return h
}

// NewResponse creates a new response.
// Handlers can use this to create a reusable response.
// The response may be reused, so caller should clear any fields.
func (h *SingleHandler[Req, Resp]) NewResponse() Resp {
	return h.newResp()
}

// NewRequest creates a new request.
// Handlers can use this to create a reusable request.
// The request may be reused, so caller should clear any fields.

Pero es la forma más sencilla de enfocarse en el lado del servidor de WebSockets y tener un ejemplo funcional:

{* ../../docs_src/websockets/tutorial001_py39.py hl[2,6:38,41:43] *}

## Crear un `websocket` { #create-a-websocket }

En tu aplicación de **FastAPI**, crea un `websocket`:

{* ../../docs_src/websockets/tutorial001_py39.py hl[1,46:47] *}

/// note | Detalles Técnicos

      TFE_Op* op,
      const std::vector<absl::optional<std::vector<int64_t>>>& input_shapes_vec,
      const std::vector<TF_Tensor*>& input_tensors,
      const absl::optional<std::vector<int64_t>>& expected_shape) {
    // Create input_shapes.
    TF_ShapeAndTypeList* input_shapes =
        TF_NewShapeAndTypeList(input_shapes_vec.size());
    for (size_t i = 0; i < input_shapes_vec.size(); ++i) {
      const auto& input_shape = input_shapes_vec[i];

	// Empirically (at least on the Windows Server 2013 builder),
	// the kernel is arbitrarily okay with < 248 bytes. That
	// matches what the docs above say:
	// "When using an API to create a directory, the specified
	// path cannot be so long that you cannot append an 8.3 file
	// name (that is, the directory name cannot exceed MAX_PATH
	// minus 12)." Since MAX_PATH is 260, 260 - 12 = 248.
	//

///

## Importar `BaseModel` de Pydantic { #import-pydantics-basemodel }

Primero, necesitas importar `BaseModel` de `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Crea tu modelo de datos { #create-your-data-model }

Luego, declaras tu modelo de datos como una clase que hereda de `BaseModel`.

Usa tipos estándar de Python para todos los atributos:

{* ../../docs_src/body/tutorial001_py310.py hl[5:9] *}

                lang = label[5:]
                lang_to_discussion_map[lang] = discussion
    logging.debug(f"Using translations map: {lang_to_discussion_map}")

    # Messages to create or check
    new_translation_message = f"Good news everyone! 😉 There's a new translation PR to be reviewed: #{pr.number} by @{pr.user.login}. 🎉 This requires 2 approvals from native speakers to be merged. 🤓"

//     affects read from source, block, file, dedup, and object storage backup targets for a specific Veeam Job. When customers
//     create a new backup job and select the object storage or a SOBR as a backup target with this setting, the job default
//     setting will be set to this value. This setting will be only applied to newly created jobs (manual changes with Active Full

//     batch: 100 # upto this many objects per archive
//     inmemory: true # indicates if the archive must be staged locally or in-memory
//     compress: true # S2/Snappy compressed archive
//     smallerThan: 5MiB # create archive for all objects smaller than 5MiB
//     skipErrs: false # skips any source side read() errors

// BatchJobSnowball describes the snowball feature when replicating objects from a local source to a remote target

      --with-gcc-major-version-only \
      --with-linker-hash-style="gnu" \
      --with-tune="generic" \
      && \
    make -j 42 && \
    make install


# Create the devtoolset libstdc++ linkerscript that links dynamically against
# the system libstdc++ 4.4 and provides all other symbols statically.
case "${VERSION}" in
devtoolset-7)

{* ../../docs_src/websockets/tutorial001_py39.py hl[2,6:38,41:43] *}

## Einen `websocket` erstellen { #create-a-websocket }

Erstellen Sie in Ihrer **FastAPI**-Anwendung einen `websocket`:

{* ../../docs_src/websockets/tutorial001_py39.py hl[1,46:47] *}

/// note | Technische Details