package jcifs.smb1.dcerpc.msrpc;

import jcifs.smb1.dcerpc.DcerpcMessage;
import jcifs.smb1.dcerpc.ndr.NdrBuffer;
import jcifs.smb1.dcerpc.ndr.NdrException;
import jcifs.smb1.dcerpc.ndr.NdrLong;
import jcifs.smb1.dcerpc.ndr.NdrObject;

/**
 * DCE/RPC interface for Distributed File System (DFS) operations.
 * Provides structures and methods for DFS management and enumeration.
 */
public class netdfs {

    /**

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package okhttp3.tls.internal.der

import java.math.BigInteger
import java.net.ProtocolException
import okio.ByteString

/**
 * ASN.1 adapters adapted from the specifications in [RFC 5280][rfc_5280].
 *
 * [rfc_5280]: https://tools.ietf.org/html/rfc5280
 */

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

import org.codelibs.fess.mylasta.direction.FessConfig;
import org.codelibs.fess.unit.UnitFessTestCase;
import org.codelibs.fess.util.ComponentUtil;

public class PermissionHelperTest extends UnitFessTestCase {

    public PermissionHelper permissionHelper;

    @Override

As it is discouraged, the interactive docs with Swagger UI won't show the documentation for the body when using `GET`, and proxies in the middle might not support it.

///

## Import Pydantic's `BaseModel` { #import-pydantics-basemodel }

First, you need to import `BaseModel` from `pydantic`:

{* ../../docs_src/body/tutorial001_py310.py hl[2] *}

## Create your data model { #create-your-data-model }

## Example Lambda handler

Install the necessary dependencies.
```sh
pip install flask requests
```

Following is an example lambda handler.
```py
from flask import Flask, request, abort, make_response
import requests

app = Flask(__name__)
@app.route('/', methods=['POST'])
def get_webhook():
	if request.method == 'POST':
		# obtain the request event from the 'POST' call
		event = request.json

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

import java.util.Arrays;

import org.codelibs.fess.unit.UnitFessTestCase;

public class FileTypeHelperTest extends UnitFessTestCase {

    private FileTypeHelper fileTypeHelper;

    @Override

 * Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
 */

package jcifs.dcerpc.ndr;

import java.util.HashMap;
import java.util.Map;

import jcifs.util.Encdec;
import jcifs.util.Strings;

/**
 * NDR (Network Data Representation) buffer for encoding and decoding DCE/RPC messages.

Standart Python'u typelarını belirterek yazıyorsun:

```Python
from typing import List, Dict
from datetime import date

from pydantic import BaseModel

# Değişkeni str olarak belirt
# ve o fonksiyon için harika bir editör desteği al
def main(user_id: str):
    return user_id


# Pydantic modeli

package schema

import (
	"reflect"
	"sync"
)

// sync pools
var (
	normalPool      sync.Map
	poolInitializer = func(reflectType reflect.Type) FieldNewValuePool {
		v, _ := normalPool.LoadOrStore(reflectType, &sync.Pool{
			New: func() interface{} {
				return reflect.New(reflectType).Interface()
			},
		})
		return v.(FieldNewValuePool)
	}

如果你需要 2 分鐘來學習如何使用 Python 型別（即使你不使用 FastAPI），可以看看這個簡短的教學：[Python 型別](python-types.md){.internal-link target=_blank}。

如果你寫帶有 Python 型別的程式碼：

```python
from datetime import date

from pydantic import BaseModel

# 宣告一個變數為 string
# 並在函式中獲得 editor support
def main(user_id: str):
    return user_id


# 宣告一個 Pydantic model
class User(BaseModel):
    id: int
    name: str