---

## **Typer**, la FastAPI delle CLI

<a href="https://typer.tiangolo.com" target="_blank"><img src="https://typer.tiangolo.com/img/logo-margin/logo-margin-vector.svg" style="width: 20%;"></a>

/// info

If you are using containers, for example with Docker or Kubernetes, I'll tell you more about that in the next chapter: [FastAPI in Containers - Docker](docker.md){.internal-link target=_blank}.

In particular, when running on **Kubernetes** you will probably **not** want to use workers and instead run **a single Uvicorn process per container**, but I'll tell you about it later in that chapter.

///

## Multiple Workers { #multiple-workers }

## In a hurry? { #in-a-hurry }

<abbr title="too long; didn't read"><strong>TL;DR:</strong></abbr>

If you are using third party libraries that tell you to call them with `await`, like:

```Python
results = await some_library()
```

Then, declare your *path operation functions* with `async def` like:

```Python hl_lines="2"
@app.get('/')

		// If version is a deleted marker, set this header as well
		if objInfo.DeleteMarker && del { // only returned during delete object
			w.Header()[xhttp.AmzDeleteMarker] = []string{strconv.FormatBool(objInfo.DeleteMarker)}
		}
	}

	if objInfo.Bucket != "" && objInfo.Name != "" {
		if lc, err := globalLifecycleSys.Get(objInfo.Bucket); err == nil && !del {
			lc.SetPredictionHeaders(w, objInfo.ToLifecycleOpts())
		}
	}

In many frameworks and systems just handling security and authentication takes a big amount of effort and code (in many cases it can be 50% or more of all the code written).

**FastAPI** provides several tools to help you deal with **Security** easily, rapidly, in a standard way, without having to study and learn all the security specifications.

But first, let's check some small concepts.

## In a hurry? { #in-a-hurry }

Ese "esperar otra cosa" normalmente se refiere a las operaciones de <abbr title="Input and Output">I/O</abbr> que son relativamente "lentas" (comparadas con la velocidad del procesador y la memoria RAM), como esperar:

* que los datos del cliente se envíen a través de la red
* que los datos enviados por tu programa sean recibidos por el cliente a través de la red

# Note that numpy 2.1.0 does not support python 3.9
numpy >= 2.0.0, < 2.2.0
wheel ~= 0.41.2
h5py >= 3.11.0
lit ~= 17.0.2
opt_einsum == 3.3.0
astunparse == 1.6.3
dill == 0.3.7
astor == 0.7.1
typing_extensions ~= 4.14.1
gast == 0.4.0
termcolor == 2.3.0
wrapt == 1.16.0
tblib == 2.0.0
ml_dtypes >= 0.5.1, < 0.6.0
auditwheel >= 6.1.0
# Install tensorboard, and keras

* 100% test coverage: cobertura de tests del 100%
* back and forth: de un lado a otro
* I/O (as in "input and output"): I/O (do not translate to "E/S")
* Machine Learning: Machine Learning (do not translate to "Aprendizaje Automático")
* Deep Learning: Deep Learning (do not translate to "Aprendizaje Profundo")
* callback hell: callback hell (do not translate to "infierno de callbacks")

## Why is MinIO cloud-native?

If you want to secure your API, there are several better things you can do, for example:

* Make sure you have well defined Pydantic models for your request bodies and responses.
* Configure any required permissions and roles using dependencies.
* Never store plaintext passwords, only password hashes.
* Implement and use well-known cryptographic tools, like Passlib and JWT tokens, etc.