yuzhiran
0258a9af9f
Comprehensive DB migration: TopicField cleanup (5 old deactivated, 3 new updated), Topic reassignment (43/47 migrated), Article cleanup (15 deleted), CollectorCategory/Cleaning (12 old deactivated), TrendFieldMapping sync (11 entries) Ultraworked with Sisyphus Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>
267 lines
13 KiB
Python
267 lines
13 KiB
Python
#!/usr/bin/env python3
|
||
"""
|
||
内容聚焦迁移脚本（Phase 2）
|
||
目标：将数据库从"6领域分散"迁移到"3领域聚焦（AI与效率、科技人文、未来工作方式）"
|
||
|
||
执行：python3 scripts/migrate_content_focus.py
|
||
"""
|
||
|
||
import sys, json, logging, datetime
|
||
from pathlib import Path
|
||
|
||
PROJECT_ROOT = Path(__file__).resolve().parent.parent
|
||
sys.path.insert(0, str(PROJECT_ROOT))
|
||
sys.path.insert(0, str(PROJECT_ROOT / "platform" / "backend"))
|
||
|
||
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
|
||
logger = logging.getLogger(__name__)
|
||
|
||
# 新领域配置（与 initial_data.py 对齐）
|
||
NEW_FIELDS = [
|
||
{"name": "AI与效率", "icon": "🤖", "color": "#764ba2", "description": "AI工具、AI工作流、效率方法、前沿资讯", "sort_order": 1},
|
||
{"name": "科技人文", "icon": "🔬", "color": "#f56c6c", "description": "AI伦理、科技反思、数字生活、人机关系", "sort_order": 2},
|
||
{"name": "未来工作方式", "icon": "💼", "color": "#667eea", "description": "远程工作、AI时代职业转型、一人企业", "sort_order": 3},
|
||
]
|
||
|
||
# 旧领域名称 → 新领域名称映射
|
||
FIELD_MIGRATION_MAP = {
|
||
"可持续生活系统": "AI与效率",
|
||
"可持续生活": "AI与效率",
|
||
"数字游民": "未来工作方式",
|
||
"个人成长": "科技人文",
|
||
"个人知识工厂": "AI与效率",
|
||
"科技人文交叉": "科技人文",
|
||
}
|
||
|
||
# 新采集分类
|
||
NEW_CATEGORIES = [
|
||
{"name": "AI前沿资讯", "search_query": "AI 人工智能 大模型 2026 前沿", "description": "AI行业动态、大模型发布、技术突破", "sort_order": 1, "is_active": True},
|
||
{"name": "AI工具实测", "search_query": "AI工具 效率提升 AI工作流 2026", "description": "AI工具评测、效率工作流、实操指南", "sort_order": 2, "is_active": True},
|
||
{"name": "AI与职场", "search_query": "AI 裁员 职业转型 AI技能 远程工作 2026", "description": "AI对就业影响、职业转型、技能升级", "sort_order": 3, "is_active": True},
|
||
{"name": "AI生活化", "search_query": "AI陪伴 AI心理咨询 AI生活助手 2026", "description": "AI心理咨询/生活搭子/AI人格化", "sort_order": 4, "is_active": True},
|
||
{"name": "科技人文", "search_query": "AI伦理 数字生活 科技反思 人机关系 2026", "description": "AI伦理/数字生活反思/科技温度", "sort_order": 5, "is_active": True},
|
||
]
|
||
|
||
# 旧分类名称（待停用）
|
||
OLD_CATEGORY_NAMES = ["循环消费", "低碳出行", "干净饮食", "零浪费生活", "绿色家电与节能", "碳普惠", "环保科技产品"]
|
||
|
||
# 新平台 tags
|
||
NEW_PLATFORM_TAGS = {
|
||
"zhihu": ["科技", "AI", "效率", "职场", "教育", "远程工作", "未来工作", "工具"],
|
||
"wechat": ["科技", "AI", "效率", "职场", "教育", "远程工作", "未来工作", "工具"],
|
||
"xiaohongshu": ["AI", "效率", "科技", "工具", "职场", "生活", "学习方法"],
|
||
}
|
||
|
||
|
||
def migrate():
|
||
try:
|
||
from app.database import SessionLocal
|
||
from app.models import TopicField, Topic, Article, CollectorCategory, CollectorSource, PlatformConfig
|
||
except ImportError as e:
|
||
logger.error(f"导入失败（确保在项目根目录执行）: {e}")
|
||
sys.exit(1)
|
||
|
||
db = SessionLocal()
|
||
try:
|
||
# ========== 1. 处理 TopicField ==========
|
||
logger.info("--- 处理 TopicField ---")
|
||
existing_fields = {f.name: f for f in db.query(TopicField).all()}
|
||
field_id_map = {} # name → id
|
||
|
||
for nf in NEW_FIELDS:
|
||
if nf["name"] in existing_fields:
|
||
f = existing_fields[nf["name"]]
|
||
f.icon = nf["icon"]
|
||
f.color = nf["color"]
|
||
f.description = nf["description"]
|
||
f.sort_order = nf["sort_order"]
|
||
f.is_active = True
|
||
field_id_map[nf["name"]] = f.id
|
||
logger.info(f" 更新领域: {nf['name']} (id={f.id})")
|
||
else:
|
||
f = TopicField(**nf)
|
||
db.add(f)
|
||
db.flush()
|
||
field_id_map[nf["name"]] = f.id
|
||
logger.info(f" 创建领域: {nf['name']} (id={f.id})")
|
||
|
||
# 停用旧领域
|
||
for old_name in ["可持续生活系统", "可持续生活", "数字游民", "个人成长", "个人知识工厂"]:
|
||
if old_name in existing_fields and old_name not in [nf["name"] for nf in NEW_FIELDS]:
|
||
f = existing_fields[old_name]
|
||
f.is_active = False
|
||
logger.info(f" 停用旧领域: {old_name} (id={f.id})")
|
||
db.commit()
|
||
|
||
# ========== 2. 迁移 Topic ==========
|
||
logger.info("--- 迁移 Topic ---")
|
||
topics = db.query(Topic).all()
|
||
topic_count = len(topics)
|
||
migrated_count = 0
|
||
for t in topics:
|
||
old_field = t.field_name or ""
|
||
new_field = None
|
||
for old_k, new_v in FIELD_MIGRATION_MAP.items():
|
||
if old_k in old_field or old_field in old_k:
|
||
new_field = new_v
|
||
break
|
||
if not new_field and t.field_id:
|
||
# 按名称猜测
|
||
for old_k, new_v in FIELD_MIGRATION_MAP.items():
|
||
if old_k[:4] in old_field or old_field[:4] in old_k:
|
||
new_field = new_v
|
||
break
|
||
if new_field and new_field in field_id_map:
|
||
t.field_id = field_id_map[new_field]
|
||
t.field_name = new_field
|
||
migrated_count += 1
|
||
elif t.field_id and t.field_name not in [nf["name"] for nf in NEW_FIELDS]:
|
||
# 无法映射的旧领域，统一设为"AI与效率"
|
||
if "AI与效率" in field_id_map:
|
||
t.field_id = field_id_map["AI与效率"]
|
||
t.field_name = "AI与效率"
|
||
migrated_count += 1
|
||
db.commit()
|
||
logger.info(f" 共 {topic_count} 个 Topic，已迁移 {migrated_count} 个")
|
||
|
||
# ========== 3. 清理旧 Article ==========
|
||
logger.info("--- 清理旧 Article ---")
|
||
all_articles = db.query(Article).all()
|
||
deleted_articles = []
|
||
for a in all_articles:
|
||
topic = db.query(Topic).filter(Topic.id == a.topic_id).first()
|
||
if topic:
|
||
# 只保留 topic 仍然活跃且在新领域内的
|
||
tf = db.query(TopicField).filter(TopicField.id == topic.field_id).first()
|
||
if tf and tf.is_active and tf.name in [nf["name"] for nf in NEW_FIELDS]:
|
||
continue
|
||
# 该 Article 关联的 topic 已失效，删除
|
||
deleted_articles.append(a.id)
|
||
db.delete(a)
|
||
db.commit()
|
||
logger.info(f" 已删除 {len(deleted_articles)} 篇旧 Article")
|
||
|
||
# ========== 4. 清理 CollectorCategory ==========
|
||
logger.info("--- 清理 CollectorCategory ---")
|
||
existing_cats = {c.name: c for c in db.query(CollectorCategory).all()}
|
||
|
||
# 创建新分类
|
||
for nc in NEW_CATEGORIES:
|
||
if nc["name"] in existing_cats:
|
||
c = existing_cats[nc["name"]]
|
||
c.search_query = nc["search_query"]
|
||
c.description = nc["description"]
|
||
c.sort_order = nc["sort_order"]
|
||
c.is_active = True
|
||
logger.info(f" 更新采集分类: {nc['name']}")
|
||
else:
|
||
db.add(CollectorCategory(**nc))
|
||
logger.info(f" 创建采集分类: {nc['name']}")
|
||
|
||
# 停用旧分类
|
||
for old_name in OLD_CATEGORY_NAMES:
|
||
if old_name in existing_cats:
|
||
c = existing_cats[old_name]
|
||
c.is_active = False
|
||
logger.info(f" 停用旧采集分类: {old_name}")
|
||
|
||
# 删除旧 '可持续生活' 和 '可持续发展' 变体
|
||
for cname, cobj in existing_cats.items():
|
||
if cname not in [nc["name"] for nc in NEW_CATEGORIES] and cname not in OLD_CATEGORY_NAMES:
|
||
if any(kw in cname for kw in ["可持续", "环保", "绿色", "低碳", "零浪费", "循环"]):
|
||
cobj.is_active = False
|
||
logger.info(f" 停用旧采集分类: {cname}")
|
||
db.commit()
|
||
|
||
# ========== 5. 清理 CollectorSource ==========
|
||
logger.info("--- 清理 CollectorSource ---")
|
||
all_sources = db.query(CollectorSource).all()
|
||
deactivated_sources = 0
|
||
for s in all_sources:
|
||
# 停用非 AI/科技 类采集源
|
||
if s.focus and any(kw in s.focus for kw in ["可持续", "环保", "绿色", "低碳", "零浪费"]):
|
||
s.is_active = False
|
||
deactivated_sources += 1
|
||
# 旧 URL 不再可访问的源
|
||
if s.url and any(domain in s.url for domain in ["greenbiz.com", "sustainablebrands.com", "treehugger.com"]):
|
||
s.is_active = False
|
||
deactivated_sources += 1
|
||
# 检查 category_id 是否对应已停用的分类
|
||
if s.category_id:
|
||
cat = db.query(CollectorCategory).filter(CollectorCategory.id == s.category_id).first()
|
||
if cat and not cat.is_active:
|
||
s.is_active = False
|
||
deactivated_sources += 1
|
||
# 新增源（由 initial_data.py 的补充逻辑处理）
|
||
for new_src in [
|
||
{"name": "AI前沿搜索", "source_type": "web_search", "query": "AI 人工智能 大模型 前沿 2026", "credibility": "medium", "focus": "AI前沿资讯", "sort_order": 1, "is_active": True},
|
||
{"name": "AI工具搜索", "source_type": "web_search", "query": "AI工具 效率提升 AI工作流 2026", "credibility": "medium", "focus": "AI工具实测", "sort_order": 2, "is_active": True},
|
||
]:
|
||
existing = db.query(CollectorSource).filter(CollectorSource.name == new_src["name"]).first()
|
||
if not existing:
|
||
db.add(CollectorSource(**new_src))
|
||
logger.info(f" 创建采集源: {new_src['name']}")
|
||
db.commit()
|
||
logger.info(f" 已停用 {deactivated_sources} 个旧采集源")
|
||
|
||
# ========== 6. 更新 PlatformConfig tags ==========
|
||
logger.info("--- 更新 PlatformConfig tags ---")
|
||
for p in db.query(PlatformConfig).all():
|
||
if p.platform in NEW_PLATFORM_TAGS:
|
||
rules = p.compliance_rules or {}
|
||
if isinstance(rules, dict) and "allowed_tags" in rules:
|
||
rules["allowed_tags"] = NEW_PLATFORM_TAGS[p.platform]
|
||
p.compliance_rules = rules
|
||
logger.info(f" 更新平台标签: {p.platform}")
|
||
db.commit()
|
||
|
||
# ========== 7. 更新 TrendFieldMapping ==========
|
||
logger.info("--- 更新 TrendFieldMapping ---")
|
||
from app.models import TrendFieldMapping
|
||
new_mappings = [
|
||
{"trend_keyword": "AI工具", "field_name": "AI与效率", "sort_order": 1},
|
||
{"trend_keyword": "AI创作", "field_name": "AI与效率", "sort_order": 2},
|
||
{"trend_keyword": "AI职场", "field_name": "AI与效率", "sort_order": 3},
|
||
{"trend_keyword": "效率工具", "field_name": "AI与效率", "sort_order": 4},
|
||
{"trend_keyword": "未来工作", "field_name": "未来工作方式", "sort_order": 5},
|
||
{"trend_keyword": "远程工作", "field_name": "未来工作方式", "sort_order": 6},
|
||
{"trend_keyword": "AI就业", "field_name": "未来工作方式", "sort_order": 7},
|
||
{"trend_keyword": "科技人文", "field_name": "科技人文", "sort_order": 8},
|
||
{"trend_keyword": "数字生活", "field_name": "科技人文", "sort_order": 9},
|
||
{"trend_keyword": "AI伦理", "field_name": "科技人文", "sort_order": 10},
|
||
{"trend_keyword": "AI情感", "field_name": "AI与效率", "sort_order": 11},
|
||
]
|
||
existing_mappings = {m.trend_keyword: m for m in db.query(TrendFieldMapping).all()}
|
||
# 标记旧的映射为停用
|
||
for keyword, mapping in existing_mappings.items():
|
||
if keyword not in [nm["trend_keyword"] for nm in new_mappings]:
|
||
mapping.is_active = False
|
||
# 创建/更新新映射
|
||
for nm in new_mappings:
|
||
if nm["trend_keyword"] in existing_mappings:
|
||
m = existing_mappings[nm["trend_keyword"]]
|
||
m.field_name = nm["field_name"]
|
||
m.sort_order = nm["sort_order"]
|
||
m.is_active = True
|
||
else:
|
||
db.add(TrendFieldMapping(**nm))
|
||
db.commit()
|
||
logger.info(f" 已同步 {len(new_mappings)} 条 TrendFieldMapping")
|
||
|
||
logger.info("=" * 50)
|
||
logger.info("✅ DB 迁移完成")
|
||
logger.info("=" * 50)
|
||
|
||
except Exception as e:
|
||
import traceback
|
||
traceback.print_exc()
|
||
logger.error(f"迁移失败: {e}")
|
||
db.rollback()
|
||
sys.exit(1)
|
||
finally:
|
||
db.close()
|
||
|
||
|
||
if __name__ == "__main__":
|
||
migrate()
|