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Adrian Rason 的 KDP 数据

Adrian Rason 在 Amazon 有 13 本书,近 30 天有 13 本上过榜,最好排名 #8,主要在Software Design, Testing & Engineering、Software Development、Testing。

13Amazon 上的书
13近 30 天上榜书
3.2平均评分
价格中位数$12.99
价格区间(中间 50%)$12.94 – $12.99
评论中位数1
评论总数7
近 30 天新书8
近 30 天突围新书5

数据解读

  • 近 30 天 100% 的书上过榜,整个书目都在卖,不靠单本。
  • 定价中位 $12.99,比主类目「Software Design, Testing & Engineering」的中位价高 30%。
  • 近 30 天新上 8 本,其中 5 本冲进了畅销榜。

Adrian Rason 排名最好的书

  1. 《OPENAI CODEX: Build, Test, Refactor, Review, and Ship Production-Ready Software with Codex》封面,作者 Adrian Rason

    OPENAI CODEX: Build, Test, Refactor, Review, and Ship Production-Ready Software with Codex CLI, Cloud Agents, GitHub, and Automated Developer Workflows (The OpenAI Codex Engineering Series)

    作者 Adrian Rason

    • 价格$39.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  2. 《HERMES AGENT IN PRODUCTION: Self-Host, Secure, Deploy, and Operate Always-On AI Assistants》封面,作者 Adrian Rason

    HERMES AGENT IN PRODUCTION: Self-Host, Secure, Deploy, and Operate Always-On AI Assistants (Hermes Agent Engineering Series)

    作者 Adrian Rason

    • 价格$12.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  3. 《Hermes Agent for Private AI: Build Secure, Self-Hosted AI Assistants with Local Models, Pe》封面,作者 Adrian Rason

    Hermes Agent for Private AI: Build Secure, Self-Hosted AI Assistants with Local Models, Persistent Memory, Private RAG, MCP Tools, and Privacy-First Automation (Hermes Agent Engineering Series)

    作者 Adrian Rason

    • 价格$12.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  4. 《GitHub Copilot for DevOps and Platform Engineering: Build AI-Powered CI/CD Pipelines, Auto》封面,作者 Adrian Rason

    GitHub Copilot for DevOps and Platform Engineering: Build AI-Powered CI/CD Pipelines, Automate Infrastructure as Code, Deploy Kubernetes, and Secure Cloud Workflows with GitHub Actions

    作者 Adrian Rason

    • 价格$12.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  5. 《OpenAI Codex Multi-Agent Engineering: Build and Orchestrate Parallel AI Coding Teams with 》封面,作者 Adrian Rason

    OpenAI Codex Multi-Agent Engineering: Build and Orchestrate Parallel AI Coding Teams with Codex, Worktrees, Skills, MCP, GitHub, and Agentic Workflows (The OpenAI Codex Engineering Series)

    作者 Adrian Rason

    • 价格$12.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  6. 《OpenAI Codex Projects Handbook : Build Real-World Agentic Coding Workflows, Developer Tool》封面,作者 Adrian Rason

    OpenAI Codex Projects Handbook : Build Real-World Agentic Coding Workflows, Developer Tools, and Intelligent Apps Step by Step (The OpenAI Codex Engineering Series)

    作者 Adrian Rason

    • 价格$9.99
    • 评分4.7
    • 评论5
    • 出版2026-06

    亚马逊页面 · KDPTop 完整数据

  7. 《SQL Server 2025: Diagnose Slow Queries, Master Execution Plans, Design Better Indexes, Opt》封面,作者 Adrian Rason

    SQL Server 2025: Diagnose Slow Queries, Master Execution Plans, Design Better Indexes, Optimize T-SQL, Resolve Blocking and Deadlocks, and Build Fast, Reliable Databases

    作者 Adrian Rason

    • 价格$12.88
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  8. 《Spec-Driven Software Development with AI: Build Production-Ready Software with Requirement》封面,作者 Adrian Rason

    Spec-Driven Software Development with AI: Build Production-Ready Software with Requirements, Specs, Tests, and AI Coding Agents (The OpenAI Codex Engineering Series)

    作者 Adrian Rason

    • 价格$12.99
    • 评分4.0
    • 评论1

    亚马逊页面 · KDPTop 完整数据

  9. 《Practical Small Language Models : Build Private AI Applications with Qwen, Gemma, Phi, Oll》封面,作者 Adrian Rason

    Practical Small Language Models : Build Private AI Applications with Qwen, Gemma, Phi, Ollama, Fine-Tuning, Quantization, RAG, and Agents

    作者 Adrian Rason

    • 价格$12.99
    • 评论-

    亚马逊页面 · KDPTop 完整数据

  10. 《Open LLM Fine-Tuning for Developers: Build, Evaluate, Optimize, and Deploy Specialized Mod》封面,作者 Adrian Rason

    Open LLM Fine-Tuning for Developers: Build, Evaluate, Optimize, and Deploy Specialized Models with LoRA, QLoRA, SFT, and Preference Tuning

    作者 Adrian Rason

    • 价格$11.99
    • 评分1.0
    • 评论1

    亚马逊页面 · KDPTop 完整数据

主要上榜类目

数据说明

数据来自 KDPTop 每天对 Amazon 公开榜单页面的抓取,中位数基于最新一期畅销榜。机会分综合了评论门槛、低评论书占比、榜单更替、新书占比和价格,0–100 分,越高越容易进入。