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Source channel @olddriverGDstudy · Post #12 · Mar 17

#语录 【关于cj中的曲线救国】 一定要好好对待每一段男女关系 要相信 一切都是最好的安排 我们要感恩生活中每一次不期而遇的温暖 做不成男女朋友 那就是要做炮友 渣男怎么了 渣男也有爱 虽然我们爱的比较短暂 直接 毕竟我是职业打针选手 有时候 要善于把痛点转化成卖点 dym来了又怎样 虽然不至于浴血奋战 但是可以曲线救国

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djangoproject

@djangoproject · Post #228 · 01/16/2017, 01:11 PM

http://www.aparat.com/v/miNUS pycon 2016- Andrew Godwin - Reinventing Django for the #Real_Time Web Django has long been tied to the #request_response pattern, but the upcoming "#channels" project changes this and allows #Django to natively support #WebSockets, running tasks after responses, easily handle #long_polling and more. Come and learn about the design, how we're trying to keep things as Django-like as possible, and how you can use it in your projects.

GitHub Trends

@githubtrending · Post #14989 · 07/23/2025, 11:30 AM

#c_lang#bluetooth#bluetooth_le#embedded#embedded_c#iot#mcu#microcontroller#real_time#rtos#zephyr#zephyr_rtos#zephyros Zephyr is a free, open-source real-time operating system (RTOS) designed for small, resource-limited devices like sensors, wearables, and IoT gateways. It supports many hardware types such as ARM, Intel x86, and RISC-V, making it flexible for different projects. Zephyr is modular, so you can include only what you need, saving memory and power. It focuses on security with features like memory protection and secure boot. It also offers built-in networking and tools for easy development and testing. This helps you build reliable, fast, and secure embedded systems efficiently, especially for IoT and real-time applications[1][2][3]. https://github.com/zephyrproject-rtos/zephyr

GitHub Trends

@githubtrending · Post #15350 · 12/21/2025, 11:30 AM

#rust#ai#change_data_capture#context_engineering#data#data_engineering#data_indexing#data_infrastructure#data_processing#etl#hacktoberfest#help_wanted#indexing#knowledge_graph#llm#pipeline#python#rag#real_time#rust#semantic_search **CocoIndex** is a fast, open-source Python tool (Rust core) for transforming data into AI formats like vector indexes or knowledge graphs. Define simple data flows in ~100 lines of code using plug-and-play blocks for sources, embeddings, and targets—install via `pip install cocoindex`, add Postgres, and run. It auto-syncs fresh data with minimal recompute on changes, tracking lineage. **You save time building scalable RAG/semantic search pipelines effortlessly, avoiding complex ETL and stale data issues for production-ready AI apps.** https://github.com/cocoindex-io/cocoindex