Merge branch 'fix2' of https://github.com/shivaparihar6119/Python into fix2

Author: shivaparihar6119

Diff for: graphs/check_bipartite_graph_all.py

@@ -90,7 +90,8 @@ def depth_first_search(node: int, color: int) -> bool:
     )
 
 
-if __name__ == "__main__":
+
+if __name__ == "__main":
     import doctest
 
     result = doctest.testmod()

Diff for: graphs/check_bipatrite.py

@@ -0,0 +1,93 @@
+from collections import defaultdict, deque
+
+
+def is_bipartite_dfs(graph: defaultdict[int, list[int]]) -> bool:
+    """
+    Check if a graph is bipartite using DFS.
+
+    Args:
+        graph (defaultdict[int, list[int]]): Adjacency list representing the graph.
+
+    Returns:
+        bool: True if bipartite, False otherwise.
+
+    This function checks if the graph can be divided into two sets of vertices,
+    such that no two vertices within the same set are connected by an edge.
+
+    Examples:
+    >>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]}))
+    True
+    >>> is_bipartite_dfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 1]}))
+    False
+    """
+
+    def dfs(node, color):
+        """
+        Perform Depth-First Search (DFS) on the graph starting from a node.
+
+        Args:
+            node: The current node being visited.
+            color: The color assigned to the current node.
+
+        Returns:
+            bool: True if the graph is bipartite starting from the current node, False otherwise.
+        """
+        if visited[node] == -1:
+            visited[node] = color
+            for neighbor in graph[node]:
+                if not dfs(neighbor, 1 - color):
+                    return False
+        return visited[node] == color
+
+    visited = defaultdict(lambda: -1)
+    for node in graph:
+        if visited[node] == -1 and not dfs(node, 0):
+            return False
+    return True
+
+
+def is_bipartite_bfs(graph: defaultdict[int, list[int]]) -> bool:
+    """
+    Check if a graph is bipartite using BFS.
+
+    Args:
+        graph (defaultdict[int, list[int]]): Adjacency list representing the graph.
+
+    Returns:
+        bool: True if bipartite, False otherwise.
+
+    This function checks if the graph can be divided into two sets of vertices,
+    such that no two vertices within the same set are connected by an edge.
+
+    Examples:
+    >>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 3], 2: [0, 4]}))
+    True
+    >>> is_bipartite_bfs(defaultdict(list, {0: [1, 2], 1: [0, 2], 2: [0, 1]}))
+    False
+    """
+    visited = defaultdict(lambda: -1)
+    for node in graph:
+        if visited[node] == -1:
+            queue = deque()
+            queue.append(node)
+            visited[node] = 0
+            while queue:
+                curr_node = queue.popleft()
+                for neighbor in graph[curr_node]:
+                    if visited[neighbor] == -1:
+                        visited[neighbor] = 1 - visited[curr_node]
+                        queue.append(neighbor)
+                    elif visited[neighbor] == visited[curr_node]:
+                        return False
+    return True
+
+
+if __name__ == "__main":
+    import doctest
+
+    result = doctest.testmod()
+
+    if result.failed:
+        print(f"{result.failed} test(s) failed.")
+    else:
+        print("All tests passed!")