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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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@CryptoM · Post #65334 · 13.04.2026 г., 00:14

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🚀 PRECIOUS METALS | Global Central Bank Gold Purchases Show Resilience, Citic Securities Reports Citic Securities has released a report indicating that the global trend of central banks purchasing gold remains structurally resilient. According to Jin10, the market may be overestimating the driving forces and impact mechanisms behind this trend. The report outlines several key points: 1) The proportion of non-standard channels and domestic storage in gold purchases is rising, reflecting the strengthened attribute of gold as a 'sovereign safe asset.' 2) The current wave of gold buying goes beyond conventional reserve management and should not be directly equated with de-dollarization. The primary logic for central banks holding gold remains crisis hedging and reserve diversification. 3) Recent disturbances, such as temporary reductions by central banks in Turkey and Russia due to fiscal pressures, are tactical and do not alter the global net buying pattern. 4) Central bank gold purchases are a long-term force elevating the gold price center, but their behavior of buying on dips means they play more of a supporting role. Variables like real interest rates have a more significant impact on gold prices. 5) The gap in gold reserve proportions between emerging market central banks and developed countries is substantial, indicating that the current cycle of central bank gold purchases is far from over. Citic Securities is optimistic about medium to long-term allocation opportunities but advises monitoring signals of weakened correlation between gold and risk assets in the short term as a key entry point for buying on dips. #PreciousMetals#Gold#CentralBank#GoldPurchases#SafeAsset#ReserveDiversification#EmergingMarkets#GoldPrice#Investment#FinancialMarkets

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