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Reusable evaluation framework for assessing Python engineering packages for adoption — license compatibility, maintenance health, integration risk, and dependency strategy.
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基于 SOC 职业分类
Write outbound email and external messages in Vamsee Achanta's voice — a subtle offer to help, never bold or rash claims. Load before drafting ANY email, LinkedIn/Collide reply, proposal note, or outreach sent under his name.
Save/publish analysis or computation results from ANY ecosystem repo to Hugging Face as a queryable, viewer-renderable dataset. Use when the user wants to "save results to hugging face", "publish dataset to HF", "hugging face data saving", "save analysis results", "hf dataset", "make results queryable", or "render via datasets-server API". Reshapes nested results into flat parquet tables, writes a dataset card with a viewer `configs:` block and provenance, applies license/public-vs-private routing, enforces a domain data-quality gate (faithful-to-source != correct), publishes to `aceengineer/<repo>-<projection>`, and verifies via the datasets-server API.
Clone, create, fork, configure, and manage GitHub repositories. Manage remotes, secrets, releases, and workflows. Works with gh CLI or falls back to git + GitHub REST API via curl.
正在显示 SKILL.md
| name | engineering-package-evaluator |
| version | 1.0.0 |
| updated | "2026-02-26T00:00:00.000Z" |
| category | development |
| description | Reusable evaluation framework for assessing Python engineering packages for adoption — license compatibility, maintenance health, integration risk, and dependency strategy. |
| tags | ["package","evaluation","license","dependency","python"] |
| platforms | ["linux","macos","windows"] |
| invocation | engineering-package-evaluator |
| depends_on | [] |
| requires | [] |
| see_also | ["plugin-management"] |
Structured evaluation framework for Python engineering packages being considered for adoption into digitalmodel or other MIT-licensed projects.
Package License?
├── MIT / BSD / Apache-2.0 → Direct dependency (safe)
├── LGPL-2.1 / LGPL-3.0 → Direct dependency (dynamic linking OK)
├── GPL-2.0 / GPL-3.0 → Optional extra ONLY (cannot bundle)
├── AGPL → Do not use (viral, affects SaaS)
└── Proprietary / Unknown → Do not use without legal review
| Metric | Green | Yellow | Red |
|---|---|---|---|
| Last commit | < 6 months | 6–18 months | > 18 months |
| Last release | < 12 months | 12–24 months | > 24 months |
| Open issues | < 50 | 50–200 | > 200 |
| Response time | < 1 week | 1–4 weeks | > 1 month |
| CI status | Passing | Flaky | Failing/none |
| Python 3.10+ | Supported | Untested | Incompatible |
| Metric | Strong | Moderate | Weak |
|---|---|---|---|
| GitHub stars | > 500 | 100–500 | < 100 |
| Contributors | > 10 | 3–10 | 1–2 |
| Documentation | Comprehensive | Basic | None/stale |
| Test suite | > 80% coverage | Some tests | No tests |
| JOSS/academic paper | Published | Preprint | None |
| Risk Factor |
|---|
| Mitigation |
|---|
| Single maintainer | Thin wrapper, plan for replacement |
| Breaking API changes | Pin version, adapter pattern |
| Large dependency tree | Evaluate transitive deps too |
| C/Fortran extensions | May not build on all platforms |
| Python version lag | Test in CI with target versions |
# pyproject.toml
[project]
dependencies = ["pygef>=0.12"]
Use when: MIT/BSD/Apache/LGPL, well-maintained, stable API.
[project.optional-dependencies]
geotechnical-gpl = ["groundhog>=0.12", "openpile>=1.0"]
Use when: GPL license, or large/heavy package not needed by all users.
try:
import groundhog
HAS_GROUNDHOG = True
except ImportError:
HAS_GROUNDHOG = False
def compute_with_groundhog(soil_profile):
if not HAS_GROUNDHOG:
raise ImportError(
"groundhog required: pip install digitalmodel[geotechnical-gpl]"
)
return groundhog.some_function(soil_profile)
# parsers/gef_reader.py — thin wrapper around pygef
"""Isolates pygef dependency. If pygef is abandoned, only this file changes."""
from pygef import read_gef
def parse_gef_file(path):
gef = read_gef(path)
return CPTData(
depth_m=gef.df["depth"].values,
qc_MPa=gef.df["qc"].values,
fs_kPa=gef.df["fs"].values,
)
package:
name: groundhog
version: "0.12.0"
pypi: https://pypi.org/project/groundhog/
repo: https://github.com/snakesonabrain/groundhog
license: GPL-3.0
assessment:
license_compatible: false # GPL vs MIT host
maintenance: green # active development
community: moderate # ~200 stars, 3 contributors, JOSS paper
test_coverage: moderate # some tests, no coverage badge
python_support: ">=3.8"
api_stability: moderate # breaking changes between 0.x versions
decision: optional_extra
strategy: |
Add as optional dependency under [geotechnical-gpl] extra.
Use GPL guard pattern. Core calculations independent.
Thin adapter in _groundhog_adapter.py for cross-validation.
risks:
- Single primary maintainer
- GPL-3.0 prevents bundling in MIT distribution
- 0.x version implies API not yet stable
plugin-management — managing plugin and extension systems| Version | Date | Changes |
|---|---|---|
| 1.0.0 | 2026-02-26 | Initial skill — license tree, health metrics, integration patterns |