A Python library for symbolic mathematics, aiming to become a full-featured computer algebra system (CAS) while keeping the code as simple as possible to be comprehensible and easily extensible.
SymPy
- Python
- Aerospace, Electrical and Electronics, Mathematics, Mechanical Engineering, Simulation
- Computer Algebra Systems (CAS), Design for Sustainability, Engineering, Machine Learning, Mathematics, Physics, Symbolic Algebra System (SAS)
Features:
- Symbolic algebra (expressions,equations),calculus (derivatives,integrals,limits,series),solvers (algebraic,differential equations),matrix operations (symbolic),discrete math,geometry,plotting (basic,integration with matplotlib),code generation (C,Fortran,NumPy,Theano),physics module (mechanics,quantum)
Pricing:
- Free
- Powerful symbolic computation capabilities, free and open-source, integrates well with the scientific Python ecosystem, good for deriving equations and understanding mathematical concepts, extensive documentation.
- Can be slower than numerical libraries for pure numerical computation, some advanced CAS features might be less mature than specialized commercial systems (Mathematica,Maple), symbolic integration can be challenging for complex integrals.
Best for:
- Students, educators, researchers, and engineers who need to perform symbolic mathematical computations, manipulate expressions, solve equations, and derive analytical solutions.