john
1aaef71f52
Document-driven MVP with FastAPI backend, Vue H5, WeChat mini shell, product demo, and Docker dev stack. Co-authored-by: Cursor <cursoragent@cursor.com>
44 lines
1.3 KiB
Python
44 lines
1.3 KiB
Python
from datetime import datetime, timezone
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from typing import Any
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from uuid import uuid4
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from pydantic import BaseModel, Field
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class ApiMeta(BaseModel):
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request_id: str = Field(alias="requestId")
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timestamp: str
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trace_id: str | None = Field(default=None, alias="traceId")
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model_config = {"populate_by_name": True}
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class StandardResponse(BaseModel):
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code: int = 0
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message: str = "ok"
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data: Any | None = None
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meta: ApiMeta
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model_config = {"populate_by_name": True}
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def build_meta(request_id: str | None = None) -> ApiMeta:
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return ApiMeta(
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requestId=request_id or uuid4().hex,
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timestamp=datetime.now(timezone.utc).isoformat(),
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traceId=uuid4().hex[:16],
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)
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def ok(data: Any = None, message: str = "ok", request_id: str | None = None) -> dict[str, Any]:
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return StandardResponse(code=0, message=message, data=data, meta=build_meta(request_id)).model_dump(
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by_alias=True
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)
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def error(code: int, message: str, request_id: str | None = None, **details: Any) -> dict[str, Any]:
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payload = {"errorCode": message, **details} if details else {"errorCode": message}
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return StandardResponse(code=code, message=message, data=payload, meta=build_meta(request_id)).model_dump(
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by_alias=True
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)
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