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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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#pydantic #libs

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Libreware

@libreware · Post #1581 · 24.04.2026 г., 14:58

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Scooter Knowledge Base https://github.com/firebl0od/Scooter_Knowledge/tree/main This repository collects and organizes information about electric scooter setup, maintenance, and troubleshooting. The primary source material is a large Telegram conversation exported from the "VESC help" group https://t.me/VescHelpGroup. The goal of the project is to extract practical knowledge from the chat logs and document it in a structured, reusable format. VESC is short for Vedder Electronic Speed Controller. It is an open-source, open-hardware motor speed controller that allows for advanced customization via software (such as the VESC Tool app). It is commonly used in electric scooters, skateboards, electric bicycles, and robotics projects to provide precise control, regenerative braking, and sensorless operation, overcoming the limitations of standard closed controllers. The knowledge/processed/themes/ directory contains 72 professionally formatted documents covering: 28 brand dossiers covering controllers, motors, and BMS systems from manufacturers like Spintend, Flipsky, Makerbase, 3Shul, and more 44 comprehensive guides including: VESC tuning and parameter optimization Battery pack design and BMS integration Motor cooling and thermal management Conversion guides for popular scooter models (Ninebot, Xiaomi, etc.) Brake upgrades and maintenance Field weakening and high-voltage setups Diagnostic tools and troubleshooting All documents use a consistent, readable format with: Clean footnote citations linking back to source material Well-organized sections with proper headings Tables and checklists for quick reference Preserved technical accuracy from the original discussions #electric#scooter#bike#controllers#vesc#batteries#diy

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#electric #scooter #bike #controllers #vesc #batteries #diy