app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Item = Body(
        examples=[
            {
                "name": "Foo",
                "description": "A very nice Item",
                "price": 35.4,

Ви можете надіслати запит так:

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

/// tip | Порада

`aGVsbG8=` - це кодування base64 для `hello`.

///

Після цього Pydantic декодує строку base64 і надасть вам початкові байти в полі моделі `data`.

Ви отримаєте відповідь приблизно таку:

```json
{
  "description": "Some data",
  "content": "hello"
}
```

class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(
    *,
    item_id: int,
    item: Annotated[
        Item,
        Body(
            examples=[
                {
                    "name": "Foo",
                    "description": "A very nice Item",
                    "price": 35.4,

  }

  override fun afterEach(context: ExtensionContext?) {
    logger.setLevel(previousLevel)
    logger.removeHandler(handler)
  }

  override fun apply(
    base: Statement,
    description: Description,
  ): Statement =
    object : Statement() {
      override fun evaluate() {
        beforeEach(null)
        try {
          base.evaluate()
        } finally {
          afterEach(null)
        }

  <modelVersion>4.0.0</modelVersion>

  <groupId>inheritance</groupId>
  <artifactId>parent</artifactId>
  <version>11-SNAPSHOT</version>

  <name>Model inheritance test</name>
  <description>Model inheritance description</description>
  <url>http://www.apache.org/</url>

  <mailingLists>
    <mailingList>
      <name>parent</name>
      <post>******@****.***</post>

    stage: Stage,
    bucketIndex: Int,
    description: String,
    tests: Map<String, List<Scenario>>,
): PerformanceTest {
    val descriptionWithMaybeBucketIndex =
        if (performanceTestCoverage.type == PerformanceTestType.FLAKINESS_DETECTION) {
            "$description - index $bucketIndex"
        } else {
            description
        }
    return PerformanceTest(
        model,

    item = {"item_id": item_id}
    if q:
        item.update({"q": q})
    if not short:
        item.update(
            {"description": "This is an amazing item that has a long description"}
        )

from fastapi import FastAPI
from pydantic import BaseModel as BaseModelV2
from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    size: float


class ItemV2(BaseModelV2):
    name: str
    description: str | None = None
    size: float


app = FastAPI()


@app.post("/items/", response_model=ItemV2)
async def create_item(item: Item):

app = FastAPI()


@app.post("/files/")
async def create_file(file: Annotated[bytes, File(description="A file read as bytes")]):
    return {"file_size": len(file)}


@app.post("/uploadfile/")
async def create_upload_file(
    file: Annotated[UploadFile, File(description="A file read as UploadFile")],
):

  private final char[] table;
  private final boolean containsZero;
  private final long filter;

  private SmallCharMatcher(char[] table, long filter, boolean containsZero, String description) {
    super(description);
    this.table = table;
    this.filter = filter;
    this.containsZero = containsZero;
  }

  private static final int C1 = 0xcc9e2d51;
  private static final int C2 = 0x1b873593;

  /*