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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 #82 · 13.08.2023 г., 09:41

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🌟AI Sunday Wonders: Revolutionizing Breast Cancer Screening Hello AI enthusiasts! In our latest AI Sunday Wonders, we dive into groundbreaking research from Lund University, Sweden. The study suggests that artificial intelligence shows immense promise in breast cancer screening. Researchers led by Lund University explored AI's potential to safely read breast cancer screening images. Their findings indicate that AI-assisted detection can identify cancer at a similar rate to human radiologists. This offers a significant advancement in early diagnosis. Unlike previous studies, this research directly compared AI-supported screening with standard care. Over 80,000 women participated in the trial, with half of them undergoing AI-assisted screening. The results revealed that AI detected more cases of cancer without increasing false positives. Dr. Kristina Lang, the lead author, highlighted AI's potential to alleviate the shortage of radiologists worldwide. While AI-supported screening still requires a radiologist's oversight, it could streamline the reading process and expedite patient care. The NHS and the Royal College of Radiologists both expressed optimism about integrating AI into breast cancer screening. This promising technology could enhance efficiency, aid decision-making, and prioritize urgent cases, especially in light of the radiologist shortage. #AISundayWonders#MedicalAI#BreastCancerScreening#AIInHealthcare

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Venture Village Wall 🦄

@venturevillagewall · Post #3344 · 18.12.2024 г., 12:06

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Helpcare AI Secures $500K Funding Helpcare AI has successfully raised $500K in funding as of December 4, 2024. The company offers a complete operating system for HIPAA-compliant AI-driven automation in healthcare administration, enhancing efficiency in healthcare management. For more details, visit Helpcare AI. #HelpcareAI#Funding#Healthcare#AI#Automation#HIPAA#Technology#HealthcareManagement#Efficiency#Startup#Investment #2024 #Innovation#MedicalAI#Admin#System#Operations#Compliance#HealthTech

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