import importlib
from types import ModuleType
from unittest.mock import patch

import pytest

from ...utils import needs_py310


@pytest.fixture(
    name="module",
    params=[
        pytest.param("tutorial009_py39"),
        pytest.param("tutorial009_py310", marks=needs_py310),
        pytest.param("tutorial009b_py39"),
    ],
)
def get_module(request: pytest.FixtureRequest):

import importlib
import re
from types import ModuleType
from unittest.mock import patch

import pytest

from ...utils import needs_py310


@pytest.fixture(
    name="module",
    params=[
        pytest.param("tutorial009c_py39"),
        pytest.param("tutorial009c_py310", marks=needs_py310),
    ],
)
def get_module(request: pytest.FixtureRequest):
    mod = importlib.import_module(f"docs_src.python_types.{request.param}")

{* ../../docs_src/body/tutorial001_py310.py hl[16] *}

...and declare its type as the model you created, `Item`.

## Results { #results }

With just that Python type declaration, **FastAPI** will:

* Read the body of the request as JSON.
* Convert the corresponding types (if needed).
* Validate the data.

          signature_crossrefs: true
          show_symbol_type_heading: true
          show_symbol_type_toc: true
nav:
- FastAPI: index.md
- features.md
- Learn:
  - learn/index.md
  - python-types.md
  - async.md
  - environment-variables.md
  - virtual-environments.md
  - Tutorial - User Guide:
    - tutorial/index.md
    - tutorial/first-steps.md
    - tutorial/path-params.md

 * either express or implied. See the License for the specific language
 * governing permissions and limitations under the License.
 */
package org.codelibs.fess.storage;

/**
 * Enum for supported storage types.
 */
public enum StorageType {

    /** Amazon S3 */
    S3,

    /** Google Cloud Storage */
    GCS,

    /** S3-compatible storage (MinIO, etc.) */
    S3_COMPAT

interface rpc
{
	/* base types */

	typedef unsigned char uint8_t;
	typedef unsigned short uint16_t;
	typedef unsigned int uint32_t;

	/* dce */

	typedef struct {
	    uint32_t time_low;
	    uint16_t time_mid;
	    uint16_t time_hi_and_version;
	    uint8_t clock_seq_hi_and_reserved;
	    uint8_t clock_seq_low;
	    uint8_t node[6];
	} uuid_t;

	/* win32 stuff */

	typedef struct {
		uint32_t type;
		uuid_t uuid;

interface rpc
{
	/* base types */

	typedef unsigned char uint8_t;
	typedef unsigned short uint16_t;
	typedef unsigned int uint32_t;

	/* dce */

	typedef struct {
	    uint32_t time_low;
	    uint16_t time_mid;
	    uint16_t time_hi_and_version;
	    uint8_t clock_seq_hi_and_reserved;
	    uint8_t clock_seq_low;
	    uint8_t node[6];
	} uuid_t;

	/* win32 stuff */

	typedef struct {
		uint32_t type;
		uuid_t uuid;

import importlib
from types import ModuleType

import pytest
from pytest import MonkeyPatch


@pytest.fixture(
    name="mod_path",
    params=[
        pytest.param("app02_py39"),
        pytest.param("app02_an_py39"),
    ],
)
def get_mod_path(request: pytest.FixtureRequest):
    mod_path = f"docs_src.settings.{request.param}"
    return mod_path


@pytest.fixture(name="main_mod")

{* ../../docs_src/response_model/tutorial003_04_py310.py hl[8] *}

... das scheitert, da die Typannotation kein Pydantic-Typ ist, und auch keine einzelne `Response`-Klasse, oder -Unterklasse, es ist eine Union (eines von beiden) von `Response` und `dict`.

### Responsemodell deaktivieren { #disable-response-model }

	httpTimeout time.Duration
}

// Name returns the name of the target
func (h *Target) Name() string {
	return "minio-http-" + h.config.Name
}

// Type - returns type of the target
func (h *Target) Type() types.TargetType {
	return types.TargetHTTP
}

// Endpoint returns the backend endpoint
func (h *Target) Endpoint() string {
	return h.config.Endpoint.String()
}