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Apache Feather/Arrow IPC format reference. V1 vs V2 format differences, pyarrow.feather read/write with compression, R arrow package integration, Arrow type system, Feather vs Parquet benchmarks, pandas DataFrame caching, LZ4/ZSTD compression options, and pipeline best practices.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/bytesagain/ai-skills --skill feather命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
Build BI dashboard specs, chart plans, SQL queries, and Apache Superset chart JSON. Use when creating dashboards, BI reports, KPI charts, or visualization layouts.
Localize product listings across English and Chinese ecommerce channels. Use when adapting Amazon, Shopify, Taobao, Pinduoduo, TK, or independent-site copy.
Optimize ecommerce keywords and product copy. Use when building keyword maps, rewriting titles, improving category text, auditing listings, or planning search terms.
正在显示 SKILL.md
基于 SOC 职业分类
| name | feather |
| version | 1.0.0 |
| description | Apache Feather/Arrow IPC format reference. V1 vs V2 format differences, pyarrow.feather read/write with compression, R arrow package integration, Arrow type system, Feather vs Parquet benchmarks, pandas DataFrame caching, LZ4/ZSTD compression options, and pipeline best practices. |
| author | BytesAgain |
| homepage | https://bytesagain.com |
| source | https://github.com/bytesagain/ai-skills |
| tags | ["feather","arrow","ipc","columnar","pandas","dataframe","data"] |
| category | data |
Apache Feather/Arrow IPC format reference — fast columnar DataFrame I/O.
| Command | Description |
|---|---|
intro | Feather overview, V1 vs V2, key properties |
python | pyarrow.feather read/write, benchmarks |
r-lang | R arrow package, Python↔R interop |
schema | Arrow types, nested types, metadata |
vs-parquet | Speed vs compression tradeoffs |
pandas | pd.read_feather, caching patterns |
compression | LZ4/ZSTD options, when to use each |
best-practices | Pipeline patterns, file size guidelines |