...but continue reading below to see how to overcome that.

## Return Type and Data Filtering

Let's continue from the previous example. We wanted to **annotate the function with one type**, but we wanted to be able to return from the function something that actually includes **more data**.

* 100% کد بر اساس <abbr title="حاشیه نویسی تایپ های پایتون (Python type annotations)، با استفاده از آن ویرایشگر و ابزارهای خارجی شما می توانند پشتیبانی بهتری از شما ارائه دهند">type annotate ها</abbr>.

* استفاده شده در اپلیکیشن های تولید

## ویژگی های Starlette

@app.get("/items/{item_id}")
def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### 📁

🔜 🎏 🏗 📁 ✍ 📁 `Dockerfile` ⏮️:

```{ .dockerfile .annotate }
# (1)
FROM python:3.9

# (2)
WORKDIR /code

# (3)
COPY ./requirements.txt /code/requirements.txt

# (4)
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (5)

    scheme: slate
    primary: teal
    accent: amber
    toggle:
      icon: material/lightbulb-outline
      name: Switch to system preference
  features:
  - content.code.annotate
  - content.code.copy
  # - content.code.select
  - content.footnote.tooltips
  - content.tabs.link
  - content.tooltips
  - navigation.footer
  - navigation.indexes
  - navigation.instant

For Kubernetes v1.5 & v1.6, you must also turn on NetworkPolicy by setting
the DefaultDeny namespace annotation. Note: this will enforce policy for *all* pods in the namespace:

```
kubectl annotate namespace default "net.beta.kubernetes.io/network-policy={\"ingress\":{\"isolation\":\"DefaultDeny\"}}"
```

When using `Cilium` as a CNI in your cluster, please edit the `flavor` field to `cilium`.

    return {"item_id": item_id, "q": q}
```

### Dockerfile

Erstellen Sie nun im selben Projektverzeichnis eine Datei `Dockerfile` mit:

```{ .dockerfile .annotate }
# (1)
FROM python:3.9

# (2)
WORKDIR /code

# (3)
COPY ./requirements.txt /code/requirements.txt

# (4)
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (5)

def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile

Now in the same project directory create a file `Dockerfile` with:

```{ .dockerfile .annotate }
# (1)!
FROM python:3.9

# (2)!
WORKDIR /code

# (3)!
COPY ./requirements.txt /code/requirements.txt

# (4)!
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

def read_item(item_id: int, q: Union[str, None] = None):
    return {"item_id": item_id, "q": q}
```

### Dockerfile

Agora, no mesmo diretório do projeto, crie um arquivo `Dockerfile` com:

```{ .dockerfile .annotate }
# (1)
FROM python:3.9

# (2)
WORKDIR /code

# (3)
COPY ./requirements.txt /code/requirements.txt

# (4)
RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt

# (5)

Das umfasst viele Bibliotheken zur Interaktion mit Cloud-Speicher, Videoverarbeitung und anderen.

```{ .python .annotate hl_lines="2  10-12  14" }
{!../../docs_src/custom_response/tutorial008.py!}
```

1. Das ist die Generatorfunktion. Es handelt sich um eine „Generatorfunktion“, da sie `yield`-Anweisungen enthält.

This includes many libraries to interact with cloud storage, video processing, and others.

```{ .python .annotate hl_lines="2  10-12  14" }
{!../../docs_src/custom_response/tutorial008.py!}
```

1. This is the generator function. It's a "generator function" because it contains `yield` statements inside.