What specific error does this skill solve?

It solves the Ruff F821 'undefined name' error which occurs when a linter flags a module used in a type hint that isn't imported at the top level because it's an optional dependency.

Does this pattern affect runtime performance?

No. The imports inside the TYPE_CHECKING block are only executed by static analysis tools and IDEs, meaning there is zero performance overhead at runtime.

Will my IDE still show autocompletion for these types?

Yes, modern IDEs like VS Code and PyCharm specifically look for the TYPE_CHECKING block to provide intellisense and type checking even if the package isn't currently installed in your environment.

Why is 'from __future__ import annotations' necessary?

This import enables PEP 563, which tells Python to treat all type hints as strings, preventing the interpreter from trying to evaluate them at runtime when the module might not be installed.

Python Optional Dependency Type Checker

Name: Python Optional Dependency Type Checker
Author: smith6jt-cop

bysmith6jt-cop

0•

开发者工具

Resolves Ruff F821 undefined name errors for optional Python dependencies using the TYPE_CHECKING pattern.

This skill provides a standardized implementation pattern for handling type hints with optional dependencies—such as Pandas, Dask, or CuPy—without requiring them at runtime. By leveraging 'from __future__ import annotations' and the 'typing.TYPE_CHECKING' flag, it allows developers to satisfy static analysis tools like Ruff and maintain IDE autocompletion while preventing runtime import errors in environments where specific libraries are not installed. This is essential for building flexible Python libraries and data science pipelines that support multiple execution backends.

主要功能

01Standardizes the use of quoted string annotations for type safety

020 GitHub stars

03Implements PEP 563 postponed evaluation of annotations

04Configures conditional import blocks using TYPE_CHECKING

05Eliminates Ruff F821 'undefined name' linter errors

06Maintains full IDE autocompletion for optional modules

使用场景

01Developing libraries with optional feature sets like GPU support via CuPy

02Improving type safety in data science codebases with conditional imports

03Resolving linter failures in CI/CD pipelines for multi-dependency projects

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add smith6jt-cop/skills_registry type-checking-pattern

For use in Claude.ai and ChatGPT

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