《Designing Data-Intensive Application》DDIA 第一版 / 第二版 中文翻译
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🌸 Run LLMs at home, BitTorrent-style. Fine-tuning and inference up to 10x faster than offloading
《深入理解 AI Infra:量化分析与系统设计》(李博杰 著)开源书稿:从硬件约束和模型架构出发,量化推导 LLM 推理与训练系统设计。含全书正文、PDF、配套计算工具与实验
Python Stream Processing
Asynchronous Python framework for event-driven services. A thin client for Kafka, RabbitMQ, NATS, Redis and MQTT with full access to native broker features, plus AsyncAPI docs, in-memory tests and observability out of the box.
Python Stream Processing. A Faust fork
A library for event sourcing in Python.
Stream Processing Made Easy
Conflict-free merge for DataFrames, JSON, ML models & distributed agents — powered by CRDTs. The first merge library where every operation is mathematically guaranteed to converge.