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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 #156 · 09/06/2016, 01:43 AM

https://wiki.python.org/moin/GlobalInterpreterLock In #CPython, the #global#interpreter lock, or #GIL, is a mutex that prevents multiple native #threads from executing Python bytecodes at once. This lock is necessary mainly because CPython's memory management is not thread-safe. (However, since the GIL exists, other features have grown to depend on the guarantees that it enforces.)

djangoproject

@djangoproject · Post #159 · 09/12/2016, 05:37 PM

https://docs.python.org/3/library/atexit.html The #atexit module defines #functions to #register and #unregister cleanup functions. Functions thus registered are automatically executed upon normal interpreter termination. atexit runs these functions in the reverse order in which they were registered; if you register A, B, and C, at #interpreter#termination time they will be run in the order C, B, A.