assert response.status_code == 404
    assert response.json() == {"detail": "Item not found"}


def test_create_item():
    response = client.post(
        "/items/",
        headers={"X-Token": "coneofsilence"},
        json={"id": "foobar", "title": "Foo Bar", "description": "The Foo Barters"},
    )
    assert response.status_code == 200
    assert response.json() == {
        "id": "foobar",
        "title": "Foo Bar",

        "/items/123",
        json={"name": "Foo", "price": 50.1},
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 123,
        "name": "Foo",
        "price": 50.1,
        "description": None,
        "tax": None,
    }


def test_put_with_no_data(client: TestClient):
    response = client.put("/items/123", json={})
    assert response.status_code == 422

**FastAPI** возьмёт Pydantic-модель оттуда, сгенерирует JSON‑схему и поместит её в нужное место.

Нужное место:

* В ключе `content`, значением которого является другой JSON‑объект (`dict`), содержащий:
    * Ключ с типом содержимого, например `application/json`, значением которого является другой JSON‑объект, содержащий:
        * Ключ `schema`, значением которого является JSON‑схема из модели — вот нужное место.

```bash
# Export Solr documents as JSON
curl "http://solr-server:8983/solr/collection1/select?q=*:*&rows=10000&wt=json" \
  -o solr-export.json
```

**Step 2: Transform to Fess Format**

Create a transformation script to map Solr fields to Fess fields:

```python
import json

# Load Solr export
with open('solr-export.json', 'r') as f:
    solr_data = json.load(f)

# Transform documents

Refer to the dashboard [json file here](https://raw.githubusercontent.com/minio/minio/master/docs/metrics/prometheus/grafana/minio-dashboard.json).

![Grafana](https://raw.githubusercontent.com/minio/minio/master/docs/metrics/prometheus/grafana/grafana-minio.png)

    * 一個媒體型別作為鍵，例如 `application/json`，其值是另一個 JSON 物件，當中包含：
        * 鍵 `schema`，其值是該模型的 JSON Schema，這裡就是正確的位置。
            * **FastAPI** 會在這裡加入一個指向你 OpenAPI 中全域 JSON Schemas 的參照，而不是直接把它嵌入。如此一來，其他應用與用戶端可以直接使用那些 JSON Schemas，提供更好的程式碼產生工具等。

///

這個路徑操作在 OpenAPI 中產生的回應將會是：

```JSON hl_lines="3-12"
{
    "responses": {
        "404": {
            "description": "Additional Response",
            "content": {

def test_get():
    response = client.post(
        "/invoices/", json={"id": "fooinvoice", "customer": "John", "total": 5.3}
    )
    assert response.status_code == 200, response.text
    assert response.json() == {"msg": "Invoice received"}


def test_openapi_schema():
    with client:
        response = client.get("/openapi.json")
        assert response.json() == snapshot(
            {
                "openapi": "3.1.0",

    assert response.status_code == 200, response.text
    assert response.json() == {"username": "Bearer footokenbar"}


def test_security_oauth2_password_other_header():
    response = client.get("/users/me", headers={"Authorization": "Other footokenbar"})
    assert response.status_code == 200, response.text
    assert response.json() == {"username": "Other footokenbar"}

///

## Responses JSON { #json-responses }

Por defecto FastAPI devuelve responses JSON.

Si declaras un [Response Model](../tutorial/response-model.md) FastAPI lo usará para serializar los datos a JSON, usando Pydantic.

Si no declaras un response model, FastAPI usará el `jsonable_encoder` explicado en [Codificador Compatible con JSON](../tutorial/encoder.md) y lo pondrá en un `JSONResponse`.

	Type     BatchJobReplicateResourceType `yaml:"type" json:"type"`
	Bucket   string                        `yaml:"bucket" json:"bucket"`
	Prefix   string                        `yaml:"prefix" json:"prefix"`
	Endpoint string                        `yaml:"endpoint" json:"endpoint"`
	Path     string                        `yaml:"path" json:"path"`
	Creds    BatchJobReplicateCredentials  `yaml:"credentials" json:"credentials"`
}