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Source channel @githubtrending · Post #14693 · May 10

#jupyter_notebook#a2a#agentic_ai#dapr#dapr_pub_sub#dapr_service_invocation#dapr_sidecar#dapr_workflow#docker#kafka#kubernetes#langmem#mcp#openai#openai_agents_sdk#openai_api#postgresql_database#rabbitmq#rancher_desktop#redis#serverless_containers The Dapr Agentic Cloud Ascent (DACA) design pattern helps you build powerful, scalable AI systems that can handle millions of AI agents working together without crashing. It uses Dapr technology with Kubernetes to efficiently manage many AI agents as lightweight virtual actors, ensuring fast response, reliability, and easy scaling. You can start small using free or low-cost cloud tools and grow to planet-scale systems. The OpenAI Agents SDK is recommended for beginners because it is simple, flexible, and gives you good control to develop AI agents quickly. This approach saves costs, avoids vendor lock-in, and supports resilient, event-driven AI workflows, making it ideal for developers aiming to create advanced, cloud-native AI applications[1][2][3][4]. https://github.com/panaversity/learn-agentic-ai

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djangoproject

@djangoproject · Post #538 · 12/28/2017, 10:33 AM

https://pendulum.eustace.io/docs/ Python datetimes made easy. Supports Python 2.7+, 3.4+ and PyPy. Native #datetime instances are enough for basic cases but when you face more complex use-cases they often show limitations and are not so intuitive to work with. #Pendulum provides a cleaner and more easy to use API while still relying on the standard library. So it's still datetime but better.

djangoproject

@djangoproject · Post #186 · 10/14/2016, 03:57 AM

http://www.saltycrane.com/blog/2008/06/how-to-get-current-date-and-time-in/ Here is an example of how to get the current #date and #time using the #datetime module in Python: