return other, other.isDir() == e.isDir()
	}
	eVers, eErr := e.xlmeta()
	oVers, oErr := other.xlmeta()
	if eErr != nil || oErr != nil {
		return nil, false
	}

	// check both fileInfo's have same number of versions, if not skip
	// the `other` entry.
	if len(eVers.versions) != len(oVers.versions) {
		eTime := eVers.latestModtime()
		oTime := oVers.latestModtime()
		if !eTime.Equal(oTime) {
			if eTime.After(oTime) {

		return nil, errExpectedBool
	}
	return FromBool(!b), nil
}

func (e *ConditionOperand) evalNode(r Record, tableAlias string) (*Value, error) {
	opVal, opErr := e.Operand.evalNode(r, tableAlias)
	if opErr != nil || e.ConditionRHS == nil {
		return opVal, opErr
	}

	// Need to evaluate the ConditionRHS
	switch {
	case e.ConditionRHS.Compare != nil:

            this.maxSpan = options.maxSpan;

        if (typeof options.dateLimit === 'object') //backwards compat
            this.maxSpan = options.dateLimit;

        if (typeof options.opens === 'string')
            this.opens = options.opens;

        if (typeof options.drops === 'string')
            this.drops = options.drops;

        if (typeof options.showWeekNumbers === 'boolean')

bool GetGraphDef(TF_Graph* graph, tensorflow::GraphDef* graph_def);

bool GetNodeDef(TF_Operation* oper, tensorflow::NodeDef* node_def);

bool GetFunctionDef(TF_Function* func, tensorflow::FunctionDef* func_def);

bool GetAttrValue(TF_Operation* oper, const char* attr_name,
                  tensorflow::AttrValue* attr_value, TF_Status* s);

    jvmArgumentProviders.add(CommandLineArgumentProvider {
        //allow ProjectBuilder to inject legacy types into the system classloader
        if (testVersionProvider.get().canCompileOrRun(9)) {
            listOf("--add-opens", "java.base/java.lang=ALL-UNNAMED")
        } else {
            emptyList()
        }
    })
    jvmArgumentProviders.add(CommandLineArgumentProvider {
        val testVersion = testVersionProvider.get()

  TF_DeleteBuffer(buffer);
  TF_DeleteStatus(s);
  return ret;
}

bool GetNodeDef(TF_Operation* oper, tensorflow::NodeDef* node_def) {
  TF_Status* s = TF_NewStatus();
  TF_Buffer* buffer = TF_NewBuffer();
  TF_OperationToNodeDef(oper, buffer, s);
  bool ret = TF_GetCode(s) == TF_OK;
  EXPECT_EQ(TF_OK, TF_GetCode(s)) << TF_Message(s);

	}
	return &fakeFileFakeFI{FileInfo: fi}, nil
}

type fakeFileFakeFI struct {
	fs.FileInfo
}

func (f *fakeFileFakeFI) Sys() any {
	return &syscall.Stat_t{Ino: 1}
}

// Open opens the named file.
// When Open returns an error, it should be of type *PathError
// with the Op field set to "open", the Path field set to name,
// and the Err field describing the problem.
//

const (
	// defaultExpirationSeconds is how long-lived a token to request (an hour)
	defaultExpirationSeconds = 60 * 60
)

// Audience to create tokens for
var tokenAudiences = []string{"istio-ca"}

// GetXdsResponse opens a gRPC connection to opts.xds and waits for a single response
func GetXdsResponse(dr *discovery.DiscoveryRequest, ns string, serviceAccount string, opts clioptions.CentralControlPlaneOptions,
	grpcOpts []grpc.DialOption,

```

### Cache the OpenAPI schema

You can use the property `.openapi_schema` as a "cache", to store your generated schema.

That way, your application won't have to generate the schema every time a user opens your API docs.

It will be generated only once, and then the same cached schema will be used for the next requests.

```Python hl_lines="13-14  25-26"
{!../../docs_src/extending_openapi/tutorial001.py!}
```

            }
            break;
        case OPERA:
            if (isLocalFile) {
                url = url.replaceFirst("file:/+", systemProperties.getProperty("file.protocol.winlocal.opera", "file://"));
            } else {
                url = url.replaceFirst("file:/+", systemProperties.getProperty("file.protocol.opera", "file://"));
            }
            break;
        default: