vamseeachanta
vamseeachanta/workspace-hub
相关职业SOC
基于 SOC 职业分类
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/vamseeachanta/workspace-hub --skill xlsx-to-python-recommended-stack命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
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
基于 SOC 职业分类
| name | xlsx-to-python-recommended-stack |
| description | Sub-skill of xlsx-to-python: Recommended Stack (+2). |
| version | 1.0.0 |
| category | data |
| type | reference |
| scripts_exempt | true |
| Library | Purpose | Install | Status |
|---|---|---|---|
| openpyxl | Cell values + formula strings + named ranges | uv add openpyxl | Active, stable |
| formulas | Formula parsing, AST, dependency graph, evaluation | uv add formulas | Active (v1.3.3) |
| networkx | Dependency graph analysis (topological sort) | uv add networkx | Active, stable |
| oletools | VBA macro source code extraction from .xlsm/.xls | uv add oletools | Active, stable |
| Library | What It Does | Why Not Primary | When to Use |
|---|---|---|---|
| pycel | Compiles Excel to executable Python + graph viz | Broader scope than needed; heavier dependency | When you need full workbook simulation |
| xlcalculator | Converts Excel formulas to Python + evaluates | Inactive (no releases in 12+ months); modernized koala2 | Reference for formula-to-Python translation patterns |
| graphedexcel | Cell dependency graph visualization (networkx + matplotlib) | Viz-only; no formula parsing | Quick visual audit of spreadsheet complexity |
| excel-dependency-graph | Directed graph of formula dependencies | Lightweight but limited features | Simple dependency mapping without evaluation |
| formula-dependency-excel | Cell dependency extraction | Minimal; proof-of-concept level | Quick prototyping |
formulas LibraryThe formulas library can compile an entire Excel workbook into a Python
DispatchPipe — a callable function with defined inputs and outputs. This is
the most mature approach for complex workbooks:
import formulas
# Load and compile the workbook
xl_model = formulas.ExcelModel().loads("calculation.xlsx").finish()
# Get the dependency-ordered calculation dispatcher
solution = xl_model.calculate()
# Access any cell's computed value
value = solution.get("'Sheet1'!B10")
# Compile a reusable function with fixed I/O
func = xl_model.compile(
inputs=["'Inputs'!B2:B10"],
outputs=["'Results'!C5:C8"]
)
result = func({"'Inputs'!B2:B10": input_array})
When to use formulas vs raw openpyxl:
| Scenario | Use |
|---|---|
| Simple formulas (arithmetic, basic functions) | openpyxl + custom parser |
| Complex formulas (VLOOKUP, INDEX/MATCH, nested IF) | formulas library |
| Need dependency graph visualization | formulas + plot extra, or graphedexcel |
| Need to evaluate formulas without Excel | formulas or pycel |
| Need only formula strings + cell refs | openpyxl alone |