Generar docstrings y comentarios para las funciones de Python.
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Puedes buscar un modelo directamente y probar los resultados que se muestran cuando usas valores de parámetros diferentes con la consola de Cloud o con una llamada directa a la API de Vertex AI.
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Mensaje Formato libre
Here are Python codes. Insert the document comment (docstring) for all functions, including the nested functions.
def is_dag_dfs(graph):
visited = set()
on_stack = set() # Track nodes on recursion stack
def dfs(node):
if node in on_stack:
return False # Back-edge found (cycle)
if node in visited:
return True
on_stack.add(node)
visited.add(node)
for neighbor in graph.get(node, []):
if not dfs(neighbor):
return False
on_stack.remove(node)
return True
return all(dfs(node) for node in graph)
Respuesta
```python
def is_dag_dfs(graph):
"""
Determines if a directed graph is a Directed Acyclic Graph (DAG) using Depth-First Search (DFS).
Args:
graph (dict): A dictionary representing the graph, where keys are nodes and values are lists of adjacent nodes.
Returns:
bool: True if the graph is a DAG, False otherwise.
"""
visited = set()
on_stack = set() # Track nodes on recursion stack
def dfs(node):
"""
Performs DFS on the graph starting from the given node.
Args:
node: The node to start DFS from.
Returns:
bool: True if the graph is a DAG, False if a cycle is found.
"""
if node in on_stack:
return False # Back-edge found (cycle)
if node in visited:
return True
on_stack.add(node)
visited.add(node)
for neighbor in graph.get(node, []):
if not dfs(neighbor):
return False
on_stack.remove(node)
return True
return all(dfs(node) for node in graph)
```
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