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This article explains how to use JoyCode together with the custom i18n-mcp tool to automatically extract, translate, and replace hard‑coded Chinese strings in Vue/JS/TS projects, dramatically reducing i18n migration effort from weeks to just a few hours.
This guide explains why local packet captures can be impractical for real‑time analysis, then walks through installing rpcapd, configuring network requirements, launching the remote capture service, and setting up Wireshark to capture traffic from a distant machine.
Uni-Layout introduces a unified framework that combines a multimodal large language model‑based generator, a human‑like evaluator trained on the large Layout‑HF100k dataset, and a Dynamic Margin Preference Optimization (DMPO) method to align generation and evaluation, achieving state‑of‑the‑art results across diverse layout tasks.
This guide explains why Playwright is essential for modern front‑end testing, walks through installation, project setup, core APIs for GET/POST requests, and provides a runnable demo to help developers quickly adopt automated testing in their web projects.
This article explains Apache Hudi’s core architecture, detailing the timeline mechanism, file layout, indexing strategies, the two main table types (Copy‑On‑Write and Merge‑On‑Read), and various query modes such as snapshot, time‑travel, read‑optimized and incremental queries.
This article explains how unreliable networks, clock instability, and node failures can cause data inconsistency in distributed clusters, introduces the Raft consensus algorithm, details its roles, election process, log replication, read/write handling, consistency models, and mechanisms to avoid split-brain and livelock.
The article details DongSQL’s kernel redesign—including RETURNING clause, Hint syntax, CCL concurrency control, statement outlines, and thread‑pool optimizations—showing concrete performance gains in high‑concurrency e‑commerce scenarios.
The 2025 Open Atom Developer Conference highlighted JD's JoyAgent project, an open‑source, 100% enterprise‑grade multi‑agent platform that excels in AI, data governance, and diagnostic analysis, with detailed features, performance metrics, and deployment experiences shared.
This article explains how different chunking methods—fixed size, semantic, recursive, document‑based, agent‑driven, sentence‑level, and paragraph‑level—affect Retrieval‑Augmented Generation, offering practical guidelines, metrics, and optimization tips for real‑world deployments.
This article explains the concept of heterogeneous treatment effects (HTE), clarifies related terminology, outlines why HTE analysis matters for product decisions, and walks through dimension selection, statistical and machine‑learning methods—including ANOVA, causal trees, meta‑learners, and double‑machine‑learning—plus a practical MVP tool with code examples and future development directions.
