daft
NewSkills for working with Daft: UDF tuning, distributed scaling, and docs navigation
Summary
This skill helps developers work with Daft, a distributed DataFrame library for Python.
- It provides guidance on tuning UDFs for performance, scaling workloads across clusters, and navigating Daft's documentation efficiently.
Install & Usage
mkdir -p .claude/skillsmkdir -p .claude/skills && curl -o .claude/skills/daft.md https://raw.githubusercontent.com/Eventual-Inc/Daft/main/SKILL.md/daftUse Cases
Usage Examples
/daft How can I optimize a UDF that uses external libraries in Daft?
/daft Show me how to scale a group-by aggregation across multiple nodes
/daft Find the documentation for Daft's window functions
Security Audits
Frequently Asked Questions
What is daft?
This skill helps developers work with Daft, a distributed DataFrame library for Python. It provides guidance on tuning UDFs for performance, scaling workloads across clusters, and navigating Daft's documentation efficiently.
How to install daft?
To install daft: create the skills directory (mkdir -p .claude/skills), then run: mkdir -p .claude/skills && curl -o .claude/skills/daft.md https://raw.githubusercontent.com/Eventual-Inc/Daft/main/SKILL.md. Finally, /daft in Claude Code.
What is daft best for?
daft is a skill categorized under Documentation. Created by Eventual, Inc..
What can I use daft for?
daft is useful for: Tuning a Python UDF to avoid serialization bottlenecks in Daft; Scaling a Daft DataFrame operation from a single machine to a Ray cluster; Finding the correct API for partitioning data in Daft documentation; Debugging a slow Daft query by identifying shuffle or memory issues; Converting a pandas pipeline to Daft for distributed execution; Optimizing I/O patterns when reading large datasets with Daft.