Xiaoxia AI
103 lines
2.5 KiB
Python
103 lines
2.5 KiB
Python
"""
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通用分页器
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"""
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from math import ceil
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from typing import Generic, List, Optional, TypeVar
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from pydantic import BaseModel, Field
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T = TypeVar("T")
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class PaginationParams(BaseModel):
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"""分页参数"""
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page: int = Field(1, ge=1, description="页码（从 1 开始）")
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page_size: int = Field(20, ge=1, le=100, description="每页数量（最大 100）")
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@property
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def offset(self) -> int:
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"""计算偏移量"""
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return (self.page - 1) * self.page_size
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@property
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def limit(self) -> int:
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"""返回限制数量"""
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return self.page_size
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class PaginationMeta(BaseModel):
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"""分页元数据"""
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page: int = Field(..., description="当前页码")
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page_size: int = Field(..., description="每页数量")
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total: int = Field(..., description="总记录数")
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total_pages: int = Field(..., description="总页数")
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has_next: bool = Field(..., description="是否有下一页")
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has_prev: bool = Field(..., description="是否有上一页")
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@classmethod
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def from_params(
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cls,
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params: PaginationParams,
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total: int,
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) -> "PaginationMeta":
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"""从参数和总数创建元数据"""
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total_pages = ceil(total / params.page_size) if total > 0 else 0
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return cls(
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page=params.page,
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page_size=params.page_size,
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total=total,
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total_pages=total_pages,
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has_next=params.page < total_pages,
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has_prev=params.page > 1,
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)
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class PaginatedResponse(BaseModel, Generic[T]):
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"""分页响应"""
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data: List[T] = Field(..., description="数据列表")
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pagination: PaginationMeta = Field(..., description="分页信息")
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@classmethod
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def create(
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cls,
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data: List[T],
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params: PaginationParams,
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total: int,
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) -> "PaginatedResponse[T]":
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"""创建分页响应"""
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return cls(
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data=data,
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pagination=PaginationMeta.from_params(params, total),
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)
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def paginate(
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items: List[T],
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params: PaginationParams,
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) -> PaginatedResponse[T]:
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"""
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内存分页（适用于 InMemory Repository）
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Args:
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items: 完整列表
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params: 分页参数
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Returns:
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分页响应
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"""
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total = len(items)
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start = params.offset
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end = start + params.limit
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page_data = items[start:end]
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return PaginatedResponse.create(
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data=page_data,
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params=params,
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total=total,
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)
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