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Feather

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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.

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  • Added September 7, 2026
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Scanned September 7, 2026

npx -y skills add bytesagain/ai-skills --skill feather --agent claude-code

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SKILL.md
---
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"
---

# Feather

Apache Feather/Arrow IPC format reference — fast columnar DataFrame I/O.

## Commands

| 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 |

Files in this skill

  • SKILL.md1.1 KB
  • scripts/script.sh12.7 KB

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