DeepSeek Harness plugin

dsh-diffgeom

Differential-geometry symbolic computation for DeepSeek Harness via SymPy.diffgeom

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Source facts

Repository
hatter123/dsh-diffgeom
Latest update
Aug 19, 2026
Category
Tools & Capabilities
GitHub stars
0
Format
plugin
Catalog evidence
Upstream dsh.bundle evidence
Evidence path
package.json#dsh.bundle
Checked against
0.1.0-rc.8
Upstream check date
2026-08-20

This evidence comes from the upstream catalog. This site has not installed, run, or security-reviewed the plugin.

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GitHub: https://github.com/hatter123/dsh-diffgeom
Plugin: dsh-diffgeom
Author: hatter123

Check the source files

Read the README and other files from this plugin directory before installing.

File explorer3 files
README.mdSource · read only

dsh-diffgeom

Differential-geometry symbolic computation for DeepSeek Harness. It registers a diffgeom tool that runs coordinate-free differential geometry through SymPy.diffgeom and returns the symbolic result.

Prerequisites

Python 3 with SymPy installed:

python -m pip install sympy

Verify:

python -c "import sympy; print(sympy.__version__)"

Install

dsh plugin --profile web add "D:/VSCode_/Project/dsh/dsh-diffgeom"

(or publish to npm and dsh plugin --profile web add dsh-diffgeom)

What it can do

  • manifolds, patches, coordinate systems
  • scalar fields and tensor fields (abstract, coordinate-free)
  • exterior derivative d (Differential)
  • wedge product (Wedge)
  • Lie derivative (LieDerivative)
  • covariant derivative, metric → Christoffel symbols → Riemann/Ricci components

Preloaded objects

The tool evaluates your Python code with a working Euclidean manifold already set up:

  • 2D: m, p, r2, coordinates x,y, basis 1-forms ex,ey, basis vectors e_x,e_y, metric g
  • 3D: m3, p3, r3, coordinates x3,y3,z3, basis ex3,ey3,ez3, vectors e_x3,e_y3,e_z3, metric g3

Plus the usual constructor/operation names: Manifold, Patch, CoordSystem, TensorProduct, Wedge, LieDerivative, Differential, metric_to_Christoffel_2nd, metric_to_Ricci_components, metric_to_Riemann_components, symbols, Function, simplify.

Examples

d(x*y)                     # exterior derivative of the scalar field x*y
Wedge(ex, ey)(e_x, e_y)    # wedge of basis 1-forms evaluated on basis vectors → 1
LieDerivative(e_x, x*y)    # Lie derivative of x*y along e_x → y

How it works

index.js runs python diffgeom_backend.py "<code>" via Node's child_process, capturing stdout. The backend builds the Euclidean manifold, evals the code, and prints the result.