## Webhooks steps { #webhooks-steps }

The process normally is that **you define** in your code what is the message that you will send, the **body of the request**.

You also define in some way at which **moments** your app will send those requests or events.

And **your users** define in some way (for example in a web dashboard somewhere) the **URL** where your app should send those requests.

## `async` and `await` { #async-and-await }

Modern versions of Python have a very intuitive way to define asynchronous code. This makes it look just like normal "sequential" code and do the "awaiting" for you at the right moments.

When there is an operation that will require waiting before giving the results and has support for these new Python features, you can code it like:

```Python
burgers = await get_burgers(2)
```

Comme il est très simple, son apprentissage est relativement intuitif, bien que la documentation soit quelque peu
technique par moments.

```
mc cp ~/images.jpg myminio/images
.../images.jpg:  8.31 KB / 8.31 KB ┃▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓┃ 100.00% 59.42 KB/s 0s
```

Wait a few moments, then check the bucket’s contents with mc ls — you will see a thumbnail appear.

```
mc ls myminio/images-thumbnail
[2017-02-08 11:39:40 IST]   992B images-thumbnail.jpg
```

s.SSSZ")},yt.inspect=function(){if(!this.isValid())return"moment.invalid(/* "+this._i+" */)";var e,a,t,s="moment",n="";return this.isLocal()||(s=0===this.utcOffset()?"moment.utc":"moment.parseZone",n="Z"),e="["+s+'("]',a=0<=this.year()&&this.year()<=9999?"YYYY":"YYYYYY",t=n+'[")]',this.format(e+a+"-MM-DD[T]HH:mm:ss.SSS"+t)},"undefined"!=typeof Symbol&&null!=Symbol.for&&(yt[Symbol.for("nodejs.util.inspect.custom")]=function(){return"Moment<"+this.format()+">"}),yt.toJSON=function(){return this.is...

        mean, var = tf.nn.moments(self.kernel, axes=[0, 1, 2], keepdims=True)
        return self.convolution_op(inputs, (self.kernel - mean) / tf.sqrt(var +
        1e-10))` Alternatively, you can override `convolution_op`: `python class
        StandardizedConv2D(tf.keras.Layer): def convolution_op(self, inputs,
        kernel): mean, var = tf.nn.moments(kernel, axes=[0, 1, 2],

```

### Mais detalhes técnicos { #more-technical-details }

Você deve ter observado que `await` pode ser usado somente dentro de funções definidas com `async def`.

Mas ao mesmo tempo, funções definidas com `async def` têm que ser "aguardadas". Então, funções com `async def` podem ser chamadas somente dentro de funções definidas com `async def` também.

Então, sobre o ovo e a galinha, como você chama a primeira função async?

J'ai évité la création d'un nouveau framework pendant plusieurs années. J'ai d'abord essayé de résoudre toutes les fonctionnalités couvertes par **FastAPI** en utilisant de nombreux frameworks, plug-ins et outils différents.

Debido a que este código se ejecuta antes de que la aplicación **comience** a tomar requests, y justo después de que **termine** de manejarlos, cubre todo el **lifespan** de la aplicación (la palabra "lifespan" será importante en un momento 😉).

* **`async` y `await`**
* **Coroutines**

## Código Asíncrono { #asynchronous-code }

El código asíncrono simplemente significa que el lenguaje 💬 tiene una forma de decirle a la computadora / programa 🤖 que en algún momento del código, tendrá que esperar que *otra cosa* termine en otro lugar. Digamos que esa *otra cosa* se llama "archivo-lento" 📝.