from pydantic import BaseModel


class User(BaseModel):
    id: int
    name: str = "John Doe"
    signup_ts: datetime | None = None
    friends: list[int] = []


external_data = {
    "id": "123",
    "signup_ts": "2017-06-01 12:22",
    "friends": [1, "2", b"3"],
}
user = User(**external_data)
print(user)
# > User id=123 name='John Doe' signup_ts=datetime.datetime(2017, 6, 1, 12, 22) friends=[1, 2, 3]
print(user.id)

app = FastAPI()


class Item(BaseModel):
    name: str
    description: Union[str, None] = None
    price: float
    tax: Union[float, None] = None
    tags: list[str] = []


@app.post("/items/")
async def create_item(item: Item) -> Item:
    return item


@app.get("/items/")
async def read_items() -> list[Item]:
    return [
        Item(name="Portal Gun", price=42.0),

app = FastAPI()


class Image(BaseModel):
    url: HttpUrl
    name: str


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None
    tags: set[str] = set()
    images: list[Image] | None = None


class Offer(BaseModel):
    name: str
    description: str | None = None
    price: float
    items: list[Item]

        final List<Map<String, String>> itemList = new ArrayList<>();
        for (final String name : dataStoreNames) {
            final Map<String, String> map = new HashMap<>();
            map.put(Constants.ITEM_LABEL, name);
            map.put(Constants.ITEM_VALUE, name);
            itemList.add(map);
        }
        RenderDataUtil.register(data, "handlerNameItems", itemList);
    }

  // Attempts to look up the tensor named "name" and stores the found result in
  // "out_tensor".
  void GetTensor(const string& name,
                 std::unique_ptr<tensorflow::Tensor>* out_tensor,
                 TF_Status* out_status) const;

 private:
  // Uses "v2_reader_" to build "var name -> shape" and "var name -> data type"
  // maps; both owned by caller.

		Type:      histogramMetric,
	}
}

func getBucketObjectVersionsMD() MetricDescription {
	return MetricDescription{
		Namespace: bucketMetricNamespace,
		Subsystem: objectsSubsystem,
		Name:      versionDistribution,
		Help:      "Distribution of object sizes in the bucket, includes label for the bucket name",
		Type:      histogramMetric,
	}
}

)

func TestConfigWriter_Prime(t *testing.T) {
	tests := []struct {
		name        string
		wantConfigs int
		inputFile   string
		wantErr     bool
	}{
		{
			name:        "errors if unable to unmarshal bytes",
			inputFile:   "",
			wantConfigs: 0,
			wantErr:     true,
		},
		{
			name:        "loads valid ztunnel config_dump",
			inputFile:   "testdata/dump.json",
			wantConfigs: 27,

<components>
	<include path="convention.xml" />
	<include path="lastaflute_core.xml"/>
	<include path="fess.xml" />

	<component name="fessSuggest" class="org.codelibs.fess.exec.SuggestCreator"
			   instance="prototype">
	</component>
	<component name="suggestHelper" class="org.codelibs.fess.helper.SuggestHelper">
	</component>

  <groupId>maven-test</groupId>
  <artifactId>maven-test-a</artifactId>
  <packaging>jar</packaging>
  <version>1.0</version>
  <repositories>
    <repository>
      <id>central</id>
      <name>Fake Maven Central Repository</name>
      <url>file://dummy</url>
    </repository>
  </repositories>
  <dependencies>
    <dependency>
      <groupId>maven-test</groupId>
      <artifactId>maven-test-b</artifactId>

app = FastAPI()

app.mount("/static", StaticFiles(directory="static"), name="static")


templates = Jinja2Templates(directory="templates")


@app.get("/items/{id}", response_class=HTMLResponse)
async def read_item(request: Request, id: str):
    return templates.TemplateResponse(
        request=request, name="item.html", context={"id": id}