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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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Inspiring Thoughts

@Inspiringthoughts · Post #10892 · 21.07.2025 г., 00:08

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At the tender age of seven, Pranjali Awasthi embarked on her coding journey under the guidance of her engineer father. This early exposure ignited a passion for technology that would shape her future. By thirteen, Pranjali was interning at Florida International University, delving into machine learning projects. These experiences highlighted the challenges researchers face in data extraction, inspiring her to seek innovative solutions. In January 2022, at just sixteen, she founded Delv.AI, an AI-powered platform designed to streamline data extraction for researchers. The startup quickly gained traction, securing approximately $450,000 in funding from notable investors. Within a year, Delv.AI achieved a valuation of around ₹100 crore (approximately $12 million), a testament to Pranjali’s vision and determination. Pranjali’s journey exemplifies the power of early passion, innovative thinking, and unwavering dedication. Her story serves as an inspiration to aspiring entrepreneurs worldwide. #YoungEntrepreneur#AIInnovation#WomenInTech#TechProdigy#StartupSuccess#Marketinggrowmatics

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Venture Village Wall 🦄

@venturevillagewall · Post #3601 · 20.12.2024 г., 16:16

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Weekend Reading for Entrepreneurs Explore this week's top news: 1️⃣ Research on mobile game success probability - Read more2️⃣ Tech trends for 2025 according to Andreessen Horowitz - Find out more3️⃣ Video on David Lieb, creator of Google Photos - Watch here4️⃣ Podcast with Vlad Tenev from Robinhood - Listen in5️⃣ David Kahn's AI predictions for 2025 - Read the article6️⃣ Interview with Rocket Lab CEO Peter Beck - Explore the interview7️⃣ Turning mistakes into success with Flamp.io - Learn how #MobileGames#TechTrends#GooglePhotos#Podcast#AI#RocketLab#StartupSuccess#Sequoia#AndreessenHorowitz#VladTenev#DavidLieb#DavidKahn#PeterBeck#Flamp#YCombinator#SpaceX#Entrepreneurship#Innovation#Research#Investment#Finance