Add python datastructure algo

Author: princegupta22

graphs/floyd_warshall.py

@@ -0,0 +1,31 @@
+# Algorithm to find shortest paths between all pairs of vertices in a weighted graph.
+
+def floyd_warshall(graph):
+    """
+    graph: adjacency matrix (2D list)
+    returns: distance matrix (shortest path between all pairs)
+    """
+    n = len(graph)
+    dist = [row[:] for row in graph]
+
+    for k in range(n):
+        for i in range(n):
+            for j in range(n):
+                if dist[i][k] + dist[k][j] < dist[i][j]:
+                    dist[i][j] = dist[i][k] + dist[k][j]
+    return dist
+
+
+if __name__ == "__main__":
+    INF = 99999
+    graph = [
+        [0, 5, INF, 10],
+        [INF, 0, 3, INF],
+        [INF, INF, 0, 1],
+        [INF, INF, INF, 0]
+    ]
+
+    result = floyd_warshall(graph)
+    print("All-Pairs Shortest Paths:")
+    for row in result:
+        print(row)

graphs/topological_sort.py

@@ -0,0 +1,35 @@
+# Perform topological sort on a directed acyclic graph (DAG)
+
+from collections import defaultdict
+
+class Graph:
+    def __init__(self):
+        self.graph = defaultdict(list)
+
+    def add_edge(self, u, v):
+        self.graph[u].append(v)
+
+    def topological_sort_util(self, v, visited, stack):
+        visited[v] = True
+        for i in self.graph[v]:
+            if not visited[i]:
+                self.topological_sort_util(i, visited, stack)
+        stack.append(v)
+
+    def topological_sort(self):
+        visited = {key: False for key in self.graph}
+        stack = []
+        for vertex in self.graph:
+            if not visited[vertex]:
+                self.topological_sort_util(vertex, visited, stack)
+        print(stack[::-1])
+
+if __name__ == "__main__":
+    g = Graph()
+    g.add_edge(5, 2)
+    g.add_edge(5, 0)
+    g.add_edge(4, 0)
+    g.add_edge(4, 1)
+    g.add_edge(2, 3)
+    g.add_edge(3, 1)
+    g.topological_sort()

strings/binary_search_recursive.py

@@ -0,0 +1,17 @@
+def binary_search(arr, target, low, high):
+    if low > high:
+        return -1
+    mid = (low + high) // 2
+    if arr[mid] == target:
+        return mid
+    elif arr[mid] > target:
+        return binary_search(arr, target, low, mid - 1)
+    else:
+        return binary_search(arr, target, mid + 1, high)
+
+
+if __name__ == "__main__":
+    arr = [2, 4, 6, 8, 10, 12]
+    target = 10
+    result = binary_search(arr, target, 0, len(arr) - 1)
+    print(f"Element found at index {result}" if result != -1 else "Not found")