Sympy

When you need exact mathematical results instead of floating-point approximations, this is your tool. It handles symbolic algebra, calculus (derivatives, integrals, limits), equation solving, and symbolic linear algebra. The skill covers everything from basic simplification to physics calculations and code generation via lambdify or LaTeX export. Key practice: always use Rational or S() for exact arithmetic instead of Python floats, and leverage symbol assumptions (positive, real, integer) to get cleaner simplifications. When you need to evaluate expressions thousands of times, convert to NumPy functions with lambdify rather than repeatedly calling subs(). Requires Python 3.9+ and SymPy 1.14+.

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GitHub stars: 56.6K
last updated: Aug 21, 2026

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Install

$ npx -y skills add k-dense-ai/scientific-agent-skills --skill sympy --agent claude-code

Installs into .claude/skills of the current project.

Files

SymPy - Symbolic Mathematics in Python

Overview

SymPy is a Python library for symbolic mathematics that enables exact computation using mathematical symbols rather than numerical approximations. This skill provides comprehensive guidance for performing symbolic algebra, calculus, linear algebra, equation solving, physics calculations, and code generation using SymPy.

Installation

Reviewed against current official documentation and executed with SymPy 1.14.0 on Python 3.13.3 (2026-10-01). Core SymPy requires Python 3.9+; the tested NumPy 2.5.3 / SciPy 1.18.1 stack needs Python 3.12+. SymPy 1.14.0 requires mpmath>=1.1,<1.4; use the compatible 1.3.0, not the newer 1.4.x release. See verification and official sources for coverage.

# Install SymPy using uv
uv pip install "sympy==1.14.0"

# Optional: for lambdify and plotting examples
uv pip install numpy scipy matplotlib

Check your version:

import sympy
print(sympy.__version__)

When to Use This Skill

SKILL.md on GitHub

Details

Repository: github.com/k-dense-ai/scientific-agent-skills
Categories: AI & Agent Building, Data Science & ML, Python
First seen: Jun 3, 2026