feat: 全量功能模块开发与集成测试修复

- 新增后端模块：Alert、APIAsset、Compliance、Lineage、Masking、Risk、SchemaChange、Unstructured、Watermark - 新增前端模块页面与API接口 - 新增Alembic迁移脚本(002-014)覆盖全量业务表 - 新增测试数据生成脚本与集成测试脚本 - 修复metadata模型JSON类型导入缺失导致启动失败的问题 - 修复前端Alert/APIAsset页面request模块路径错误 - 更新docker-compose与开发计划文档
2026-04-25 08:51:38 +08:00
parent 8b2bc84399
commit 6d70520e79
110 changed files with 6125 additions and 87 deletions
@@ -0,0 +1,59 @@
+"""
+Generate synthetic manual-labeled data for ML model training/demo.
+Run this script after metadata has been scanned so there are columns to label.
+"""
+import random
+import sys
+import os
+
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), ".."))
+
+from app.core.database import SessionLocal
+from app.models.metadata import DataColumn
+from app.models.classification import Category
+from app.models.project import ClassificationResult
+
+
+def main():
+    db = SessionLocal()
+    try:
+        columns = db.query(DataColumn).limit(300).all()
+        if not columns:
+            print("No columns found in database. Please scan a data source first.")
+            return
+
+        categories = db.query(Category).filter(Category.level == 2).all()
+        if not categories:
+            print("No sub-categories found.")
+            return
+
+        # Clear old manual labels to avoid duplicates
+        db.query(ClassificationResult).filter(ClassificationResult.source == "manual").delete()
+        db.commit()
+
+        count = 0
+        for col in columns:
+            # Deterministic pseudo-random based on column name for reproducibility
+            rng = random.Random(col.name)
+            cat = rng.choice(categories)
+            # Create a fake manual result (project_id=1 assumed to exist or None)
+            result = ClassificationResult(
+                project_id=None,
+                column_id=col.id,
+                category_id=cat.id,
+                level_id=cat.parent.level if cat.parent else 3,  # fallback
+                source="manual",
+                confidence=1.0,
+                status="manual",
+            )
+            db.add(result)
+            count += 1
+
+        db.commit()
+        print(f"Generated {count} manual labels across {len(categories)} categories.")
+    finally:
+        db.close()
+
+
+if __name__ == "__main__":
+    main()