This is your go-to for symbolic math in Python when you need exact answers instead of floating point approximations. It covers the full SymPy workflow from defining symbols and solving equations algebraically to calculus operations, matrix manipulations, and physics calculations. The skill includes proper guidance on lambdify for converting symbolic expressions to fast NumPy functions, code generation for C and Fortran, and critical details like using assumptions on symbols to get better simplifications. What makes it genuinely useful is the coverage of common pitfalls, like the difference between Rational(1,2) and 0.5, and when to reach for solveset versus linsolve versus dsolve. If you're doing anything beyond basic numerical computation, this skill will save you from StackOverflow rabbit holes.
- skills.sh installs
- 396
- GitHub stars
- 33.2K
- last updated
- Aug 21, 2026
Install
$ npx -y skills add davila7/claude-code-templates --skill sympy --agent claude-codeInstalls 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.
When to Use This Skill
Use this skill when:
- Solving equations symbolically (algebraic, differential, systems of equations)
- Performing calculus operations (derivatives, integrals, limits, series)
- Manipulating and simplifying algebraic expressions
- Working with matrices and linear algebra symbolically
- Doing physics calculations (mechanics, quantum mechanics, vector analysis)
- Number theory computations (primes, factorization, modular arithmetic)
- Geometric calculations (2D/3D geometry, analytic geometry)
- Converting mathematical expressions to executable code (Python, C, Fortran)
- Generating LaTeX or other formatted mathematical output
- Needing exact mathematical results (e.g.,
sqrt(2)not1.414...)
Core Capabilities
1. Symbolic Computation Basics
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- Repository
- github.com/davila7/claude-code-templates
- Categories
- Python, Game Development
- First seen
- Jun 3, 2026
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