n^2) space complexity
-making it impractical in practice. It however provides O(max(search_string, length of longest word))
-lookup time making it an optimal approach when space is not an issue.
+making it impractical in practice. It however provides O(max(search_string, length of
+longest word)) lookup time making it an optimal approach when space is not an issue.
 """