[Pydantic](https://docs.pydantic.dev/) is a Python library to perform data validation.

You declare the "shape" of the data as classes with attributes.

And each attribute has a type.

Then you create an instance of that class with some values and it will validate the values, convert them to the appropriate type (if that's the case) and give you an object with all the data.

And you get all the editor support with that resulting object.

import configurations.ParallelizationMethod
import java.util.SortedSet

class TestClassTime(
    val sourceSet: String,
    val buildTimeMs: Int,
)

data class TestCoverageAndBucketSplits(
    val testCoverageUuid: Int,
    val buckets: List<FunctionalTestBucket>,
)

data class FunctionalTestBucket(
    val subprojects: SortedSet<String>,
    val parallelizationMethod: ParallelizationMethod,
) {

 * Implementations can specify how long cached data should be retained.
 *
 * @since 4.0.0
 */
@Experimental
public interface CacheMetadata {

    /**
     * Returns the cache retention that should be applied to the associated data.
     *
     * @return The CacheRetention indicating how long data should be retained, or null if
     *         no specific cache retention is defined
     */

	}

	harumph := Harumph{}
	if err := DB.Create(&harumph).Error; err == nil {
		t.Fatalf("should failed to create data, name can't be blank")
	}

	harumph = Harumph{Name: "jinzhu"}
	if err := DB.Create(&harumph).Error; err != nil {
		t.Fatalf("should be able to create data, but got %v", err)
	}

	var result Harumph
	if err := DB.First(&result, "id = ?", harumph.ID).Error; err != nil || harumph.Name != "jinzhu" {

      if (context.executionException.isPresent) return@AfterEachCallback
      assertThat(data.readByteString().hex(), "Data not empty")
        .isEqualTo("")
    }

  // Mutually exclusive. Use the one corresponding to the peer whose behavior you wish to test.
  private val serverWriter =
    WebSocketWriter(
      isClient = false,
      sink = data,
      random = random,
      perMessageDeflate = false,

查看 `/docs` 时，你会看到字段 `data` 期望接收 base64 编码的字节：

<div class="screenshot">
<img src="/img/tutorial/json-base64-bytes/image01.png">
</div>

你可以发送如下请求：

```json
{
    "description": "Some data",
    "data": "aGVsbG8="
}
```

/// tip | 提示

`aGVsbG8=` 是 `hello` 的 base64 编码。

///

随后 Pydantic 会解码该 base64 字符串，并在模型的 `data` 字段中提供原始字节。

你将会收到类似的响应：

```json
{

    @BeforeEach
    void setUp() {
        ace = new ACE();
    }

    @Test
    @DisplayName("Test decode with allow ACE")
    void testDecodeAllowACE() throws Exception {
        // Prepare test data - Allow ACE
        testBuffer = new byte[100];
        testBuffer[0] = 0x00; // Allow ACE
        testBuffer[1] = 0x03; // FLAGS_OBJECT_INHERIT | FLAGS_CONTAINER_INHERIT
        testBuffer[2] = 0x20; // Size low byte (32)

abstract class GeneratePlatformsDataTask : DefaultTask() {

    data class PlatformData(val name: String, val dirs: List<String>, val uses: List<String>)

    @get:OutputFile
    abstract val outputFile: RegularFileProperty

    @get:Input
    abstract val platforms: ListProperty<Platform>

    @TaskAction
    fun action() {
        val allPlatforms = platforms.get()
        val data = allPlatforms.map { platform ->
            PlatformData(

	b.SetParallelism(4)
	b.RunParallel(func(pb *testing.PB) {
		c := make(chan bool)
		var data [4 << 10]uint64
		for i := 0; pb.Next(); i++ {
			if i%4 == 0 {
				m.Lock(id, source)
				acc0 -= 100
				acc1 += 100
				m.Unlock(b.Context())
			} else {
				for i := 0; i < len(data); i += 4 {
					data[i]++
				}
				// Elaborate way to say runtime.Gosched

from fastapi import FastAPI, Form
from pydantic import BaseModel

app = FastAPI()


class FormData(BaseModel):
    username: str
    password: str


@app.post("/login/")
async def login(data: FormData = Form()):