Dann verwenden wir den Request direkt und extrahieren den Body als `bytes`. Das bedeutet, dass FastAPI nicht einmal versucht, die Request-Payload als JSON zu parsen.

        committer: TensorFlow Release Automation <******@****.***>
        token: ${{ secrets.JENKINS_TOKEN }}
        reviewers: mihaimaruseac,learning-to-play,nitins17
        body: |
          This PR was created by a GitHub Actions workflow to update all the SIG Build-based RBE containers to the most recent containers. See:

             * array. Incedentally when these andx smbs are created they are not
             * necessarily populated with header data because they're not writing
             * the header, only their body. But for whatever reason one might wish
             * to populate fields if the writeXxx operation needs this header data
             * for whatever reason. I copy over the uid here so it appears correct

      if (this.launch != CommandLine) {
        println(request.url)
      }

      client
        .newCall(request)
        .execute()
        .use {
          val firstLine =
            it.body
              .string()
              .lines()
              .first()
          if (this.launch != CommandLine) {
            println("${it.code} ${it.request.url.host} $firstLine")
          }
          Unit

Then you just do the same in your tests.

E.g.:

* To pass a *path* or *query* parameter, add it to the URL itself.
* To pass a JSON body, pass a Python object (e.g. a `dict`) to the parameter `json`.
* If you need to send *Form Data* instead of JSON, use the `data` parameter instead.
* To pass *headers*, use a `dict` in the `headers` parameter.

### Parâmetros do Pydantic v1 { #pydantic-v1-parameters }

Se você precisar usar algumas das ferramentas específicas do FastAPI para parâmetros como `Body`, `Query`, `Form` etc. com modelos do Pydantic v1, pode importá-las de `fastapi.temp_pydantic_v1_params` enquanto conclui a migração para o Pydantic v2:

{* ../../docs_src/pydantic_v1_in_v2/tutorial004_an_py310.py hl[4,18] *}

    logging.info("Pushing branch")
    subprocess.run(["git", "push", "origin", branch_name], check=True)
    logging.info("Creating PR")
    pr = repo.create_pull(title=message, body=message, base="master", head=branch_name)
    logging.info(f"Created PR: {pr.number}")
    logging.info("Finished")


if __name__ == "__main__":

	lockServers = make([]*lockServer, numberOfNodes)
)

func getLockArgs(r *http.Request) (args LockArgs, err error) {
	buf, err := io.ReadAll(r.Body)
	if err != nil {
		return args, err
	}
	_, err = args.UnmarshalMsg(buf)
	return args, err
}

type lockServerHandler struct {
	lsrv *lockServer
}

<img src="/img/tutorial/generate-clients/image08.png">

## Benefits { #benefits }

When using the automatically generated clients, you would get **autocompletion** for:

* Methods.
* Request payloads in the body, query parameters, etc.
* Response payloads.

You would also have **inline errors** for everything.

		Timeout:   10 * time.Second,
	}

	resp, err := client.Do(req)
	if err != nil {
		ki.Error = err.Error()
		return ki
	}
	defer resp.Body.Close()
	decoder := json.NewDecoder(resp.Body)
	if err := decoder.Decode(&ki); err != nil {
		ki.Error = err.Error()
	}
	return ki
}