여러분은 자동으로 생성된 인터랙티브 API(<a href="https://github.com/swagger-api/swagger-ui" class="external-link" target="_blank">Swagger UI</a>에서 제공된)를 볼 수 있습니다:

![Swagger UI](https://fastapi.tiangolo.com/img/index/index-01-swagger-ui-simple.png)

## 대안 API 문서

   * serialized with XML 1.0.
   *
   * <p>For SOAP 1.1 messages, see {@code XML_UTF_8} per <a
   * href="http://www.w3.org/TR/2000/NOTE-SOAP-20000508/">W3C Note on Simple Object Access Protocol
   * (SOAP) 1.1</a>
   *
   * @since 20.0
   */
  public static final MediaType SOAP_XML_UTF_8 = createConstantUtf8(APPLICATION_TYPE, "soap+xml");

    simultaneously. This can be used to implement interactive conversations within a single HTTP
    call.

    Create duplex calls by overriding the new `RequestBody.isDuplex()` method to return true.
    This simple option dramatically changes the behavior of the request body and of the entire
    call.

    The `RequestBody.writeTo()` method may now retain a reference to the provided sink and

	// test cases with sample input and expected output.
	testCases := []struct {
		bucketName string
		// bucket policy to be set,
		// set as request body.
		bucketPolicyReader io.ReadSeeker
		// length in bytes of the bucket policy being set.

	if versionID == "" {
		versionID = dobj.VersionID
	}

	rinfo = dobj.ReplicationState.targetState(tgt.ARN)
	rinfo.OpType = dobj.OpType
	rinfo.endpoint = tgt.EndpointURL().Host
	rinfo.secure = tgt.EndpointURL().Scheme == "https"
	defer func() {
		if rinfo.ReplicationStatus == replication.Completed && tgt.ResetID != "" && dobj.OpType == replication.ExistingObjectReplicationType {

But you can also exploit the benefits of parallelism and multiprocessing (having multiple processes running in parallel) for **CPU bound** workloads like those in Machine Learning systems.

That, plus the simple fact that Python is the main language for **Data Science**, Machine Learning and especially Deep Learning, make FastAPI a very good match for Data Science / Machine Learning web APIs and applications (among many others).

}

// Set server_def on the context, possibly updating it.
// TODO(b/291142876) Simplify TFE_ContextSetServerDefWithTimeoutAndRetries and
// TFE_ContextUpdateServerDefWithTimeout to be simple wrappers around the same
// C++ function.
// Retries are used for CreateContext calls, which is used in
// ParameterServerStrategy initialization to be robust to worker preemption.

	public final fun path ()Ljava/lang/String;
	public final fun persistent ()Z
	public final fun sameSite ()Ljava/lang/String;
	public final fun secure ()Z
	public fun toString ()Ljava/lang/String;
	public final fun value ()Ljava/lang/String;
}

public final class okhttp3/Cookie$Builder {
	public fun <init> ()V
	public final fun build ()Lokhttp3/Cookie;

		// as a List() call is an important performance improvement.
		//
		// Spark based s3a committers are a  big enough use-case to have this optimization.
		//
		// A sample code to see the improvements is as follows, this sample code is
		// simply a read on JSON from MinIO and write it back as "parquet".
		//
		// import org.apache.spark.sql.SparkSession

node-role.kubernetes.io/ingress: platform annotations: {} # kubernetes.io/ingress.class: nginx # kubernetes.io/tls-acme: "true" # kubernetes.io/ingress.allow-http: "false" # kubernetes.io/ingress.global-static-ip-name: "" # nginx.ingress.kubernetes.io/secure-backends: "true" # nginx.ingress.kubernetes.io/backend-protocol: "HTTPS" # nginx.ingress.kubernetes.io/whitelist-source-range: 0.0.0.0/0 path: / hosts: - minio-example.local tls: [] # - secretName: chart-example-tls # hosts: # - chart-example.local...