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Изворен канал @pythonotes · Post #397 · 12 ное.

Использование Pydantic сегодня стало нормой, и это правильно. Но иногда на ревью вижу, что используют его не всегда корректно. Например, метод BaseModel.model_dump() по умолчанию не преобразует стандартные типы, такие как datetime, UUID или Decimal, в простой сериализуемый для JSON вид. Тогда пишут кастмоный сериализатор для этих типов чтобы функция json.dump() не падала с ошибкой. import uuid from datetime import datetime from decimal import Decimal from uuid import UUID from pydantic import BaseModel class MyModel(BaseModel): id: UUID date: datetime value: Decimal obj = MyModel( id=uuid.uuid4(), date=datetime.now(), value='1.23' ) print(obj.model_dump()) # не подходит для json.dump # { # 'id': UUID('4f8c1bc4-25fd-40cd-9dbe-2c73639b0dc1'), # 'date': datetime.datetime(2025, 12, 12, 12, 12, 12, 111111), # 'value': Decimal('1.23') # } # добавляем свой кастомный сериализатор json.dumps(obj.model_dump(), cls=MySerializer) # { # 'id': '4f8c1bc4-25fd-40cd-9dbe-2c73639b0dc1', # 'date': '2025-12-12T12:12:12.111111', # 'value': '1.23' # } В данном случае класс MySerializer обрабатывает datetime, UUID и Decimal. Например так: class MySerializer(json.JSONEncoder): def default(self, o): if isinstance(o, Decimal): return str(o) elif isinstance(o, datetime): return o.isoformat() elif isinstance(o, UUID): return str(o) return super().default(o) Специально для тех, кто всё еще так делает - в этом нет необходимости! Pydantic может это сделать сам, просто нужно добавить параметр mode="json". json.dumps(obj.model_dump(mode="json")) # { # 'id': '4f8c1bc4-25fd-40cd-9dbe-2c73639b0dc1', # 'date': '2012-12-12T12:12:12.111111', # 'value': '1.23' # } #pydantic#libs

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AI & Law

@ai_and_law · Post #522 · 10.03.2025 г., 08:04

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❗️Turing Award Winners Sound the Alarm on AI Safety Andrew Barto and Richard Sutton, pioneers of foundational AI training method and recipients of this year’s Turing Award, are using their moment in the spotlight to issue a stark warning: AI companies are prioritizing profit over safety. Comparing the current approach to “building a bridge and testing it by having people use it,” they criticize the industry for rushing AI models to market without sufficient safeguards. Their concerns echo those of other leading AI researchers, including past Turing Award winners Geoffrey Hinton and Yoshua Bengio, who have also warned about the risks of unchecked AI development. With OpenAI shifting toward a for-profit model and major AI firms racing to deploy new technologies, the debate over responsible AI governance is more urgent than ever. #AI#AIGovernance#TuringAward#AISafety#ResponsibleAI

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Venture Village Wall 🦄

@venturevillagewall · Post #4349 · 09.03.2025 г., 22:00

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Weekly AI Digest: Key Developments 🔹 Anthropic raises $3.5B through incremental funding rounds. Read more 🔹 QwQ 32B launched, slightly trailing top performers. Details here 🔹 Wan 2.1 remains a top open-source model amid competition. Learn more 🔹 Hunyuan Image2Video: Tencent's response to Alibaba's offering. Explore here 🔹 SourceCraft introduces cloud-based team development as VM replacement. More info 🔹 Apple's Mac Studio handles demanding models and LLMs. Discover more 🔹 SpeechSense analyzes customer conversations using LLM technology. Details 🔹 RL wins Turing Award, recognized with a $1M prize. Full story 🔹 Bitcoin drops to $82,223; Ethereum to $1,998, with $243M in liquidations. Read market update. #AI#Crypto#VC#Anthropic#Bitcoin#Ethereum#Hunyuan#Tencent#AIModels#OpenSource#MacStudio#SpeechSense#Investments#Funding#TuringAward#Liquidations#QwQ#SourceCraft#SmartTech

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#ai #crypto #vc #anthropic #bitcoin #ethereum #hunyuan #tencent #aimodels #opensource #macstudio #speechsense #investments #funding #turingaward #liquidations #qwq #sourcecraft #smarttech