下面是optional的语法格式: python from typing import Optional, Union variable_name: Optional[Union[type1, type2, ..., None]] = default_value 其中,variable_name表示变量的名称,type1和type2表示变量可以接受的类型,None表示变量可以接受None作为值,default_value表示变量的默认值。optional类型注解放置在变量...
Union允许你指定变量、函数参数或返回值可以是多种类型中的一种 from typing import Union def process_data(data: Union[int, str]) -> None: if isinstance(data, int): print(f"Processing integer: {data}") elif isinstance(data, str): print(f"Processing string: {data}") # 使用示例 process_dat...
from typing import Optional, List, Type, Sequence, Dict, Union, Any, Callable from bottle import Response from fastapi import FastAPI, APIRouter, params, routing from fastapi.datastructures import Default from fastapi.routing import APIRoute from starlette.responses import JSONResponse from starlette.ro...
cuda.ipc_collect() #导入必要的库和模块: from fastapi import FastAPI, Request from pydantic import BaseModel from typing import Union, Optional, List import asyncio #创建 FastAPI 应用实例: app = FastAPI() #增加日志记录,方便调试和监控。 import logging logging.basicConfig(level=logging.INFO) #定义...
fromtypingimportOptional@dataclassclassA:x:stry:Optional[int]data={'x':'test', }result=from_dict(data_class=A,data=data)assertresult==A(x='test',y=None) Unions If your field can accept multiple types, you should useUnion. Dacite will try to match data with provided types one by one...
from typing import Dict, List, Optional, Union, Tuple, Iterable import numpy as np from PIL import Image import torch # Imagenet mean and std IMAGENET_STANDARD_MEAN = [0.5, 0.5, 0.5] IMAGENET_STANDARD_STD = [0.5, 0.5, 0.5] def resize( ...
from typing import List, Optional, Tuple, Union from llama_stack_client import LlamaStackClient from llama_stack_client.types import Attachment, ToolResponseMessage, UserMessage from llama_stack_client.types.agent_create_params import AgentConfig from .custom_tool import CustomTool class Agent: def ...
Union Optional 案例实战 参考链接: 写在篇前 typing 是python3.5中开始新增的专用于类型注解(type hints)的模块,为python程序提供静态类型检查,如下面的greeting函数规定了参数name的类型是str,返回值的类型也是str。 def greeting(name: str) -> str:
File "/home/rczheng/anaconda3/envs/alt-se/lib/python3.7/site-packages/pytorch_lightning/loops/batch/training_batch_loop.py", line 14, in <module> from typing import Any, List, Optional, OrderedDict, Tuple, Union imported fromtyping, nottyping_extensions. Python3.7.0does not include it. ...
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