Various ruff fixes (#12821)

graphs/graph_adjacency_list.py

@@ -21,14 +21,14 @@ from __future__ import annotations
 import random
 import unittest
 from pprint import pformat
-from typing import Generic, TypeVar
+from typing import TypeVar
 
 import pytest
 
 T = TypeVar("T")
 
 
-class GraphAdjacencyList(Generic[T]):
+class GraphAdjacencyList[T]:
     def __init__(
         self, vertices: list[T], edges: list[list[T]], directed: bool = True
     ) -> None:

graphs/graph_adjacency_matrix.py

@@ -21,14 +21,14 @@ from __future__ import annotations
 import random
 import unittest
 from pprint import pformat
-from typing import Generic, TypeVar
+from typing import TypeVar
 
 import pytest
 
 T = TypeVar("T")
 
 
-class GraphAdjacencyMatrix(Generic[T]):
+class GraphAdjacencyMatrix[T]:
     def __init__(
         self, vertices: list[T], edges: list[list[T]], directed: bool = True
     ) -> None:

graphs/graph_list.py

@@ -6,12 +6,12 @@
 from __future__ import annotations
 
 from pprint import pformat
-from typing import Generic, TypeVar
+from typing import TypeVar
 
 T = TypeVar("T")
 
 
-class GraphAdjacencyList(Generic[T]):
+class GraphAdjacencyList[T]:
     """
     Adjacency List type Graph Data Structure that accounts for directed and undirected
     Graphs.  Initialize graph object indicating whether it's directed or undirected.

graphs/minimum_spanning_tree_kruskal2.py

@@ -1,11 +1,11 @@
 from __future__ import annotations
 
-from typing import Generic, TypeVar
+from typing import TypeVar
 
 T = TypeVar("T")
 
 
-class DisjointSetTreeNode(Generic[T]):
+class DisjointSetTreeNode[T]:
     # Disjoint Set Node to store the parent and rank
     def __init__(self, data: T) -> None:
         self.data = data
@@ -13,7 +13,7 @@ class DisjointSetTreeNode(Generic[T]):
         self.rank = 0
 
 
-class DisjointSetTree(Generic[T]):
+class DisjointSetTree[T]:
     # Disjoint Set DataStructure
     def __init__(self) -> None:
         # map from node name to the node object
@@ -46,7 +46,7 @@ class DisjointSetTree(Generic[T]):
         self.link(self.find_set(data1), self.find_set(data2))
 
 
-class GraphUndirectedWeighted(Generic[T]):
+class GraphUndirectedWeighted[T]:
     def __init__(self) -> None:
         # connections: map from the node to the neighbouring nodes (with weights)
         self.connections: dict[T, dict[T, int]] = {}

graphs/minimum_spanning_tree_prims2.py

@@ -10,7 +10,7 @@ connection from the tree to another vertex.
 from __future__ import annotations
 
 from sys import maxsize
-from typing import Generic, TypeVar
+from typing import TypeVar
 
 T = TypeVar("T")
 
@@ -47,7 +47,7 @@ def get_child_right_position(position: int) -> int:
     return (2 * position) + 2
 
 
-class MinPriorityQueue(Generic[T]):
+class MinPriorityQueue[T]:
     """
     Minimum Priority Queue Class
 
@@ -184,7 +184,7 @@ class MinPriorityQueue(Generic[T]):
         self.position_map[node2_elem] = node1_pos
 
 
-class GraphUndirectedWeighted(Generic[T]):
+class GraphUndirectedWeighted[T]:
     """
     Graph Undirected Weighted Class
 
@@ -217,7 +217,7 @@ class GraphUndirectedWeighted(Generic[T]):
         self.connections[node2][node1] = weight
 
 
-def prims_algo(
+def prims_algo[T](
     graph: GraphUndirectedWeighted[T],
 ) -> tuple[dict[T, int], dict[T, T | None]]:
     """