feat: 初始提交 - 科创企业特有风险的识别与管理 (数智风控系统)

2026-08-14 08:21:26 +08:00
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+# -*- coding: utf-8 -*-
+"""
+知识图谱构建引擎
+基于 NetworkX 构建科创企业供应链风险传染图谱
+节点类型：企业、供应商、客户、核心人员、制裁实体
+边类型：供应关系、客户关系、任职关系、投资关系
+"""
+import json
+import logging
+from pathlib import Path
+
+import networkx as nx
+
+logger = logging.getLogger(__name__)
+
+DATA_DIR = Path(__file__).parent.parent / "data"
+
+
+def build_graph() -> nx.DiGraph:
+    """
+    构建完整的科创企业供应链风险知识图谱
+    """
+    G = nx.DiGraph()
+
+    # 1. 加载企业数据，添加企业节点
+    _add_company_nodes(G)
+
+    # 2. 加载供应链数据，添加关系边
+    _add_supply_chain_edges(G)
+
+    # 3. 加载实体清单，标记受制裁节点
+    _mark_sanctioned_nodes(G)
+
+    logger.info(f"图谱构建完成: {G.number_of_nodes()} 节点, {G.number_of_edges()} 边")
+    return G
+
+
+def _add_company_nodes(G: nx.DiGraph):
+    """添加科创板企业节点及其关联的核心人员节点"""
+    filepath = DATA_DIR / "sample_companies.json"
+    with open(filepath, "r", encoding="utf-8") as f:
+        companies = json.load(f)
+
+    for company in companies:
+        name = company["short_name"]
+        G.add_node(
+            name,
+            node_type="科创企业",
+            stock_code=company["stock_code"],
+            industry=company["industry"],
+            sector=company["sector"],
+            is_sanctioned=company["compliance"]["entity_list_status"] != "未列入",
+            risk_level="正常",
+            color="#4CAF50",  # 默认绿色
+        )
+
+        # 添加核心技术人员节点
+        for person in company.get("core_tech_personnel", []):
+            person_id = f"{person['name']}@{name}"
+            G.add_node(
+                person_id,
+                node_type="核心人员",
+                real_name=person["name"],
+                title=person["title"],
+                status=person["status"],
+                importance=person["importance"],
+                company=name,
+                color="#2196F3",  # 蓝色
+            )
+            G.add_edge(
+                person_id, name,
+                relation="任职于",
+                edge_type="personnel",
+            )
+
+        # 添加供应商节点
+        for supplier in company.get("supply_chain", {}).get("key_suppliers", []):
+            supplier_name = supplier.split("（")[0].split("(")[0].strip()
+            if not G.has_node(supplier_name):
+                G.add_node(
+                    supplier_name,
+                    node_type="供应商",
+                    is_sanctioned=False,
+                    risk_level="正常",
+                    color="#FF9800",  # 橙色
+                )
+            G.add_edge(
+                supplier_name, name,
+                relation="供应",
+                detail=supplier,
+                edge_type="supply",
+            )
+
+        # 添加客户节点
+        for customer in company.get("supply_chain", {}).get("key_customers", []):
+            customer_name = customer.split("（")[0].split("(")[0].strip()
+            if not G.has_node(customer_name):
+                G.add_node(
+                    customer_name,
+                    node_type="客户",
+                    is_sanctioned=False,
+                    risk_level="正常",
+                    color="#9C27B0",  # 紫色
+                )
+            G.add_edge(
+                name, customer_name,
+                relation="供货给",
+                edge_type="customer",
+            )
+
+
+def _add_supply_chain_edges(G: nx.DiGraph):
+    """从供应链关系文件添加更详细的边"""
+    filepath = DATA_DIR / "supply_chain.json"
+    with open(filepath, "r", encoding="utf-8") as f:
+        data = json.load(f)
+
+    # 添加供应关系
+    for rel in data.get("supply_relations", []):
+        from_node = rel["from"]
+        to_node = rel["to"]
+
+        # 确保节点存在
+        if not G.has_node(from_node):
+            G.add_node(from_node, node_type="供应商", is_sanctioned=False,
+                       risk_level="正常", color="#FF9800")
+        if not G.has_node(to_node):
+            G.add_node(to_node, node_type="企业", is_sanctioned=False,
+                       risk_level="正常", color="#4CAF50")
+
+        G.add_edge(
+            from_node, to_node,
+            relation=rel["relation"],
+            critical=rel.get("critical", False),
+            status=rel.get("status", "正常"),
+            edge_type="supply",
+        )
+
+    # 添加投资关系
+    for rel in data.get("investment_relations", []):
+        from_node = rel["from"]
+        to_node = rel["to"]
+
+        if not G.has_node(from_node):
+            G.add_node(from_node, node_type="投资方", is_sanctioned=False,
+                       risk_level="正常", color="#607D8B")
+
+        G.add_edge(
+            from_node, to_node,
+            relation=rel["relation"],
+            share_ratio=rel.get("share_ratio", 0),
+            edge_type="investment",
+        )
+
+
+def _mark_sanctioned_nodes(G: nx.DiGraph):
+    """标记受制裁的节点，并向下游传播风险"""
+    filepath = DATA_DIR / "entity_list.json"
+    with open(filepath, "r", encoding="utf-8") as f:
+        entities = json.load(f)
+
+    # 收集所有受制裁实体的名称和别名
+    sanctioned_names = set()
+    for entity in entities:
+        sanctioned_names.add(entity["entity_name"])
+        for alias in entity.get("aliases", []):
+            sanctioned_names.add(alias)
+
+    # 标记图谱中的受制裁节点
+    for node in G.nodes():
+        for sname in sanctioned_names:
+            if node in sname or sname in node:
+                G.nodes[node]["is_sanctioned"] = True
+                G.nodes[node]["risk_level"] = "高危"
+                G.nodes[node]["color"] = "#F44336"  # 红色
+                break
+
+
+def get_node_info(G: nx.DiGraph, node_name: str) -> dict:
+    """获取节点详细信息"""
+    if node_name not in G:
+        return {"error": f"节点 '{node_name}' 不存在"}
+
+    node_data = dict(G.nodes[node_name])
+    predecessors = list(G.predecessors(node_name))
+    successors = list(G.successors(node_name))
+
+    return {
+        "name": node_name,
+        "attributes": node_data,
+        "upstream": predecessors,
+        "downstream": successors,
+        "degree": G.degree(node_name),
+    }
+
+
+def get_graph_stats(G: nx.DiGraph) -> dict:
+    """获取图谱统计信息"""
+    node_types = {}
+    for _, data in G.nodes(data=True):
+        t = data.get("node_type", "未知")
+        node_types[t] = node_types.get(t, 0) + 1
+
+    sanctioned_count = sum(
+        1 for _, data in G.nodes(data=True) if data.get("is_sanctioned", False)
+    )
+
+    return {
+        "total_nodes": G.number_of_nodes(),
+        "total_edges": G.number_of_edges(),
+        "node_types": node_types,
+        "sanctioned_nodes": sanctioned_count,
+        "density": nx.density(G),
+    }