user-acceptance-test

Validate a Python structural engineering library through fresh install, imports, and public API checks.

5|1|Updated Dec 10, 2025
One-click install
npx skills add https://github.com/Pravin-surawase/structural_engineering_lib --skill user-acceptance-test
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: user-acceptance-test
Source: https://github.com/Pravin-surawase/structural_engineering_lib/tree/main/.github/skills/user-acceptance-test
Command: npx skills add https://github.com/Pravin-surawase/structural_engineering_lib --skill user-acceptance-test

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill catches release-breaking issues that internal tests often miss by validating the library the way an actual user installs, imports, and runs it.

Core Features & Use Cases

  • Fresh-install verification: Confirms the package can be installed cleanly and imported without deprecation warnings or hidden packaging problems.
  • End-to-end workflow checks: Exercises beam design, column design, detailing, BBS generation, reporting, and CSV import to prove the full pipeline works.
  • API surface validation: Verifies exported symbols, reload behavior, and basic runtime stability so public interfaces remain reliable after changes.
  • Use case: Before a release, run this Skill to make sure the library behaves correctly for a structural engineer using it through Python, a CLI-like workflow, or integrated automation.

Quick Start

Ask the assistant to run a full user acceptance test for the library, including fresh installation, import checks, core design workflows, CSV parsing, reporting, and API surface validation.

Frequently Asked Questions about user-acceptance-test

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

FAQPage Schema
How do I validate a Python library release from a real user's perspective?

User acceptance testing for a Python release verifies clean installation, warning-free imports, public API surface reliability, and full pipeline workflows. It catches release-breaking packaging issues that internal unit tests often miss by simulating an actual end-user environment.

What is API surface validation and why does it matter for packaging changes?

API surface validation checks exported symbols, module reload behavior, and runtime stability to ensure public interfaces remain reliable. It matters for packaging changes because it catches hidden import warnings and structural regressions before they reach end users.

How do I test structural engineering workflows like beam design and BBS generation in Python?

Testing structural engineering workflows in Python involves running end-to-end pipeline checks for beam design, column design, detailing, BBS generation, CSV ingestion, and report creation. This verifies the full pipeline operates correctly from a user's perspective.

Does user acceptance testing require a clean Python environment setup?

Yes, user acceptance testing requires a clean Python environment setup to accurately simulate a fresh install. This confirms the package installs without hidden dependencies and imports without deprecation warnings or packaging problems.

What is the best way to catch release-breaking Python import errors before publishing?

The best way to catch release-breaking Python import errors is to run fresh-install verification and warning-free import checks in a clean environment. This validates packaging integrity, confirms exported symbols, and ensures public API surfaces function correctly before release.

Why does my Python package pass internal tests but fail on fresh install?

Python packages often pass internal tests but fail on fresh install due to hidden packaging problems, missing dependencies, or deprecation warnings. Running user acceptance tests in a clean environment exposes these release-breaking issues by validating imports and public API surfaces.