Hermes CI Fix
fdc42d443d
- kpi_causality 加列: source_type/verify_status/verified_at/verified_by/entity_id(回填)
- 核心服务: app/services/causality_verification.py (Pearson+滞后对齐+状态机)
- 数据验证脚本: scripts/correlation-check.py (月度cron, 输出JSON报告)
- API: create/update支持source_type, GET /verify-status, PUT /{id}/verify(人工确认)
- 全部端点按entity_id账套隔离, kpi/{id}/network/simulate补跨企业校验
- 前端: KPIDetail因果链页显示验证状态徽标(数据证实/存疑/待检)
- 测试: test_causality_verification.py 37用例 + 原因果链测试全过(59个)
- 50条因果链首轮验证: 1数据证实(#37渠补率到净利润lag1 r=-0.89), 4存疑, 45待检(数据不足)
96 lines
4.0 KiB
Python
96 lines
4.0 KiB
Python
"""kpi_causality 因果链验证机制迁移脚本 (2026-08-27 P2)
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加列:
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- source_type: varchar(20) 建链来源 AI_suggested/manual/imported
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- verify_status: varchar(20) 验证状态 pending/data_verified/human_verified/disputed
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- verified_at: datetime 验证时间
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- verified_by: varchar(50) 验证人/AI/脚本
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- entity_id: int 多租户隔离 (2026-08-27 收官补齐)
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幂等: 列已存在则跳过; entity_id 回填只更新 NULL/0 行。
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用法: python scripts/migrate_causality_verification.py
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"""
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import logging
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import sys
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from pathlib import Path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from sqlalchemy import text
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from app.database import get_engine
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(message)s")
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logger = logging.getLogger("migrate-causality-verification")
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COLUMNS = [
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("source_type", "ALTER TABLE kpi_causality ADD COLUMN source_type VARCHAR(20) NOT NULL DEFAULT 'manual' COMMENT '建链来源 AI_suggested/manual/imported'"),
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("verify_status", "ALTER TABLE kpi_causality ADD COLUMN verify_status VARCHAR(20) NOT NULL DEFAULT 'pending' COMMENT '验证状态 pending/data_verified/human_verified/disputed'"),
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("verified_at", "ALTER TABLE kpi_causality ADD COLUMN verified_at DATETIME NULL COMMENT '验证时间'"),
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("verified_by", "ALTER TABLE kpi_causality ADD COLUMN verified_by VARCHAR(50) NULL COMMENT '验证人/AI/脚本'"),
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("entity_id", "ALTER TABLE kpi_causality ADD COLUMN entity_id INT NOT NULL DEFAULT 1 COMMENT '企业ID (多租户隔离 2026-08-27)'"),
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]
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def run():
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engine = get_engine()
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with engine.connect() as conn:
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# 1. 检查表是否存在
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exists = conn.execute(text(
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"SELECT COUNT(*) FROM information_schema.tables WHERE table_schema = DATABASE() AND table_name = 'kpi_causality'"
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)).scalar()
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if not exists:
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logger.error("kpi_causality 表不存在，跳过")
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return 1
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# 2. 现有列
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existing = {r[0] for r in conn.execute(text(
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"SELECT column_name FROM information_schema.columns WHERE table_schema = DATABASE() AND table_name = 'kpi_causality'"
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))}
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logger.info("现有列: %s", sorted(existing))
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# 3. 加列（幂等）
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for col, ddl in COLUMNS:
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if col in existing:
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logger.info("列 %s 已存在，跳过", col)
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else:
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conn.execute(text(ddl))
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logger.info("已添加列 %s", col)
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# 4. 回填 entity_id（无条件从 source KPI 对齐，纠正默认值偏差）
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# 仅当来源KPI存在才回填；无来源KPI的孤儿链保持原值
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conn.execute(text(
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"UPDATE kpi_causality c JOIN kpi_definitions k ON k.id = c.source_kpi_id "
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"SET c.entity_id = k.entity_id"
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))
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orphan = conn.execute(text(
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"SELECT COUNT(*) FROM kpi_causality c LEFT JOIN kpi_definitions k ON k.id = c.source_kpi_id "
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"WHERE k.id IS NULL"
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)).scalar()
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if orphan:
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logger.warning("%d 条因果链无来源KPI（孤儿链）", orphan)
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else:
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logger.info("entity_id 已全部按来源KPI回填")
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# 5. 验证
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cols = {r[0] for r in conn.execute(text(
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"SELECT column_name FROM information_schema.columns WHERE table_schema = DATABASE() AND table_name = 'kpi_causality'"
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))}
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missing = {c for c, _ in COLUMNS} - cols
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if missing:
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logger.error("仍有缺失列: %s", missing)
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return 1
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row = conn.execute(text(
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"SELECT COUNT(*) FROM kpi_causality WHERE entity_id IS NULL OR entity_id = 0"
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)).scalar()
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if row:
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logger.error("仍有 %d 行 entity_id 为空", row)
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return 1
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total = conn.execute(text("SELECT COUNT(*) FROM kpi_causality")).scalar()
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logger.info("迁移完成: kpi_causality %d 条, 新列: source_type/verify_status/verified_at/verified_by/entity_id", total)
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return 0
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if __name__ == "__main__":
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sys.exit(run())
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