t.Fatalf("Expected GetObject reading data to succeed, but failed with %v", err)
	}
	gr.Close()

	const expectedHash = "fffb6377948ebea75ad2b8058e849ef5"
	foundHash := fmt.Sprintf("%x", h.Sum(nil))
	if foundHash != expectedHash {
		t.Fatalf("Expected data to have md5sum = `%s`, found `%s`", expectedHash, foundHash)
	}
}

// Test reading an object with some outdated data in some disks

`UploadFile` tem os seguintes métodos `async`. Todos eles chamam os métodos de arquivos por baixo dos panos (usando o objeto `SpooledTemporaryFile` interno).

* `write(data)`: escreve dados (`data`) em `str` ou `bytes` no arquivo.
* `read(size)`: Lê um número de bytes/caracteres de acordo com a quantidade `size` (`int`).
* `seek(offset)`: Navega para o byte na posição `offset` (`int`) do arquivo.

			}

			if !bytes.Equal(data, testCase.data) {
				t.Fatalf("case %v: expected %v, got %v", i+1, testCase.data, data)
			}
		}
	}
}

func testStorageAPIDeleteFile(t *testing.T, storage StorageAPI) {
	err := storage.AppendFile(context.Background(), "foo", "myobject", []byte("foo"))
	if err != nil {
		t.Fatalf("unexpected error %v", err)
	}

	testCases := []struct {
		volumeName string

        //custom options from user
        if (typeof options !== 'object' || options === null)
            options = {};

        //allow setting options with data attributes
        //data-api options will be overwritten with custom javascript options
        options = $.extend(this.element.data(), options);

        //html template for the picker UI
        if (typeof options.template !== 'string' && !(options.template instanceof $))

                                            <c:forEach var="data" varStatus="s"
                                                       items="${elevateWordItems}">
                                                <tr
                                                        data-href="${contextPath}/admin/elevateword/details/4/${f:u(data.id)}">
                                                    <td>${f:h(data.suggestWord)}</td>

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str
    model_config = {"extra": "forbid"}


@app.post("/login/")
async def login(data: FormData = Form()):

from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str


@app.post("/login/")
async def login(data: Annotated[FormData, Form()]):

# General - How To - Recipes

Here are several pointers to other places in the docs, for general or frequent questions.

## Filter Data - Security

To ensure that you don't return more data than you should, read the docs for [Tutorial - Response Model - Return Type](../tutorial/response-model.md){.internal-link target=_blank}.

## Documentation Tags - OpenAPI

    if (!$(e.target).closest("#searchOptions, #searchOptionsButton").length) {
      $("#searchOptions").removeClass("active");
    }
  });

  $("[data-toggle='control-options']").click(function(e) {
    e.preventDefault();
    var target = $(this).attr("data-target") || $(this).attr("href");
    if (target) {
      $(target).toggleClass("active");
    }
  });

  $("#searchOptionsClearButton").on("click", function(e) {

using tensorflow::NodeDef;

static void BoolDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<bool*>(data);
}

static void Int32Deallocator(void* data, size_t, void* arg) {
  delete[] static_cast<int32_t*>(data);
}

static void DoubleDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<double*>(data);
}

static void FloatDeallocator(void* data, size_t, void* arg) {
  delete[] static_cast<float*>(data);