make-pythonic
OfficialMake DataFusion Python APIs feel native
Authorapache
Version1.0.0
Installs0
System Documentation
What problem does it solve?
This Skill addresses the friction of using DataFusion's Python bindings by allowing native Python types for literal-like arguments, reducing boilerplate from lit() and col() wrappers, while preserving backward compatibility and aligning with Pythonic expectations.
Core Features & Use Cases
- Audit and adjust function signatures in python/datafusion/functions.py to accept native Python types for literal arguments (e.g., Expr | int or Expr | float where appropriate), guided by upstream Rust constraints.
- Identify literal-only argument patterns (per Technique 1/2) and implement coercion rules, update aliases, and refresh doctests to reflect the new calling conventions.
- Provide real-world examples that demonstrate calling functions with native literals, such as split_part(col("a"), ",", 2), instead of lit(",") and lit(2).
Quick Start
Audit and refactor the python/datafusion/functions.py to accept native Python literals (e.g., 3, "x") and adjust coercion, aliases, and doctests.
Dependency Matrix
Required Modules
None requiredComponents
Standard package💻 Claude Code Installation
Recommended: Let Claude install automatically. Simply copy and paste the text below to Claude Code.
Please help me install this Skill: Name: make-pythonic Download link: https://github.com/apache/datafusion-python/archive/main.zip#make-pythonic Please download this .zip file, extract it, and install it in the .claude/skills/ directory.
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