"/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

def test_post():
    data = {"title": "towel", "size": 5}
    response = client.post("/items/", json=data)
    assert response.status_code == 200, response.text
    assert response.json() == data


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text
    assert response.json() == {
        "openapi": "3.1.0",
        "info": {"title": "FastAPI", "version": "0.1.0"},

**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.

    assert response.status_code == 200, response.text
    assert response.json() == {"item": "The Foo Wrestlers"}


def test_get_item_not_found():
    response = client.get("/items/bar")
    assert response.status_code == 404, response.text
    assert response.headers.get("x-error") == "Some custom header"
    assert response.json() == {"detail": "Item not found"}


def test_get_starlette_item():

def test_post_body_valid(client: TestClient):
    response = client.put(
        "/items/5",
        json={
            "importance": 2,
            "item": {"name": "Foo", "price": 50.5},
            "user": {"username": "Dave"},
        },
    )
    assert response.status_code == 200
    assert response.json() == {
        "item_id": 5,
        "importance": 2,
        "item": {
            "name": "Foo",

def test_call_invalid():
    response = client.post("/", json={"foo": {"bar": "baz"}})
    assert response.status_code == 422


def test_call_valid():
    response = client.post("/", json={})
    assert response.status_code == 200
    assert response.json() == {}


def test_openapi_schema():
    response = client.get("/openapi.json")
    assert response.status_code == 200, response.text

```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

    assert response.json() == {
        "detail": [
            {
                "type": "missing",
                "loc": ["body", "files"],
                "msg": "Field required",
                "input": None,
            }
        ]
    }


def test_post_body_json(client: TestClient):
    response = client.post("/files/", json={"file": "Foo"})

// XferStats has transfer stats for replication
type XferStats struct {
	Curr    float64          `json:"currRate" msg:"cr"`
	Avg     float64          `json:"avgRate" msg:"av"`
	Peak    float64          `json:"peakRate" msg:"p"`
	N       int64            `json:"n" msg:"n"`
	measure *rateMeasurement `json:"-"`
	sma     *SMA             `json:"-"`
}

// Clone returns a copy of XferStats
func (rx *XferStats) Clone() *XferStats {

**FastAPI** prendra le modèle Pydantic à partir de là, générera le `JSON Schema` et le placera au bon endroit.

Le bon endroit est :

* Dans la clé `content`, qui a pour valeur un autre objet JSON (`dict`) qui contient :
    * Une clé avec le type de support, par ex. `application/json`, qui contient comme valeur un autre objet JSON, qui contient :
        * Une clé `schema`, qui a pour valeur le schéma JSON du modèle, voici le bon endroit.