# Currently, there is no way to pass multiple cookies with the same name.
# The only way to pass multiple values for cookie params is to serialize them using

			if err != nil {
				err = msgp.WrapError(err)
				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z *LockArgs) Msgsize() (s int) {
	s = 1 + 4 + msgp.StringPrefixSize + len(z.UID) + 10 + msgp.ArrayHeaderSize
	for za0001 := range z.Resources {
		s += msgp.StringPrefixSize + len(z.Resources[za0001])
	}

def get_explicit() -> Item:
    return Item(name="widget", price=9.99)


client = TestClient(app)


def test_default_response_class_skips_json_dumps():
    """When no response_class is set, the fast path serializes directly to
    JSON bytes via Pydantic's dump_json and never calls json.dumps."""
    with patch(
        "starlette.responses.json.dumps", wraps=__import__("json").dumps
    ) as mock_dumps:

Si vous déclarez un [Modèle de réponse](../tutorial/response-model.md), FastAPI l'utilise pour sérialiser les données en JSON, en utilisant Pydantic.

Si vous ne déclarez pas de modèle de réponse, FastAPI utilise le `jsonable_encoder` expliqué dans [Encodeur compatible JSON](../tutorial/encoder.md) et le place dans une `JSONResponse`.

// Tensorflow's CPU implementation through constant folding.
TF_CAPI_EXPORT unsigned char TF_GetXlaConstantFoldingDisabled();
TF_CAPI_EXPORT void TF_SetXlaConstantFoldingDisabled(
    unsigned char should_enable);

// Create a serialized tensorflow.ConfigProto proto, where:
//
// a) ConfigProto.optimizer_options.global_jit_level is set to ON_1 if
// `enable_xla_compilation` is non-zero, and OFF otherwise.

import org.jspecify.annotations.NullMarked;

/**
 * Methods factored out so that they can be emulated differently in GWT.
 *
 * @author Chris Povirk
 */
@GwtCompatible
@NullMarked
final class Platform {
  /** Serializes and deserializes the specified object. */
  @SuppressWarnings("unchecked")
  static <T> T reserialize(T object) {
    checkNotNull(object);
    ByteArrayOutputStream bytes = new ByteArrayOutputStream();
    try {

import org.jspecify.annotations.NullMarked;

/**
 * Methods factored out so that they can be emulated differently in GWT.
 *
 * @author Chris Povirk
 */
@GwtCompatible
@NullMarked
final class Platform {
  /** Serializes and deserializes the specified object. */
  @SuppressWarnings("unchecked")
  static <T> T reserialize(T object) {
    checkNotNull(object);
    ByteArrayOutputStream bytes = new ByteArrayOutputStream();
    try {

		if err != nil {
			err = msgp.WrapError(err)
			return
		}
		(*z) = BackendType(zb0001)
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z BackendType) Msgsize() (s int) {
	s = msgp.IntSize
	return
}

// MarshalMsg implements msgp.Marshaler
func (z *BucketInfo) MarshalMsg(b []byte) (o []byte, err error) {

			if err != nil {
				err = msgp.WrapError(err)
				return
			}
		}
	}
	o = bts
	return
}

// Msgsize returns an upper bound estimate of the number of bytes occupied by the serialized message
func (z *BucketReplicationStat) Msgsize() (s int) {

#include "tensorflow/core/platform/refcount.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {

class FunctionRecord;

// A traced function: this hides the complexity of converting the serialized
// representation between various supported formats e.g. FunctionDef and Mlir
// function.
class AbstractFunction : public core::RefCounted {
 protected:
  enum AbstractFunctionKind { kGraph, kMlir };