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第一章:依赖注入核心原理 1.1 依赖树构建机制 1 2 3 4 5 6 7 8 9 10 11 12 13 14 from fastapi import Dependsdef auth_service (): return OAuth2Scheme() def db_conn (auth: dict = Depends(auth_service ) ): return Database(creds=auth) @app.get("/data" ) async def get_data (conn=Depends(db_conn ) ): return conn.query()
依赖树可视化 :
1 2 graph TD get_data --> db_conn --> auth_service
1.2 作用域控制 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 from fastapi import Depends, FastAPIfrom sqlalchemy.orm import sessionmakerSessionLocal = sessionmaker(autocommit=False ) def get_db (): db = SessionLocal() try : yield db finally : db.close() cache = LRUCache(size=100 ) def get_cache (): return cache
第二章:Pydantic深度集成 2.1 动态模型注入 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 from pydantic import create_modeldef dynamic_model (fields: dict ): return create_model('DynamicModel' , **fields) class FilterFactory : @classmethod def create (cls, model: BaseModel ): class QueryParams (model ): limit: int = 100 offset: int = 0 return QueryParams @app.get("/search" ) async def search (params=Depends(FilterFactory.create(User ) ) ): return params.dict ()
2.2 校验逻辑复用 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 from pydantic import validator, root_validatorclass GeoValidator : @classmethod def lat_validator (cls, v ): if not -90 <= v <= 90 : raise ValueError("纬度范围错误" ) return v class Location (BaseModel ): lat: float lng: float _validate_lat = validator('lat' , allow_reuse=True )(GeoValidator.lat_validator)
第三章:高级注入模式 3.1 工厂模式注入 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 class NotificationClient : def __init__ (self, type : str ): self .client = self ._create_client(type ) @staticmethod def _create_client (type ): return { "sms" : SMSClient(), "email" : EmailClient() }[type ] def get_notifier (type : str ): def _factory (): return NotificationClient(type ) return _factory @app.post("/alert" ) async def send_alert ( notifier: NotificationClient = Depends(get_notifier("sms" ) ) ): notifier.client.send()
3.2 条件依赖注入 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 from fastapi import Headerdef feature_flag_dep (feature_name: str ): class FeatureChecker : def __init__ (self, enabled: bool = Depends(check_feature_enabled ) ): if not enabled: raise HTTPException(403 , "功能未启用" ) return FeatureChecker def check_feature_enabled ( feature: str = Header(... ), config: Config = Depends(get_config ) ) -> bool : return config.is_enabled(feature) @app.get("/beta" ) async def beta_feature ( checker=Depends(feature_flag_dep("beta" ) ) ): return "功能可用"
第四章:错误处理与调试 4.1 依赖链错误传播 1 2 3 4 5 6 7 8 9 10 11 12 13 14 class DatabaseError (Exception ): pass def db_dep (): try : yield connection except Exception as e: raise DatabaseError() from e @app.exception_handler(DatabaseError ) async def handle_db_error (request, exc ): return JSONResponse(500 , {"detail" : "数据库异常" })
4.2 依赖图可视化调试 1 2 3 4 5 6 7 8 9 10 11 from fastapi.dependencies.utils import solve_dependenciesdef print_dependency_tree (): routes = app.routes for route in routes: if isinstance (route, APIRoute): solved = solve_dependencies(route.dependant) print (f"Route {route.path} :" ) for dep in solved.flat_graph(): print (f"└─ {dep.call.__name__} " )
第五章:测试与维护 5.1 依赖覆盖测试 1 2 3 4 5 6 7 8 9 10 11 12 from fastapi.testclient import TestClientdef override_dep (): return MockDatabase() app.dependency_overrides[get_db] = override_dep client = TestClient(app) response = client.get("/data" ) assert "mock" in response.text
5.2 依赖版本管理 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 from packaging.version import parseclass VersionedDep : def __init__ (self, api_version: str = Header(... ) ): self .version = parse(api_version) def check_min_version (self, min_version: str ): if self .version < parse(min_version): raise HTTPException(400 , "版本过低" ) @app.get("/new-feature" ) async def new_feature ( dep: VersionedDep = Depends( ), checker=Depends(dep.check_min_version("2.3" ) ) ): return "功能可用"
课后Quiz Q1:如何实现跨路由共享查询参数? A) 在每个路由重复定义参数 B) 使用全局变量存储参数 C) 通过依赖注入共享参数
Q2:依赖注入的yield语句有什么作用?
实现请求后清理逻辑 提高依赖执行速度 支持异步生成器 Q3:如何测试被覆盖的依赖项?
错误解决方案速查表 错误类型 解决方案 422 Validation Error 检查请求参数是否匹配Pydantic模型定义 DIResolutionError 确认依赖树没有循环引用,所有依赖项已正确定义 DependencyInstantiationError 检查yield依赖是否正确处理异常,验证上下文管理器实现
扩展阅读 《Dependency Injection Principles》 - 依赖注入设计原则深度解析《Clean Architecture in Python》 - Python整洁架构实践指南《FastAPI Internals》 - 框架源码分析与实现原理架构箴言 :优秀的依赖注入设计应遵循SOLID原则,特别是依赖倒置原则(DIP)。建议使用依赖图分析工具保持注入层次不超过5层,对高频依赖实施缓存策略,并定期进行依赖关系审计。
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