60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
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# This file based on a ChatGPT reponse for the following prompt:
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# "can you write code in python to build up a DAG representing
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# a dependency tree, and then a function that can return all the
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# dependencies of a given node?"
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class Node:
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def __init__(self, name):
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self.name = name
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self.dependencies = set()
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class DAG:
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def __init__(self):
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self.nodes = {}
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def add_node(self, node_name, dependencies=None):
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if node_name in self.nodes:
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raise ValueError(f"Node '{node_name}' already exists in the graph.")
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node = Node(node_name)
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if dependencies:
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node.dependencies.update(dependencies)
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self.nodes[node_name] = node
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def add_dependency(self, node_name, dependency_name):
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if node_name not in self.nodes:
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raise ValueError(f"Node '{node_name}' does not exist in the graph.")
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if dependency_name not in self.nodes:
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raise ValueError(f"Dependency '{dependency_name}' does not exist in the graph.")
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self.nodes[node_name].dependencies.add(dependency_name)
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def get_dependencies(self, node_name):
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if node_name not in self.nodes:
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raise ValueError(f"Node '{node_name}' does not exist in the graph.")
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node = self.nodes[node_name]
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dependencies = set()
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def traverse_dependencies(current_node):
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for dependency in current_node.dependencies:
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dependencies.add(dependency)
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if dependency in self.nodes:
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traverse_dependencies(self.nodes[dependency])
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traverse_dependencies(node)
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return dependencies
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def has_node(self, node_name):
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return node_name in self.nodes
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def __str__(self):
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graph_str = ""
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for node_name, node in self.nodes.items():
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graph_str += f"{node_name} -> {', '.join(node.dependencies)}\n"
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return graph_str
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