We can do the same as before to **read** `Hero`s, again, we use `response_model=list[HeroPublic]` to ensure that the data is validated and serialized correctly.

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[65:72] hl[65] *}

### Read One Hero with `HeroPublic` { #read-one-hero-with-heropublic }

We can **read** a single hero:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[65:72] hl[65] *}

### Einen einzelnen Helden mit `HeroPublic` lesen { #read-one-hero-with-heropublic }

Wir können einen einzelnen Helden **lesen**:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

Аналогично мы можем **читать** `Hero` — снова используем `response_model=list[HeroPublic]`, чтобы данные валидировались и сериализовались корректно.

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[65:72] hl[65] *}

### Чтение одного героя с `HeroPublic` { #read-one-hero-with-heropublic }

Мы можем **прочитать** одного героя:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[65:72] hl[65] *}

### Ler Um Hero com `HeroPublic` { #read-one-hero-with-heropublic }

Podemos **ler** um único herói:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

Podemos hacer lo mismo que antes para **leer** `Hero`s, nuevamente, usamos `response_model=list[HeroPublic]` para asegurar que los datos se validen y serialicen correctamente.

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[65:72] hl[65] *}

### Leer Un Hero con `HeroPublic` { #read-one-hero-with-heropublic }

Podemos **leer** un único héroe:

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[75:80] hl[77] *}

func biggestZipBytes() []byte {
	s := `
0000000 50 4b 03 04 14 00 08 00 08 00 00 00 00 00 00 00
0000010 00 00 00 00 00 00 00 00 00 00 0a 00 00 00 62 69
0000020 67 67 65 72 2e 7a 69 70 ec dc 6b 4c 53 67 18 07
0000030 f0 16 c5 ca 65 2e cb b8 94 20 61 1f 44 33 c7 cd
0000040 c0 86 4a b5 c0 62 8a 61 05 c6 cd 91 b2 54 8c 1b
0000050 63 8b 03 9c 1b 95 52 5a e3 a0 19 6c b2 05 59 44
0000060 64 9d 73 83 71 11 46 61 14 b9 1d 14 09 4a c3 60

		// Test listing a directory which contains an empty directory (64)
		{"test-bucket-empty-dir", "", "temporary/", "", 10, resultCases[33], nil, true},
		// Test listing with marker > last object such that response should be empty (65)
		{"test-bucket-single-object", "", "A/C", "", 1000, resultCases[34], nil, true},
		// Test listing an object with a trailing slash and a slash delimiter (66)

			closer.Close()
		}
	})
}

func toSnake(camel string) (snake string) {
	var b strings.Builder
	l := len(camel)
	for i, v := range camel {
		// A is 65, a is 97
		if v >= 'a' {
			b.WriteRune(v)
			continue
		}
		// v is capital letter here
		// disregard first letter
		// add underscore if last letter is capital letter

}

func testAPIPutObjectStreamSigV4Handler(obj ObjectLayer, instanceType, bucketName string, apiRouter http.Handler,
	credentials auth.Credentials, t *testing.T,
) {
	objectName := "test-object"
	bytesDataLen := 65 * humanize.KiByte
	bytesData := bytes.Repeat([]byte{'a'}, bytesDataLen)
	oneKData := bytes.Repeat([]byte("a"), 1*humanize.KiByte)

	var err error

	type streamFault int
	const (
		None streamFault = iota

*testing.B) { // IG 10.3.A says "ML-DSA digital signature generation CASTs should cover // all applicable rejection sampling loop paths". For ML-DSA-44, there are // four paths. For ML-DSA-65 and ML-DSA-87, only three. This benchmark helps // us figure out which is faster: four rejections of ML-DSA-44, or three of // ML-DSA-65. (It's the former, but only barely.) b.Run("ML-DSA-44", func(b *testing.B) { // Same as TestACVPRejectionKAT/Test/Path/ML-DSA-44/1. seed := fromHex("5C624FCC1862452452D0") μ := fro...