*/
    private String sanitizeForLog(String str) {
        if (str == null) {
            return "null";
        }

        // Truncate long strings
        if (str.length() > 100) {
            str = str.substring(0, 100) + "...";
        }

        // Remove control characters
        return str.replaceAll("[\\x00-\\x1F\\x7F]", "?");
    }

    /**

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: str | None = None
    traceparent: str | None = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: CommonHeaders = Header()):

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


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

    model_config = {
        "json_schema_extra": {
            "examples": [
                {
                    "name": "Foo",
                    "description": "A very nice Item",
                    "price": 35.4,

from typing import Any


def get_body_model_name(openapi: dict[str, Any], path: str) -> str:
    body = openapi["paths"][path]["post"]["requestBody"]
    body_schema = body["content"]["multipart/form-data"]["schema"]

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: Union[str, None] = None
    traceparent: Union[str, None] = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(headers: CommonHeaders = Header(convert_underscores=False)):

     * @throws Exception
     */
    public void testFromBinaryToObject_DefaultFilter_AllowsSafeClasses() throws Exception {
        // Test String
        final String str = "test string";
        byte[] binary = SerializeUtil.fromObjectToBinary(str);
        assertEquals(str, SerializeUtil.fromBinaryToObject(binary));

        // Test Integer
        final Integer num = 42;
        binary = SerializeUtil.fromObjectToBinary(num);

from fastapi import FastAPI, Header
from pydantic import BaseModel

app = FastAPI()


class CommonHeaders(BaseModel):
    host: str
    save_data: bool
    if_modified_since: Union[str, None] = None
    traceparent: Union[str, None] = None
    x_tag: list[str] = []


@app.get("/items/")
async def read_items(
    headers: Annotated[CommonHeaders, Header(convert_underscores=False)],
):

到目前为止，您一直在使用常见的数据类型，如:

* `int`
* `float`
* `str`
* `bool`

但是您也可以使用更复杂的数据类型。

您仍然会拥有现在已经看到的相同的特性:

* 很棒的编辑器支持。
* 传入请求的数据转换。
* 响应数据转换。
* 数据验证。
* 自动补全和文档。

## 其他数据类型

下面是一些你可以使用的其他数据类型:

* `UUID`:
    * 一种标准的 "通用唯一标识符" ，在许多数据库和系统中用作ID。
    * 在请求和响应中将以 `str` 表示。
* `datetime.datetime`:
    * 一个 Python `datetime.datetime`.
    * 在请求和响应中将表示为 ISO 8601 格式的 `str` ，比如: `2008-09-15T15:53:00+05:00`.

		}
	}
}

func TestParseKey(t *testing.T) {
	testCases := []struct {
		str         string
		expectedKey Key
	}{
		{
			str: "01894394-d046-4783-ba0d-f1c6885790dc.event",
			expectedKey: Key{
				Name:      "01894394-d046-4783-ba0d-f1c6885790dc",
				Extension: ".event",
				ItemCount: 1,
			},
		},
		{
			str: "100:01894394-d046-4783-ba0d-f1c6885790dc.event.snappy",
			expectedKey: Key{

from typing import Union

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


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


@app.put("/items/{item_id}")
async def update_item(
    item_id: int,
    item: Item = Body(
        examples=[
            {
                "name": "Foo",