n = copy(p, r.data)
	r.eof = true
	return n, nil
}

// Wrapper for calling testMakeBucket for both Erasure and FS.
func TestMakeBucket(t *testing.T) {
	ExecObjectLayerTest(t, testMakeBucket)
}

// Tests validate bucket creation.
func testMakeBucket(obj ObjectLayer, instanceType string, t TestErrHandler) {
	err := obj.MakeBucket(context.Background(), "bucket-unknown", MakeBucketOptions{})
	if err != nil {

	if apiErr != noError {
		writeErrorResponse(ctx, w, apiErr, r.URL)
		return
	}
	// Validate the received bucket replication config
	if err = replicationConfig.Validate(bucket, sameTarget); err != nil {
		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}
	configData, err := xml.Marshal(replicationConfig)
	if err != nil {

	if s3Error := checkRequestAuthType(ctx, r, policy.PutBucketPolicyAction, bucket, ""); s3Error != ErrNone {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(s3Error), r.URL)
		return
	}

	// Before proceeding validate if bucket exists.
	_, err := objAPI.GetBucketInfo(ctx, bucket, BucketOptions{})
	if err != nil {
		writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
		return
	}

	aclHeader := r.Header.Get(xhttp.AmzACL)

	}

	data := r.Reader
	// Validate input data size and it can never be less than zero.
	if data.Size() < -1 {
		bugLogIf(ctx, errInvalidArgument, logger.ErrorKind)
		return pi, toObjectErr(errInvalidArgument)
	}

	uploadIDPath := er.getUploadIDDir(bucket, object, uploadID)
	// Validates if upload ID exists.
	fi, _, err := er.checkUploadIDExists(ctx, bucket, object, uploadID, true)

# OpenAPI `models`

OpenAPI Pydantic models used to generate and validate the generated OpenAPI.

# Body - Nested Models { #body-nested-models }

With **FastAPI**, you can define, validate, document, and use arbitrarily deeply nested models (thanks to Pydantic).

## List fields { #list-fields }

You can define an attribute to be a subtype. For example, a Python `list`:

{* ../../docs_src/body_nested_models/tutorial001_py310.py hl[12] *}

This will make `tags` be a list, although it doesn't declare the type of the elements of the list.

* Validate **các cấu trúc phức tạp**:
    * Sử dụng các models Pydantic phân tầng, `List` và `Dict` của Python `typing`,...
    * Và các validators cho phép các cấu trúc dữ liệu phức tạp trở nên rõ ràng và dễ dàng để định nghĩa, kiểm tra và tài liệu hóa thành JSON Schema.
    * Bạn có thể có các object **JSON lồng nhau** và tất cả chúng đã validate và annotated.
* **Có khả năng mở rộng**:

package cmd

import (
	"context"
	"net/http"
	"strconv"
	"strings"

	"github.com/minio/minio/internal/logger"
	"github.com/minio/mux"

	"github.com/minio/pkg/v3/policy"
)

// Validate all the ListObjects query arguments, returns an APIErrorCode
// if one of the args do not meet the required conditions.
// Special conditions required by MinIO server are as below

	"github.com/minio/minio/internal/event"
	"github.com/minio/minio/internal/hash"
	xhttp "github.com/minio/minio/internal/http"
)

var etagRegex = regexp.MustCompile("\"*?([^\"]*?)\"*?$")

// Validates the preconditions for CopyObjectPart, returns true if CopyObjectPart
// operation should not proceed. Preconditions supported are:
//
//	x-amz-copy-source-if-modified-since
//	x-amz-copy-source-if-unmodified-since

        "price": 42.0,
        "tax": 3.2
    },
    "user": {
        "username": "dave",
        "full_name": "Dave Grohl"
    },
    "importance": 5
}
```

Again, it will convert the data types, validate, document, etc.

## Multiple body params and query { #multiple-body-params-and-query }

Of course, you can also declare additional query parameters whenever you need, additional to any body parameters.