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51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
# AI辅助生成：deepseek-v3-2，2026年3月20日
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import os
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from dotenv import load_dotenv
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from sqlalchemy import create_engine, event
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from sqlalchemy.orm import sessionmaker
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load_dotenv()
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# 数据库连接 URL，可从 .env 配置，默认 SQLite
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SQLALCHEMY_DATABASE_URL = os.getenv("SQLALCHEMY_DATABASE_URL", "sqlite:///./data/demo.db")
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# 创建数据库引擎
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# 增加 timeout=30 允许连接在遇到 locked 时最多等待 30 秒，而不是直接报错
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engine = create_engine(
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SQLALCHEMY_DATABASE_URL,
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connect_args={"check_same_thread": False, "timeout": 30}
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)
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# ==========================================
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# 监听 SQLite 连接，注入 PRAGMA 指令
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# ==========================================
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@event.listens_for(engine, "connect")
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def set_sqlite_pragma(dbapi_connection, connection_record):
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cursor = dbapi_connection.cursor()
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# 1. 开启 WAL 模式：读写分离
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cursor.execute("PRAGMA journal_mode=WAL;")
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# 2. 优化同步模式：在 WAL 模式下，NORMAL 既能保证不丢数据，又能大幅提升写入速度
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cursor.execute("PRAGMA synchronous=NORMAL;")
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# 3. 强制开启外键约束：极其重要！SQLite 默认不检查外键，这行能保护你的多态关联不乱套
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cursor.execute("PRAGMA foreign_keys=ON;")
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cursor.close()
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# 创建数据库会话工厂
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine)
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# 依赖注入函数：每个请求过来时，给它发一个数据库连接，请求结束时自动关闭
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def get_db():
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db = SessionLocal()
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try:
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yield db
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finally:
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db.close()
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