# `APIRouter` class

Here's the reference information for the `APIRouter` class, with all its parameters, attributes and methods.

You can import the `APIRouter` class directly from `fastapi`:

```python
from fastapi import APIRouter
```

::: fastapi.APIRouter
    options:
        members:
            - websocket
            - include_router
            - get
            - put
            - post
            - delete

You can import it directly from `fastapi`:

```python
from fastapi import BackgroundTasks
```

* оголосити параметр шляху `item_id`, використовуючи `Path`
* розмістити їх у різному порядку
* не використовувати `Annotated`

...у Python є спеціальний синтаксис для цього.

Передайте `*` як перший параметр функції.

You can import it from `fastapi.requests`:

```python
from fastapi.requests import HTTPConnection
```

```

### Step 3: Test on RabbitMQ

The python program below waits on the queue exchange `bucketevents` and prints event notifications on the console. We use [Pika Python Client](https://www.rabbitmq.com/tutorials/tutorial-three-python.html) library to do this.

```py
#!/usr/bin/env python
import pika

connection = pika.BlockingConnection(pika.ConnectionParameters(

    * Mit <a href="https://tartiflette.github.io/tartiflette-asgi/" class="external-link" target="_blank">Tartiflette ASGI</a> für ASGI-Integration
* <a href="https://graphene-python.org/" class="external-link" target="_blank">Graphene</a>
    * Mit <a href="https://github.com/ciscorn/starlette-graphene3" class="external-link" target="_blank">starlette-graphene3</a>

Read more about it in the [FastAPI docs for Static Files](https://fastapi.tiangolo.com/tutorial/static-files/).

You can import it directly from `fastapi.staticfiles`:

```python
from fastapi.staticfiles import StaticFiles
```

WIP ML Build Docker container for ML repositories (Tensorflow, JAX and XLA).

This container branches off from
/tensorflow/tools/tf_sig_build_dockerfiles/. However, since
hermetic CUDA and hermetic Python is now available for Tensorflow, a lot of the
requirements installed on the original container can be removed to reduce the
footprint of the container and make it more reusable across different ML

* declarar el parámetro de path `item_id` usando `Path`
* tenerlos en un orden diferente
* no usar `Annotated`

...Python tiene una sintaxis especial para eso.

Pasa `*`, como el primer parámetro de la función.

* den Pfad-Parameter `item_id` mit `Path` deklarieren
* sie in einer anderen Reihenfolge haben
* nicht `Annotated` verwenden

... möchten, dann hat Python eine kleine Spezial-Syntax dafür.

Übergeben Sie `*`, als den ersten Parameter der Funktion.