Below is the exact text you should paste into README.md — do not include any surrounding triple‑backtick lines.
Your launch‑pad for building Manim animations that explain network‑science & graph‑theory concepts.
If you’re a researcher, educator, or student who wants to turn abstract graph‑theory ideas into eye‑catching videos, ManimNet gives you:
| What you get | What it covers |
|---|---|
| Ready‑made scenes | • Community detection (Louvain / modularity) • Common network topologies (star, ring, scale‑free, small‑world …) • Adjacency‑matrix ↔ graph dual views • Graph‑theoretic building blocks (paths, cycles, cliques, MST) |
| Reusable helpers | CustomDot, build_edge, build_clique, colour palettes, image nodes |
| Scaffold & tests | CI, pre‑commit hooks, pytest, docs skeleton |
| CLI | mnet render <scene> one‑liner rendering |
Goal: shorten the time from idea → high‑res MP4 so you can focus on the story rather than boilerplate.
Install ManimNet (once published to PyPI) and render an example:
pip install manimnet
mnet render multi‑clique # <— plays a community‑detection example