基于类的依赖与 Yield 依赖
学习使用类创建更复杂的依赖,并利用 `yield` 管理资源的初始化和清理逻辑。
基于类的依赖与 Yield 依赖 是 CoddyKit 上的免费 FastAPI Backend Development Bootcamp 课时。 这是第 3 节课,共 4 节。 你可以在下方免费阅读本课时的完整内容 — 然后在浏览器中使用内置代码编辑器和全天候 AI 导师进行实践。 这是 FastAPI Backend Development Bootcamp 学习路径的一部分,你的进度在网页和 CoddyKit 应用中同步。 FastAPI Backend Development Bootcamp 课程共包含 4 节课。
本课时的部分内容尚未翻译,以英文显示。
Beyond Simple Function Dependencies
In previous lessons, we learned about basic function-based dependencies in FastAPI. These are great for simple tasks like validation or injecting common values.
But what if your dependency needs to maintain state, accept configuration, or manage resources that require both setup and cleanup? That's where class-based and yield dependencies come in!
Why Use Class-Based Dependencies?
Class-based dependencies offer several advantages for more complex scenarios:
- Organization: Encapsulate related logic and data within a class.
- State: Classes can hold internal state, which can be useful (though be mindful of request isolation).
- Configuration: Easily pass parameters to the dependency during its instantiation.
- Testability: Easier to mock or inject specific class instances for testing.
Defining a Class Dependency
To create a class-based dependency, you define a Python class. FastAPI can then use an instance of this class. If your class has a __call__ method, FastAPI will invoke it to get the dependency's value.
Let's see a simple example:
class MyService:
def __init__(self):
self.message = "Welcome from MyService!"
def __call__(self):
# This method is called by FastAPI to get the value
return self.message
# Simulate FastAPI's usage:
# FastAPI would instantiate MyService() once or per request
service_instance = MyService()
# It then calls the __call__ method to get the value
dependency_value = service_instance()
print(dependency_value)How FastAPI Handles Class Dependencies
When you use Depends(MyClass), FastAPI will:
- Create an instance of
MyClass. - If
MyClasshas a__call__method, it will call it and use the returned value as the dependency. - Otherwise, it will use the instance of
MyClassitself as the dependency.
If you use Depends(MyClass()), you're passing an already instantiated object, and FastAPI will simply use that object (and its __call__ method if present).
Class Dependencies with Parameters
A major benefit of class-based dependencies is the ability to pass parameters to their constructor. This is perfect for injecting configuration or other dependencies into your service class.
Imagine a service that needs an API key:
class ExternalApiService:
def __init__(self, api_key: str):
self.api_key = api_key
self.base_url = "https://api.external.com"
def __call__(self):
return f"API Service configured with key: {self.api_key}"
# In a real FastAPI app, the api_key might come from
# an environment variable or another dependency.
# Here, we simulate instantiation with different keys.
prod_api = ExternalApiService(api_key="prod_secret_123")
dev_api = ExternalApiService(api_key="dev_test_abc")
print(prod_api())
print(dev_api())Introducing Yield Dependencies
Some resources, like database connections or file handlers, need not only to be set up but also properly cleaned up afterwards. This is where yield dependencies shine!
A yield dependency is a generator function that allows you to run code before the endpoint is executed (setup) and after the response is sent (teardown).
Yield for Resource Setup
The code before the yield statement in your dependency function is executed as setup logic. The value that is yielded is what your endpoint function will receive as a dependency.
def get_database_session():
print("DB: Establishing connection...") # Setup logic
db_session = {"id": 1, "status": "active"} # Simulate a session
yield db_session # This value is passed to the dependent function
# Teardown logic (after yield) would go here
# Simulate a function that uses the dependency
def process_data(session):
print(f"Endpoint: Processing data with session ID: {session['id']}")
# How FastAPI conceptually uses it:
# 1. Calls get_database_session()
# 2. Takes the yielded value
# 3. Passes it to process_data()
session_generator = get_database_session()
active_session = next(session_generator) # Runs setup, gets yielded value
process_data(active_session)
# FastAPI would then ensure the generator is closed, triggering teardown.Yield for Resource Teardown
The power of yield dependencies is in their ability to perform cleanup. Any code placed after the yield statement will execute once the request has finished and the response has been sent.
This is typically done within a try...finally block to guarantee cleanup, even if errors occur.
def get_file_handle():
print("File: Opening 'log.txt'...")
file_handle = open("log.txt", "w") # Simulate opening a file
try:
yield file_handle # Provide the file handle
finally:
print("File: Closing 'log.txt'.")
file_handle.close() # Teardown logic: close the file
# Simulate a function using the dependency
def write_log(f_handle):
f_handle.write("Lesson content generated.\n")
print("Endpoint: Wrote to log file.")
# Manual simulation of FastAPI's lifecycle:
file_generator = get_file_handle()
current_file = next(file_generator) # Setup runs
write_log(current_file)
# This step would be handled by FastAPI to trigger teardown
try:
next(file_generator) # Continues generator, runs finally block
except StopIteration:
print("Generator exhausted, teardown complete.")Combining Class-based & Yield Dependencies
You can use both class-based and yield dependencies together! For instance, a class-based dependency might provide configuration for a database, and a yield dependency would then use that configuration to establish and close a database connection.
This allows for highly modular and robust resource management within your FastAPI application.
Quick Check
Consider the benefits and use cases for advanced dependency injection patterns.
Lesson Summary
Great job! In this lesson, you've leveled up your understanding of FastAPI dependencies.
- Class-based dependencies help organize complex logic, maintain state, and accept configuration.
- Yield dependencies (generator functions) are powerful for managing resources that require both setup (before
yield) and guaranteed teardown (afteryield, often in afinallyblock).
These patterns make your FastAPI applications more robust, maintainable, and easier to test.
常见问题解答
「基于类的依赖与 Yield 依赖」课时是免费的吗?
是的 — 「基于类的依赖与 Yield 依赖」的完整文本可在网页上免费阅读。要进行交互式练习(内置代码编辑器和全天候 AI 导师)并解锁 FastAPI Backend Development Bootcamp 课程的其余内容,请升级到 CoddyKit PRO。 FastAPI Backend Development Bootcamp 课程共包含 4 节课。
「基于类的依赖与 Yield 依赖」这节课中我会学到什么?
学习使用类创建更复杂的依赖,并利用 `yield` 管理资源的初始化和清理逻辑。 你通过在浏览器中直接运行的动手代码来练习 FastAPI Backend Development Bootcamp,全天候 AI 导师会在你学习这节课的过程中回答你的问题。
学习 FastAPI Backend Development Bootcamp 需要有经验吗?
无需任何先前经验。CoddyKit 上的 FastAPI Backend Development Bootcamp 课程适合初学者到高级学习者,你可以从这里开始或从头开始,按照自己的节奏学习。 这是第 3 节课,共 4 节。
「基于类的依赖与 Yield 依赖」课时需要多长时间?
大多数 CoddyKit 课程大约需要 5–10 分钟。每节课都很精短且互动,所以你能稳步进步,并在网页和应用中从离开的地方继续。
我能在这节 FastAPI Backend Development Bootcamp 课中编写并运行代码吗?
能。每节 FastAPI Backend Development Bootcamp 课都包含内置代码编辑器,你可以在浏览器中直接编写并运行真实代码,并获得即时 AI 反馈 — 无需本地设置。
此课程中的所有课时
- 理解 FastAPI 中的依赖
- 注入常用依赖
- 基于类的依赖与 Yield 依赖
- 全局依赖与子依赖