A. Unique TensorFlower <******@****.***> 1705975132 -0800

## 🖼 📁 📊

➡️ 💬 👆 ✔️ 📁 📊 💖 👉:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
│   ├── dependencies.py
│   └── routers
│   │   ├── __init__.py
│   │   ├── items.py
│   │   └── users.py
│   └── internal
│       ├── __init__.py
│       └── admin.py
```

!!! tip
    📤 📚 `__init__.py` 📁: 1️⃣ 🔠 📁 ⚖️ 📁.

    👉 ⚫️❔ ✔ 🏭 📟 ⚪️➡️ 1️⃣ 📁 🔘 ➕1️⃣.

db_state = ContextVar("db_state", default=db_state_default.copy())


class PeeweeConnectionState(peewee._ConnectionState):
    def __init__(self, **kwargs):
        super().__setattr__("_state", db_state)
        super().__init__(**kwargs)

    def __setattr__(self, name, value):
        self._state.get()[name] = value

    def __getattr__(self, name):
        return self._state.get()[name]

class Child(tf.Module):

  def __init__(self):
    super(Child, self).__init__()
    self.my_variable = tf.Variable(3.)


# Creates a dag object graph.
# There is only one instance of `Child`, but it is reachable via two names.
# Thus, self.my_variable is reachable via two paths.
class TestModule(tf.Module):

  def __init__(self):
    super(TestModule, self).__init__()
    self.child1 = Child()

class Person:
    def __init__(self, name: str):
        self.name = name


def get_person_name(one_person: Person):

# it is being invoked.
# CHECK: module
# CHECK-SAME: tf.versions
# CHECK-SAME: bad_consumers
# CHECK-SAME: min_consumer
# CHECK-SAME: producer


class TestModule(tf.Module):

  def __init__(self):
    super(TestModule, self).__init__()
    self.v42 = tf.Variable(42.0)
    self.c43 = tf.constant(43.0)

  # During serialization, the constants are given internal (non-user-accessible, non-semantically-load-bearing) exported names.

Let's say you have a file structure like this:

```
.
├── app
│   ├── __init__.py
│   ├── main.py
│   ├── dependencies.py
│   └── routers
│   │   ├── __init__.py
│   │   ├── items.py
│   │   └── users.py
│   └── internal
│       ├── __init__.py
│       └── admin.py
```

!!! tip
    There are several `__init__.py` files: one in each directory or subdirectory.

from fastapi import Depends, FastAPI

app = FastAPI()


class FixedContentQueryChecker:
    def __init__(self, fixed_content: str):
        self.fixed_content = fixed_content

    def __call__(self, q: str = ""):
        if q:
            return self.fixed_content in q
        return False


checker = FixedContentQueryChecker("bar")


@app.get("/query-checker/")

A. Unique TensorFlower <******@****.***> 1705975132 -0800

{!../../../docs_src/dependencies/tutorial011.py!}
```

本例中，**FastAPI**  使用 `__call__` 检查附加参数及子依赖项，稍后，还要调用它向*路径操作函数*传递值。

## 参数化实例

接下来，使用 `__init__` 声明用于**参数化**依赖项的实例参数：

```Python hl_lines="7"
{!../../../docs_src/dependencies/tutorial011.py!}
```

本例中，**FastAPI** 不使用 `__init__`，我们要直接在代码中使用。

## 创建实例

使用以下代码创建类实例：

```Python hl_lines="16"
{!../../../docs_src/dependencies/tutorial011.py!}
```