Skill · em Dados, IA e pesquisa
ray-data
Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL…
Procedência
- Origem: davila7/claude-code-templates
- Caminho:
cli-tool/components/skills/ai-research/data-processing-ray-data - Versão fixada:
57f899e5394bb8ca166f38eacae8f0853cbfe033 - Licença: MIT
- Espelhado em 25/09/2026
- 2 downloads no Claude Code Templates (lido em 25/09/2026)
Antes de instalar
3 arquivos · 10,6 KB · só texto, nenhum script
Instalar na sua CLI
O comando baixa a versão fixada (commit 57f899e) direto da origem, para a pasta que a CLI lê. Precisa de curl (macOS e Linux); no Windows não há comando, porque o Rook Labs é para macOS.
Claude Code
Neste projeto: instala em .claude/skills/ray-data/.
d=".claude/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Global: instala em ~/.claude/skills/ray-data/.
d="$HOME/.claude/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Codex
Neste projeto: instala em .agents/skills/ray-data/.
d=".agents/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Global: instala em ~/.agents/skills/ray-data/.
d="$HOME/.agents/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Antigravity
Neste projeto: instala em .agents/skills/ray-data/.
d=".agents/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Global: instala em ~/.gemini/antigravity-cli/skills/ray-data/.
d="$HOME/.gemini/antigravity-cli/skills/ray-data" u="https://raw.githubusercontent.com/davila7/claude-code-templates/57f899e5394bb8ca166f38eacae8f0853cbfe033/cli-tool/components/skills/ai-research/data-processing-ray-data" curl -fsSL --create-dirs \ -o "$d/SKILL.md" "$u/SKILL.md" \ -o "$d/references/integration.md" "$u/references/integration.md" \ -o "$d/references/transformations.md" "$u/references/transformations.md"
Peça ao Rook
Já usa o Rook Labs? Cole no chat do Rook: instale a skill https://rooklabs.sh/marketplace/cct.ray-data
Prévia do SKILL.md
---
name: ray-data
description: Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.
version: 1.0.0
author: Orchestra Research
license: MIT
tags: [Data Processing, Ray Data, Distributed Computing, ML Pipelines, Batch Inference, ETL, Scalable, Ray, PyTorch, TensorFlow]
dependencies: ["ray[data]", pyarrow, pandas]
---
# Ray Data - Scalable ML Data Processing
Distributed data processing library for ML and AI workloads.
## When to use Ray Data
**Use Ray Data when:**
- Processing large datasets (>100GB) for ML training
- Need distributed data preprocessing across cluster
- Building batch inference pipelines
- Loading multi-modal data (images, audio, video)
- Scaling data processing from laptop to cluster
**Key features**:
- **Streaming execution**: Process data larger than memory
- **GPU support**: Accelerate transforms with GPUs
- **Framework integration**: PyTorch, TensorFlow, HuggingFace
- **Multi-modal**: Images, Parquet, CSV, JSON, audio, video
**Use alternatives instead**:
- **Pandas**: Small data (<1GB) on single machine
- **Dask**: Tabular data, SQL-like operations
- **Spark**: Enterprise ETL, SQL queries
## Quick start
### Installation
```bash
pip install -U 'ray[data]'
…