ruff rule ANN202 missing-return-type-private-function

Author: cclauss

data_structures/binary_tree/segment_tree_other.py

@@ -173,7 +173,7 @@ def _build_tree(self, start, end):
         right = self._build_tree(mid + 1, end)
         return SegmentTreeNode(start, end, self.fn(left.val, right.val), left, right)
 
-    def _update_tree(self, node, i, val):
+    def _update_tree(self, node, i, val) -> None:
         if node.start == i and node.end == i:
             node.val = val
             return

data_structures/hashing/hash_table.py

@@ -80,7 +80,7 @@ def hash_function(self, key):
         """
         return key % self.size_table
 
-    def _step_by_step(self, step_ord):
+    def _step_by_step(self, step_ord) -> None:
         print(f"step {step_ord}")
         print(list(range(len(self.values))))
         print(self.values)
@@ -130,7 +130,7 @@ def bulk_insert(self, values) -> None:
             self._step_by_step(i)
             i += 1
 
-    def _set_value(self, key, data):
+    def _set_value(self, key, data) -> None:
         """
         _set_value functions allows to update value at a particular hash
 

data_structures/hashing/hash_table_with_linked_list.py

@@ -7,7 +7,7 @@ class HashTableWithLinkedList(HashTable):
     def __init__(self, *args, **kwargs):
         super().__init__(*args, **kwargs)
 
-    def _set_value(self, key, data):
+    def _set_value(self, key, data) -> None:
         self.values[key] = deque() if self.values[key] is None else self.values[key]
         self.values[key].appendleft(data)
         self._keys[key] = self.values[key]

data_structures/heap/binomial_heap.py

@@ -373,7 +373,7 @@ def pre_order(self):
         self.__traversal(top_root, heap_pre_order)
         return heap_pre_order
 
-    def __traversal(self, curr_node, preorder, level=0):
+    def __traversal(self, curr_node, preorder, level=0) -> None:
         """
         Pre-order traversal of nodes
         """

data_structures/linked_list/deque_doubly.py

@@ -19,7 +19,7 @@ def __init__(self, link_p, element, link_n):
             self._data = element
             self._next = link_n
 
-        def has_next_and_prev(self):
+        def has_next_and_prev(self) -> str:
             return (
                 f" Prev -> {self._prev is not None}, Next -> {self._next is not None}"
             )

divide_and_conquer/heaps_algorithm.py

@@ -32,7 +32,7 @@ def heaps(arr: list) -> list:
 
     res = []
 
-    def generate(k: int, arr: list):
+    def generate(k: int, arr: list) -> None:
         if k == 1:
             res.append(tuple(arr[:]))
             return

divide_and_conquer/heaps_algorithm_iterative.py

@@ -32,7 +32,7 @@ def heaps(arr: list) -> list:
 
     res = []
 
-    def generate(n: int, arr: list):
+    def generate(n: int, arr: list) -> None:
         c = [0] * n
         res.append(tuple(arr))
 

dynamic_programming/knapsack.py

@@ -100,7 +100,7 @@ def knapsack_with_example_solution(w: int, wt: list, val: list):
     return optimal_val, example_optional_set
 
 
-def _construct_solution(dp: list, wt: list, i: int, j: int, optimal_set: set):
+def _construct_solution(dp: list, wt: list, i: int, j: int, optimal_set: set) -> None:
     """
     Recursively reconstructs one of the optimal subsets given
     a filled DP table and the vector of weights

dynamic_programming/rod_cutting.py

@@ -174,7 +174,7 @@ def bottom_up_cut_rod(n: int, prices: list):
     return max_rev[n]
 
 
-def _enforce_args(n: int, prices: list):
+def _enforce_args(n: int, prices: list) -> None:
     """
     Basic checks on the arguments to the rod-cutting algorithms
 

graphs/edmonds_karp_multiple_source_and_sink.py

@@ -9,7 +9,7 @@ def __init__(self, graph, sources, sinks):
         self.maximum_flow_algorithm = None
 
     # make only one source and one sink
-    def _normalize_graph(self, sources, sinks):
+    def _normalize_graph(self, sources, sinks) -> None:
         if sources is int:
             sources = [sources]
         if sinks is int:
@@ -74,7 +74,7 @@ def execute(self) -> None:
             self.executed = True
 
     # You should override it
-    def _algorithm(self):
+    def _algorithm(self) -> None:
         pass
 
 
@@ -100,7 +100,7 @@ def __init__(self, flow_network):
         self.heights = [0] * self.verticies_count
         self.excesses = [0] * self.verticies_count
 
-    def _algorithm(self):
+    def _algorithm(self) -> None:
         self.heights[self.source_index] = self.verticies_count
 
         # push some substance to graph