Add doctest to graphs/basic_graphs.py

graphs/basic_graphs.py

@@ -185,10 +185,29 @@ def topo(g, ind=None, q=None):
 
 
 def adjm():
- n = input().strip()
+ r"""
+ Reading an Adjacency matrix
+
+ Parameters:
+ None
+
+ Returns:
+ tuple: A tuple containing a list of edges and number of edges
+
+ Example:
+ >>> # Simulate user input for 3 nodes
+ >>> input_data = "4\n0 1 0 1\n1 0 1 0\n0 1 0 1\n1 0 1 0\n"
+ >>> import sys,io
+ >>> original_input = sys.stdin
+ >>> sys.stdin = io.StringIO(input_data) # Redirect stdin for testing
+ >>> adjm()
+ ([(0, 1, 0, 1), (1, 0, 1, 0), (0, 1, 0, 1), (1, 0, 1, 0)], 4)
+ >>> sys.stdin = original_input # Restore original stdin
+ """
+ n = int(input().strip())
  a = []
  for _ in range(n):
- a.append(map(int, input().strip().split()))
+ a.append(tuple(map(int, input().strip().split())))
  return a, n
 
 
@@ -260,10 +279,29 @@ def prim(g, s):
 
 
 def edglist():
- n, m = map(int, input().split(" "))
+ r"""
+ Get the edges and number of edges from the user
+
+ Parameters:
+ None
+
+ Returns:
+ tuple: A tuple containing a list of edges and number of edges
+
+ Example:
+ >>> # Simulate user input for 3 edges and 4 vertices: (1, 2), (2, 3), (3, 4)
+ >>> input_data = "4 3\n1 2\n2 3\n3 4\n"
+ >>> import sys,io
+ >>> original_input = sys.stdin
+ >>> sys.stdin = io.StringIO(input_data) # Redirect stdin for testing
+ >>> edglist()
+ ([(1, 2), (2, 3), (3, 4)], 4)
+ >>> sys.stdin = original_input # Restore original stdin
+ """
+ n, m = tuple(map(int, input().split(" ")))
  edges = []
  for _ in range(m):
- edges.append(map(int, input().split(" ")))
+ edges.append(tuple(map(int, input().split(" "))))
  return edges, n
 
 
@@ -278,7 +316,9 @@ def edglist():
 
 
 def krusk(e_and_n):
- # Sort edges on the basis of distance
+ """
+ Sort edges on the basis of distance
+ """
  (e, n) = e_and_n
  e.sort(reverse=True, key=lambda x: x[2])
  s = [{i} for i in range(1, n + 1)]
@@ -299,8 +339,37 @@ def krusk(e_and_n):
  break
 
 
-# find the isolated node in the graph
 def find_isolated_nodes(graph):
+ """
+ Find the isolated node in the graph
+
+ Parameters:
+ graph (dict): A dictionary representing a graph.
+
+ Returns:
+ list: A list of isolated nodes.
+
+ Examples:
+ >>> graph1 = {1: [2, 3], 2: [1, 3], 3: [1, 2], 4: []}
+ >>> find_isolated_nodes(graph1)
+ [4]
+
+ >>> graph2 = {'A': ['B', 'C'], 'B': ['A'], 'C': ['A'], 'D': []}
+ >>> find_isolated_nodes(graph2)
+ ['D']
+
+ >>> graph3 = {'X': [], 'Y': [], 'Z': []}
+ >>> find_isolated_nodes(graph3)
+ ['X', 'Y', 'Z']
+
+ >>> graph4 = {1: [2, 3], 2: [1, 3], 3: [1, 2]}
+ >>> find_isolated_nodes(graph4)
+ []
+
+ >>> graph5 = {}
+ >>> find_isolated_nodes(graph5)
+ []
+ """
  isolated = []
  for node in graph:
  if not graph[node]: