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Subaru-PFS
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testing

Identify edge cases and parameterized tests for HoloViz software packages.

3|Updated May 31, 2023
Search Tags:#testing#pytest#edge-cases#unit-testing#quality-assurance#holoviz
One-click install
npx skills add https://github.com/Subaru-PFS/spt_etc_webapp --skill testing-subaru-pfs
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: testing
Source: https://github.com/Subaru-PFS/spt_etc_webapp/tree/main/.claude/skills/contributing-to-holoviz/skills/testing
Command: npx skills add https://github.com/Subaru-PFS/spt_etc_webapp --skill testing-subaru-pfs

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill addresses the challenge of maintaining high-quality, reliable test coverage in HoloViz repositories by providing standardized patterns for edge cases and logical validation.

Core Features & Use Cases

  • Edge Case Identification: Provides systematic approaches to testing NaN values, datetime types, and boundary conditions common in data-heavy applications.
  • Test Pattern Standardization: Offers templates for parameterized testing to reduce code duplication and improve test readability.
  • Use Case: Use this skill when writing new unit tests for a data processing function to ensure that empty inputs, duplicate labels, and floating-point errors are handled gracefully before submitting a pull request.

Quick Start

Use the testing skill to review the current test suite for logical gaps and suggest parameterized test cases for the specified data processing module.

Frequently Asked Questions about testing

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I identify edge cases for unit testing data-heavy HoloViz applications?▼

To handle empty inputs and duplicate labels in HoloViz tests, use systematic logical validation patterns. This skill offers templates to ensure graceful error handling for boundary conditions and data type anomalies before code submission.

What is the best way to reduce code duplication in pytest test suites?▼

Robust unit and UI tests in HoloViz require focusing on boundary conditions, data type validation, and logical branching. This skill facilitates creating these tests through parameterized patterns and systematic error handling approaches.

How do I review a test suite for logical gaps in data processing modules?▼

Before submitting a pull request, ensure empty inputs, duplicate labels, and floating-point errors are handled gracefully. This skill provides standardized testing guidelines to verify robust unit test coverage for HoloViz packages.

Does this testing skill provide templates for parameterized testing in HoloViz?▼

This skill addresses maintaining high-quality test coverage in HoloViz repositories by offering standardized patterns for edge cases. It targets challenges with NaN values, datetime types, and boundary conditions common in data-heavy applications.

Why does my unit test fail when handling NaN values and datetime types?▼

Systematic error handling is required when unit tests fail on empty inputs or duplicate labels. This skill offers standardized testing guidelines to catch logical gaps and ensure boundary conditions are validated before submission.

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