TGINSIGHT SIMILAR POSTS
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
Пребарај: #ern
@proanalysistrader · Post #28509 · 02.03.2025 г., 04:21
#ERN/USDT analysis : #ERN is currently in an uptrend, trading above the 200 Exponential Moving Average (EMA). The price has recently bounced back and broken out above the trendline, suggesting a potential continuation of the uptrend. The price is anticipated to move upside and test the swing high level. TF : 30min Entry : $1.704 Target : $1.992 SL : $1.620
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@proanalysistrader · Post #28398 · 18.01.2025 г., 18:12
#ERN/USDT analysis : #ERN is currently in a bearish trend, characterized by a series of lower lows (LLs) and lower highs (LHs) while adhering to the trendline. The price is anticipated to continue this direction, testing lower levels in the near future. TF : 1D Entry : $2.230 Target : $1.610 SL : $2.608
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@proanalysistrader · Post #27973 · 29.09.2024 г., 16:30
#ERN/USDT analysis : #ERN has broken out above the 200 EMA and is currently consolidating above it. The price is expected to sustain its bullish momentum and is likely to continue its upward trajectory. TF : 4h Entry : $2.277 Target : $2.554 SL : $2.088
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@coinlegs · Post #9334 · 08.11.2023 г., 07:15
I found an altcoin which is close to All-Time-Low (1 year) #ERN added a small amount of it to my bag, DYOR
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@coinlegs · Post #10123 · 21.03.2024 г., 10:15
🐬DOLPHIN | AI PREDICTIONS 21.03.2024 10:00 GMT Expected 5% Profit/Loss in 24 Hours #POLYX | 0.4088 | PP: 50% | LP: 94% #PHA | 0.329 | PP: 50% | LP: 95% #ERN | 7.537 | PP: 50% | LP: 96% #LTO | 0.1761 | PP: 50% | LP: 97% #FTM | 1.0574 | PP: 46% | LP: 91% #REI | 0.10968 | PP: 46% | LP: 93% #OM | 0.64366 | PP: 45% | LP: 96% #SSV | 56.36 | PP: 44% | LP: 92% #CFX | 0.434 | PP: 44% | LP: 98% #STX | 3.3721 | PP: 43% | LP: 96% #PAXG | 2183 | PP: 43% | LP: 97% #CYBER | 13.737 | PP: 43% | LP: 98% #FLOKI | 0.00024944 | PP: 42% | LP: 99% #RSR | 0.006467 | PP: 41% | LP: 98% #DUSK | 0.4065 | PP: 40% | LP: 98% #FET | 2.6868 | PP: 40% | LP: 98% #BNB | 559.5 | PP: 40% | LP: 99% #DEXE | 10.712 | PP: 39% | LP: 97% #TRU | 0.09719 | PP: 39% | LP: 97% #OCEAN | 1.2 | PP: 39% | LP: 98% #SOL | 187.61 | PP: 39% | LP: 99% #IQ | 0.014558 | PP: 38% | LP: 95% #MKR | 3058 | PP: 38% | LP: 99% #PEPE | 0.00000823 | PP: 38% | LP: 99% #OOKI | 0.003513 | PP: 36% | LP: 99% #HIFI | 1.0967 | PP: 35% | LP: 97% #APT | 15.292 | PP: 35% | LP: 99% #CLV | 0.12307 | PP: 35% | LP: 99% #UTK | 0.13 | PP: 34% | LP: 96% #AMP | 0.010762 | PP: 34% | LP: 99% #DEGO | 3.603 | PP: 33% | LP: 99% #FORTH | 6.283 | PP: 33% | LP: 99% #NULS | 0.4503 | PP: 33% | LP: 99% #TKO | 0.6404 | PP: 33% | LP: 99% #FIS | 0.7002 | PP: 33% | LP: 100% #SANTOS | 7.64 | PP: 32% | LP: 94% #WBTC | 66789.15 | PP: 32% | LP: 99% #JASMY | 0.020469 | PP: 31% | LP: 98% #BCH | 432.2 | PP: 31% | LP: 99% #BTC | 66843.96 | PP: 31% | LP: 100% #SUN | 0.015141 | PP: 30% | LP: 94% #CKB | 0.020456 | PP: 30% | LP: 99% #RAY | 2.2809 | PP: 30% | LP: 99% #POND | 0.03243 | PP: 29% | LP: 90% #CREAM | 23.08 | PP: 29% | LP: 99% #FOR | 0.03258 | PP: 29% | LP: 99% #NEXO | 1.359 | PP: 29% | LP: 99% #UFT | 0.638 | PP: 29% | LP: 99% #FLUX | 1.4129 | PP: 29% | LP: 100% #ACA | 0.1858 | PP: 28% | LP: 99% ... ——————————————————————— Total Predictions: 371 PP > 50%: 4 LP > 50%: 365 PP > 60%: 0 LP > 60%: 362 PP > 70%: 0 LP > 70%: 347 PP > 80%: 0 LP > 80%: 331 PP > 90%: 0 LP > 90%: 316 ——————————————————————— PP: Profit Probability | LP: Loss Probability