<div class="termy">

```console
$ pip install -r requirements.txt
---> 100%
Successfully installed fastapi pydantic uvicorn
```

</div>

/// info

Há outros formatos e ferramentas para definir e instalar dependências de pacote.

Eu vou mostrar um exemplo depois usando Poetry em uma seção abaixo. 👇

///

### Criando o Código do **FastAPI**

}

// ParamKind is a tuple of Group Kind and Version.
// +structType=atomic
message ParamKind {
  // APIVersion is the API group version the resources belong to.
  // In format of "group/version".
  // Required.
  optional string apiVersion = 1;

  // Kind is the API kind the resources belong to.
  // Required.
  optional string kind = 2;
}

APISpec tem plug-ins para muitos frameworks (e tem um plug-in para Starlette também).

O jeito como ele funciona é que você escreve a definição do _schema_ usando formato YAML dentro da _docstring_ de cada função controlando uma rota.

E ele gera _schemas_ OpenAPI.

É assim como funciona no Flask, Starlette, Responder etc.

<div class="termy">

```console
$ pip install -r requirements.txt
---> 100%
Successfully installed fastapi pydantic uvicorn
```

</div>

/// info

Es gibt andere Formate und Tools zum Definieren und Installieren von Paketabhängigkeiten.

Ich zeige Ihnen später in einem Abschnitt unten ein Beispiel unter Verwendung von Poetry. 👇

///

### Den **FastAPI**-Code erstellen

Es ist ein Plugin für viele Frameworks (und es gibt auch ein Plugin für Starlette).

Die Funktionsweise besteht darin, dass Sie die Definition des Schemas im YAML-Format im Docstring jeder Funktion schreiben, die eine Route verarbeitet.

Und es generiert OpenAPI-Schemas.

So funktioniert es in Flask, Starlette, Responder, usw.

build:elinux_aarch64 --config=elinux
build:elinux_aarch64 --cpu=aarch64
build:elinux_armhf --config=elinux
build:elinux_armhf --cpu=armhf
build:elinux_armhf --copt -mfp16-format=ieee

# Config-specific options should come above this line.

# Load rc file written by ./configure.
try-import %workspace%/.tf_configure.bazelrc
try-import %workspace%/xla_configure.bazelrc

						fmt.Println("ERROR:", err)
					}
				}
			}
		}

		return nil
	}
	err := app.Run(os.Args)
	if err != nil {
		log.Fatal(err)
	}
}

var (
	// XL header specifies the format
	xlHeader = [4]byte{'X', 'L', '2', ' '}

	// Current version being written.
	xlVersionCurrent [4]byte
)

const (
	// Breaking changes.
	// Newer versions cannot be read by older software.

<div class="termy">

```console
$ pip install -r requirements.txt
---> 100%
Successfully installed fastapi pydantic
```

</div>

/// info

There are other formats and tools to define and install package dependencies.

///

### Create the **FastAPI** Code

* Create an `app` directory and enter it.
* Create an empty file `__init__.py`.
* Create a `main.py` file with:

#include "tensorflow/c/eager/c_api.h"

#include <string.h>

#include <memory>
#include <string>

// clang-format off
#include "tensorflow/core/framework/attr_value.pb.h"
#include "tensorflow/core/framework/types.pb.h"
#include "tensorflow/core/platform/platform.h"
// clang-format on

#include "absl/strings/match.h"
#include "tensorflow/c/eager/c_api_experimental.h"
#include "tensorflow/c/eager/c_api_internal.h"

	state srState

	iamMetaCache srIAMCache
}

type srState srStateV1

// srStateV1 represents version 1 of the site replication state persistence
// format.
type srStateV1 struct {
	Name string `json:"name"`

	// Peers maps peers by their deploymentID
	Peers                   map[string]madmin.PeerInfo `json:"peers"`