multipart_not_installed_error,
)


def test_incorrect_multipart_installed_form(monkeypatch):
    monkeypatch.setattr("python_multipart.__version__", "0.0.12")
    with warnings.catch_warnings(record=True):
        warnings.simplefilter("always")
        monkeypatch.delattr("multipart.multipart.parse_options_header", raising=False)
    with pytest.raises(RuntimeError, match=multipart_incorrect_install_error):

  private val noContextTakeover: Boolean,
) : Closeable {
  private val deflatedBytes = Buffer()

  private val deflater =
    Deflater(
      Deflater.DEFAULT_COMPRESSION,
      // nowrap (omits zlib header):
      true,
    )

  private val deflaterSink = DeflaterSink(deflatedBytes, deflater)

  /** Deflates [buffer] in place as described in RFC 7692 section 7.2.1. */
  @Throws(IOException::class)

  }

  @Test fun `deflate golden value`() {
    val deflater = MessageDeflater(false)
    val deflated = deflater.deflate("Hello deflate!".encodeUtf8())
    assertThat(deflated.hex()).isEqualTo("f248cdc9c95748494dcb492c49550400")
  }

  @Test fun `inflate deflate`() {
    val deflater = MessageDeflater(false)
    val inflater = MessageInflater(false)

                    # For Pydantic v1
                    and getattr(field, "shape", 1) == 1
                )
            )

    return ParamDetails(type_annotation=type_annotation, depends=depends, field=field)


def add_param_to_fields(*, field: ModelField, dependant: Dependant) -> None:
    field_info = field.field_info
    field_info_in = getattr(field_info, "in_", None)
    if field_info_in == params.ParamTypes.path:

  }
  return valid;
}
}  // namespace

void TFE_CallDLManagedTensorDeleter(void* dlm_ptr) {
  DLManagedTensor* dlMTensor = static_cast<DLManagedTensor*>(dlm_ptr);
  if (dlMTensor->deleter != nullptr) {
    dlMTensor->deleter(dlMTensor);
  }
}

void* TFE_HandleToDLPack(TFE_TensorHandle* h, TF_Status* status) {
  auto tf_dlm_context = GetDlContext(h, status);
  if (!status->status.ok()) {
    return nullptr;

_initializers = _KerasLazyLoader(
    globals(), submodule="initializers", name="initializers")
setattr(_current_module, "losses", _losses)
setattr(_current_module, "metrics", _metrics)
setattr(_current_module, "optimizers", _optimizers)
setattr(_current_module, "initializers", _initializers)


# Do an eager load for Keras' code so that any function/method that needs to

import types
from enum import Enum
from typing import Any, Callable, Dict, Set, Type, TypeVar, Union

from pydantic import BaseModel

DecoratedCallable = TypeVar("DecoratedCallable", bound=Callable[..., Any])
UnionType = getattr(types, "UnionType", Union)
ModelNameMap = Dict[Union[Type[BaseModel], Type[Enum]], str]

            openapi_examples = getattr(field_info, "openapi_examples", None)
            example = getattr(field_info, "example", None)
            if openapi_examples:
                parameter["examples"] = jsonable_encoder(openapi_examples)
            elif example != Undefined:
                parameter["example"] = jsonable_encoder(example)
            if getattr(field_info, "deprecated", None):

    }

    public void setId(final String id) {
        this.id = id;
    }

    public void setCss(final String css) {
        this.css = css;
    }

    public void setAttr(final String name, final String value) {
        attrName = name;
        attrValue = value;
    }

    @Override
    public String toString() {

### Ler um Único Hero

Podemos **ler** um único `Hero`.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[58:63] hl[60] *}

### Deletar um Hero

Também podemos **deletar** um `Hero`.

{* ../../docs_src/sql_databases/tutorial001_an_py310.py ln[66:73] hl[71] *}

### Executar o App

Você pode executar o app:

<div class="termy">

```console