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Изворен канал @pythonotes · Post #397 · 12 ное.

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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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@githubtrending · Post #14942 · 10.07.2025 г., 13:30

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#go#chart#charts#cncf#helm#kubernetes Helm is a tool that helps manage applications on Kubernetes. It simplifies deploying and managing apps by using pre-configured packages called Helm Charts. These charts include all the necessary resources for an application, making it easy to install, update, or remove apps with just a few commands. This saves time and reduces errors, as you only need to edit a single file to change settings across different environments. Using Helm boosts productivity and makes deploying complex applications much easier. https://github.com/helm/helm

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#go#chart#charts#cncf#helm#kubernetes
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@githubtrending · Post #14809 · 08.06.2025 г., 13:30

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#ruby#beginners#hacktoberfest#hacktoberfest2020#helm#kubernetes#kubetools Kubernetes is a powerful tool for managing containerized applications. To learn Kubernetes, you can use platforms like Kubelabs, which offer interactive tutorials and labs. These resources help you understand Kubernetes concepts from the basics to advanced levels. By using these platforms, you can practice deploying applications, managing resources, and ensuring high availability and scalability. This hands-on approach helps you gain practical experience and improve your skills in managing complex applications efficiently. https://github.com/collabnix/kubelabs

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#ruby#beginners#hacktoberfest#hacktoberfest2020#helm#kubernetes#kubetools
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@githubtrending · Post #15595 · 01.04.2026 г., 11:30

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#go#distribution_spec#helm#kubernetes#oci#oci_distribution#opencontainers#zot Zot is a lightweight, production-ready OCI-native container registry for storing images, Helm charts, SBOMs, and other artifacts without vendor lock-in. It offers built-in authentication (OIDC, LDAP), storage options (S3, Azure), scanning, caching to cut Docker Hub limits/latency, and ARM/edge support as a single binary. You benefit by easily self-hosting a secure, scalable alternative to Docker Hub, saving costs, boosting speed, and enabling secret-less workflows on any device. https://github.com/project-zot/zot

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#go#distribution_spec#helm#kubernetes#oci#oci_distribution#opencontainers#zot