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54 lines
1.8 KiB
54 lines
1.8 KiB
from py2neo import Graph, Node, Relationship
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from Config import Config
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# 1. 连接Neo4j数据库
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graph = Graph(Config.NEO4J_URI, auth=Config.NEO4J_AUTH)
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# 清空数据库
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graph.delete_all()
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print("数据库已清空")
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# 2. 创建化学物质节点 (三种反应物+一种生成物)
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reactant_A = Node("Chemical", name="铁", formula="Fe")
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reactant_B = Node("Chemical", name="氧气", formula="O2")
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reactant_C = Node("Chemical", name="水", formula="H2O")
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product = Node("Chemical", name="氧化铁", formula="Fe2O3")
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# 3. 创建反应节点并添加属性
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reaction = Node("Reaction",
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name="铁锈蚀反应",
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equation="4Fe + 3O2 + 6H2O → 4Fe(OH)3",
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condition="常温常压"
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)
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# 4. 建立反应物与反应的关系(带计量系数属性)
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rel_A = Relationship(reactant_A, "参与反应", reaction, coefficient=4)
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rel_B = Relationship(reactant_B, "参与反应", reaction, coefficient=3)
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rel_C = Relationship(reactant_C, "参与反应", reaction, coefficient=6)
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# 5. 建立反应与生成物的关系
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rel_product = Relationship(reaction, "生成", product, yield_rate="98%")
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# 6. 将节点和关系提交到数据库
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graph.create(reactant_A)
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graph.create(reactant_B)
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graph.create(reactant_C)
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graph.create(product)
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graph.create(reaction)
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graph.create(rel_A)
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graph.create(rel_B)
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graph.create(rel_C)
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graph.create(rel_product)
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# 7. 查询示例:查找所有参与铁锈蚀反应的物质
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query = """
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MATCH (c:Chemical)-[r:PARTICIPATES_IN]->(re:Reaction {name:'铁锈蚀反应'})
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RETURN c.name AS chemical, r.coefficient AS coefficient, re.equation AS equation
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"""
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result = graph.run(query)
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for record in result:
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print(f"化学物质: {record['chemical']}, 计量系数: {record['coefficient']}")
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print(f"反应方程式: {record['equation']}") |