t.Run(fmt.Sprintf("Test %d", i+1), func(t *testing.T) {
			lc, err := ParseLifecycleConfig(bytes.NewReader([]byte(tc.inputConfig)))
			if err != tc.expectedParsingErr {
				t.Fatalf("%d: Expected %v during parsing but got %v", i+1, tc.expectedParsingErr, err)
			}
			if tc.expectedParsingErr != nil {
				// We already expect a parsing error,
				// no need to continue this test.
				return
			}

			wantResult: `{"request":{"uri":"/1","header":{"User-Agent":"test"}}}`,
			withJSON: `{"request":{"uri":"/1","header":{"User-Agent":"test"}}}
{"request":{"uri":"/2","header":{}}}`,
		},
		{
			name:       "is-not-missing",
			query:      `select * from s3object[*] as s where s.request.header['User-Agent'] is not missing`,
			wantResult: `{"request":{"uri":"/1","header":{"User-Agent":"test"}}}`,

It has:

* Seriously impressive performance.
* WebSocket support.
* In-process background tasks.
* Startup and shutdown events.
* Test client built on HTTPX.
* CORS, GZip, Static Files, Streaming responses.
* Session and Cookie support.
* 100% test coverage.
* 100% type annotated codebase.
* Few hard dependencies.

            }

            if (equals("LATEST", parent.getVersion()) || equals("RELEASE", parent.getVersion())) {
                addViolation(
                        problems,
                        Severity.WARNING,
                        Version.BASE,
                        "parent.version",
                        null,
                        "is either LATEST or RELEASE (both of them are being deprecated)",

{* ../../docs_src/schema_extra_example/tutorial001_py310.py hl[13:24] *}

这些额外信息会原样添加到该模型输出的 JSON Schema 中，并会在 API 文档中使用。

你可以使用属性 `model_config`，它接收一个 `dict`，详见 [Pydantic 文档：配置](https://docs.pydantic.dev/latest/api/config/)。

你可以设置 `"json_schema_extra"`，其值为一个 `dict`，包含你希望出现在生成 JSON Schema 中的任意附加数据，包括 `examples`。

/// tip | 提示

你也可以用同样的技巧扩展 JSON Schema，添加你自己的自定义额外信息。

例如，你可以用它为前端用户界面添加元数据等。

///

    }

    @Test
    public void test_sanitizeFilename_removesDoubleDotsAndWhitespace() {
        assertEquals("/test.log", AdminLogAction.sanitizeFilename(".. /test.log"));
        assertEquals("/test.log", AdminLogAction.sanitizeFilename(" ../test.log"));
        assertEquals("/test.log", AdminLogAction.sanitizeFilename(".. / .. /test.log"));

        assertEquals("\\test\\file.txt", request.getPath());

        // Test path with leading backslash (should be stripped)
        request.setPath("\\test\\file.txt");
        assertEquals("\\test\\file.txt", request.getPath());

        // Test path with trailing backslash (should be stripped)
        request.setPath("test\\directory\\");
        assertEquals("\\test\\directory", request.getPath());

/// tip | Dica

O SQLModel terá utilitários de migração envolvendo o Alembic, mas por enquanto, você pode usar o [Alembic](https://alembic.sqlalchemy.org/en/latest/) diretamente.

///

### Criar um Hero { #create-a-hero }

Como cada modelo SQLModel também é um modelo Pydantic, você pode usá-lo nas mesmas **anotações de tipo** que usaria para modelos Pydantic.

Example:

```sh
export MINIO_DOMAIN=mydomain.com
minio server /data
```

    @Test
    @DisplayName("Test isDFSSupported returns false")
    void testIsDFSSupportedFalse() {
        // Arrange
        when(negotiationResponse.isDFSSupported()).thenReturn(false);

        // Act
        boolean result = negotiationResponse.isDFSSupported();

        // Assert
        assertFalse(result);
        verify(negotiationResponse).isDFSSupported();
    }

    @Test