final String roleField = fessConfig.getIndexFieldRole();
        roleSet.stream().forEach(name -> roleQuery.should(QueryBuilders.termQuery(roleField, name)));
        final String deniedPrefix = fessConfig.getRoleSearchDeniedPrefix();
        roleSet.stream().forEach(name -> roleQuery.mustNot(QueryBuilders.termQuery(roleField, deniedPrefix + name)));
        boolQuery.filter(roleQuery);
    }

    /**

	buckets = append(buckets, BucketInfo{
		Name: pathJoin(minioMetaBucket, minioConfigPrefix),
	}, BucketInfo{
		Name: pathJoin(minioMetaBucket, bucketMetaPrefix),
	})

	// Heal latest buckets first.
	sort.Slice(buckets, func(i, j int) bool {
		a, b := strings.HasPrefix(buckets[i].Name, minioMetaBucket), strings.HasPrefix(buckets[j].Name, minioMetaBucket)
		if a != b {
			return a
		}

	}
	for _, tt := range tests {
		if got := isXLMetaFormatValid(tt.version, tt.format); got != tt.want {
			t.Errorf("Test %d: Expected %v but received %v", tt.name, got, tt.want)
		}
	}
}

func TestIsXLMetaErasureInfoValid(t *testing.T) {
	tests := []struct {
		name   int
		data   int
		parity int
		want   bool
	}{
		{1, 5, 6, false},
		{2, 5, 5, true},
		{3, 0, 5, false},
		{3, -1, 5, false},

        CloseableUtil.closeQuietly(in);

        final String content = extractData.getContent();
        logger.info(content);

        // Verify header extraction
        assertTrue(content.contains("Name"));
        assertTrue(content.contains("Email"));
        assertTrue(content.contains("Age"));
        assertTrue(content.contains("Department"));

        // Verify data extraction

        // Assert
        assertEquals(2283323396289696982L, value, "serialVersionUID should be stable");
    }

    // Behavior check: toString contains class name and message when present
    @Test
    @DisplayName("toString contains class name and message when provided")
    void toString_containsClassName_and_Message() {
        // Arrange
        String msg = "signature invalid";

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


app = FastAPI()


@app.post("/items/")
async def create_item(item: Item):
    item_dict = item.model_dump()
    if item.tax is not None:
        price_with_tax = item.price + item.tax
        item_dict.update({"price_with_tax": price_with_tax})

from fastapi import FastAPI
from pydantic import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


app = FastAPI()


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Item, q: str | None = None):
    result = {"item_id": item_id, **item.model_dump()}
    if q:
        result.update({"q": q})

from typing import Annotated

from fastapi import Body, FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    description: str | None = None
    price: float
    tax: float | None = None


@app.put("/items/{item_id}")
async def update_item(item_id: int, item: Annotated[Item, Body(embed=True)]):
    results = {"item_id": item_id, "item": item}

from pydantic.v1 import BaseModel


class Item(BaseModel):
    name: str
    description: str | None = None

# This is the official list of TensorFlow authors for copyright purposes.
# This file is distinct from the CONTRIBUTORS files.
# See the latter for an explanation.

# Names should be added to this file as:
# Name or Organization <email address>
# The email address is not required for organizations.

Google Inc.
Yuan Tang <******@****.***>