)
def test_post(path):
    data = {"a": 2, "b": "foo"}
    response = client.post(path, json=data)
    assert response.status_code == 200, response.text
    assert data == response.json()


@pytest.mark.parametrize(
    "path", ["/a/compute", "/a/compute/", "/b/compute", "/b/compute/"]
)
def test_post_invalid(path):
    data = {"a": "bar", "b": "foo"}
    response = client.post(path, json=data)

`UploadFile` tiene los siguientes métodos `async`. Todos ellos llaman a los métodos correspondientes del archivo por debajo (usando el `SpooledTemporaryFile` interno).

* `write(data)`: Escribe `data` (`str` o `bytes`) en el archivo.
* `read(size)`: Lee `size` (`int`) bytes/caracteres del archivo.
* `seek(offset)`: Va a la posición de bytes `offset` (`int`) en el archivo.

        .withFeatures(
            ListFeature.GENERAL_PURPOSE, CollectionFeature.ALLOWS_NULL_VALUES, CollectionSize.ANY)
        .createTestSuite();
  }

  public void testConsumingIterator() {
    // Test data
    List<String> list = Lists.newArrayList("a", "b");

    // Test & Verify
    Iterator<String> consumingIterator = Iterators.consumingIterator(list.iterator());

  TFE_ContextUpdateServerDef(ctx, 0, serialized_update.data(),
                             serialized_update.size(), status);
  EXPECT_NE(TF_OK, TF_GetCode(status)) << TF_Message(status);

  // Even after the prevoiusly failed cluster update, another update and op
  // execution should work fine as long as the provided server_def is valid.
  TFE_ContextUpdateServerDef(ctx, 0, serialized.data(), serialized.size(),

app = FastAPI()


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


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

        WithJsonSchema,
    )

    class FakeNumpyArray:
        def __init__(self):
            self.data = [1.0, 2.0, 3.0]

    FakeNumpyArrayPydantic = Annotated[
        FakeNumpyArray,
        WithJsonSchema(TypeAdapter(list[float]).json_schema()),
        PlainSerializer(lambda v: v.data),
    ]

    class MyModel(BaseModel):
        model_config = ConfigDict(arbitrary_types_allowed=True)

### Bug or Regression

* Add --no-negcache flag to kube-dns to prevent caching of NXDOMAIN responses. ([#66036](https://github.com/kubernetes/kubernetes/pull/66036), [@prameshj](https://github.com/prameshj))
* fix data loss issue if using existing azure disk with partitions in disk mount  ([#63270](https://github.com/kubernetes/kubernetes/pull/63270), [@andyzhangx](https://github.com/andyzhangx))

# List zip contents
response = s3.list_objects_v2(Bucket="your-bucket", Prefix="path/to/file.zip/")
print(response)

# Download data.csv stored in the zip file

errors.crud_failed_to_create_instance = Gagal membuat data baru.
errors.crud_failed_to_create_crud_table = Gagal membuat data baru. ({0})
errors.crud_failed_to_update_crud_table=Gagal memperbarui data. ({0})
errors.crud_failed_to_delete_crud_table=Gagal menghapus data. ({0})
errors.crud_could_not_find_crud_table = Data {0} tidak ditemukan.
errors.could_not_find_backup_index=Tidak dapat menemukan indeks backup.