wehub-resource-sync
89 lines
3.3 KiB
Markdown
89 lines
3.3 KiB
Markdown
# Case Study: rsl-siege-manager (Python + TypeScript monorepo)
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A graphify dry-run against [`glitchwerks/rsl-siege-manager`](https://github.com/glitchwerks/rsl-siege-manager) — a real-world web app with a Python (FastAPI) backend, a TypeScript (React + Vite) frontend, and a Python Discord bot, all in one repo. Captured here as a worked example of running graphify on a mixed-language full-stack codebase that includes a substantial test suite.
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**Corpus:** `glitchwerks/rsl-siege-manager` @ commit `6085fd66`
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**Date:** 2026-05-15
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**Findings:** [`review.md`](./review.md)
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**Raw artifacts:** [`GRAPH_REPORT.md`](./GRAPH_REPORT.md), [`graph.html`](./graph.html), [`graph.json`](./graph.json), [`manifest.json`](./manifest.json)
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## How to reproduce
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### 1. Clone the corpus
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```bash
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git clone https://github.com/glitchwerks/rsl-siege-manager
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cd rsl-siege-manager
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git checkout 6085fd66
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```
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### 2. Install the CLI
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```powershell
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uv tool install graphifyy
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```
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> The PyPI package is `graphifyy` (double-y). The CLI command is `graphify`.
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Verify it's on PATH:
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```powershell
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graphify --version
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```
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If "not recognized" on Windows, open a new shell — `uv tool` updates PATH but the current session won't see it.
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### 3. Run extraction
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This case study ran extraction with no `.graphifyignore` (the run included tests). To reproduce a tests-included run:
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```powershell
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graphify extract .
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```
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Watch terminal output. graphify uses tree-sitter for code (free, fast) and LLM API calls only for non-code files (markdown, PDFs, images). On a code-heavy repo like rsl-siege-manager, the cost is dominated by docs.
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Check the cost summary when it finishes:
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```powershell
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Get-Content .\graphify-out\cost.json
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```
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### 4. Inspect
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```powershell
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# The headline summary an assistant would read
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code .\graphify-out\GRAPH_REPORT.md
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# The interactive graph
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Start-Process .\graphify-out\graph.html
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```
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## What's in this directory
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| File | What it is |
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|---|---|
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| `README.md` | This file — corpus description + reproduction steps |
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| `review.md` | Findings against the headline outputs in `GRAPH_REPORT.md` |
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| `GRAPH_REPORT.md` | Raw graphify report (god nodes, communities, surprising connections, suggested questions) |
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| `graph.html` | Interactive force-directed visualization |
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| `graph.json` | Underlying graph data used by `graphify query` |
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| `manifest.json` | Per-file extraction record |
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The AST cache (`graphify-out/cache/`) is regenerable and not committed.
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## Why this corpus
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rsl-siege-manager is structurally interesting for graphify evaluation because:
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- **Three services in one repo** — Python backend, TypeScript frontend, Python bot — exercises cross-language inference.
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- **Substantial test suite** — both Python (`backend/tests/`) and TypeScript (`frontend/src/**/__tests__/`) — surfaces how degree-centrality behaves on covered codebases.
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- **17 Alembic migrations** with revision docstrings — exercises how docstring-shaped content is or is not treated as graph entities.
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- **Clean three-tier architecture** — a developer can describe the structure in one sentence, giving a clear ground truth to evaluate community detection against.
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## Reference
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- graphify repo: https://github.com/safishamsi/graphify
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- graphify PyPI: https://pypi.org/project/graphifyy/
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- rsl-siege-manager: https://github.com/glitchwerks/rsl-siege-manager
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