netdfs.DfsStorageInfo storageInfo = new netdfs.DfsStorageInfo();
        storageInfo.state = netdfs.DFS_STORAGE_STATE_ONLINE;
        storageInfo.server_name = "server1";
        storageInfo.share_name = "share1";

        ByteArrayOutputStream bos = new ByteArrayOutputStream();
        // Create buffer for encoding - initially allocate some space
        byte[] encodeBuffer = new byte[1024];

type ReadMultipleReq struct {
	Bucket       string   `msg:"bk"`           // Bucket. Can be empty if multiple buckets.
	Prefix       string   `msg:"pr,omitempty"` // Shared prefix of all files. Can be empty. Will be joined to filename without modification.
	Files        []string `msg:"fl"`           // Individual files to read.
	MaxSize      int64    `msg:"ms"`           // Return error if size is exceed.

   * '\\u5432'} would yield the byte array {@code {0x54, 0x32}}.
   *
   * <p>If you need to convert and concatenate several values (possibly even of different types),
   * use a shared {@link java.nio.ByteBuffer} instance, or use {@link
   * com.google.common.io.ByteStreams#newDataOutput()} to get a growable buffer.
   */
  @GwtIncompatible // doesn't work
  public static byte[] toByteArray(char value) {

   * (short) 0x1234} would yield the byte array {@code {0x12, 0x34}}.
   *
   * <p>If you need to convert and concatenate several values (possibly even of different types),
   * use a shared {@link java.nio.ByteBuffer} instance, or use {@link
   * com.google.common.io.ByteStreams#newDataOutput()} to get a growable buffer.
   */
  @GwtIncompatible // doesn't work
  public static byte[] toByteArray(short value) {

  private static void testConcatOverflow(int arraysDim1, int arraysDim2) {
    assertThat((long) arraysDim1 * arraysDim2).isNotEqualTo((long) (arraysDim1 * arraysDim2));

    int[][] arrays = new int[arraysDim1][];
    // it's shared to avoid using too much memory in tests
    int[] sharedArray = new int[arraysDim2];
    Arrays.fill(arrays, sharedArray);

    try {
      Ints.concat(arrays);
      fail();

rder:1px solid #dee2e6;display:-ms-flexbox;display:flex;margin-right:1rem;max-width:7rem;padding:.5rem}.product-image-thumb img{max-width:100%;height:auto;-ms-flex-item-align:center;align-self:center}.product-image-thumb:hover{opacity:.5}.product-share a{margin-right:.5rem}.projects td{vertical-align:middle}.projects .list-inline{margin-bottom:0}.projects .table-avatar img,.projects img.table-avatar{border-radius:50%;display:inline;width:2.5rem}.projects .project-state{text-align:center}body.iframe-mode...

"`one_person`은 `Person`이라는 **클래스**다"라는 뜻이 아닙니다.

## Pydantic 모델 { #pydantic-models }

[Pydantic](https://docs.pydantic.dev/)은 데이터 검증을 수행하는 파이썬 라이브러리입니다.

속성을 가진 클래스 형태로 데이터의 "모양(shape)"을 선언합니다.

그리고 각 속성은 타입을 가집니다.

그 다음 그 클래스의 인스턴스를 몇 가지 값으로 생성하면, 값들을 검증하고, (그런 경우라면) 적절한 타입으로 변환한 뒤, 모든 데이터를 가진 객체를 제공합니다.

그리고 그 결과 객체에 대해 에디터의 모든 지원을 받을 수 있습니다.

Pydantic 공식 문서의 예시:

この例外には、要求されたスコープがあればそれらを空白区切りの文字列（`scope_str` を使用）として含めます。このスコープ文字列は `WWW-Authenticate` ヘッダに入れます（仕様の一部です）。

{* ../../docs_src/security/tutorial005_an_py310.py hl[106,108:116] *}

## `username` とデータ構造の検証 { #verify-the-username-and-data-shape }

`username` を取得できていることを確認し、スコープを取り出します。

そして、そのデータを Pydantic モデルで検証します（`ValidationError` 例外を捕捉）。JWT トークンの読み取りや Pydantic によるデータ検証でエラーが発生した場合は、先ほど作成した `HTTPException` を送出します。

   *
   * <p>It should be noted that using a {@code Striped<L>} with relatively few stripes, and {@code
   * bulkGet(keys)} with a relative large number of keys can cause an excessive number of shared
   * stripes (much like the birthday paradox, where much fewer than anticipated birthdays are needed
   * for a pair of them to match). Please consider carefully the implications of the number of

    assertThat((long) arraysDim1 * arraysDim2).isNotEqualTo((long) (arraysDim1 * arraysDim2));

    char[][] arrays = new char[arraysDim1][];
    // it's shared to avoid using too much memory in tests
    char[] sharedArray = new char[arraysDim2];
    Arrays.fill(arrays, sharedArray);

    try {
      Chars.concat(arrays);
      fail();