Cadabra vs SymPy

Struggling to choose between Cadabra and SymPy? Both products offer unique advantages, making it a tough decision.

Cadabra is a Science & Math solution with tags like algebra, tensor, polynomial, simplification, physics, opensource.

It boasts features such as Symbolic tensor computations, Component tensor computations, Extensible architecture, Python API, TeX and LaTeX output and pros including Specialized for tensor computations in theoretical physics, Clean and modular codebase, Active development and support.

On the other hand, SymPy is a Development product tagged with mathematics, symbolic-math, computer-algebra.

Its standout features include Symbolic mathematics, Computer algebra system, Mathematical expressions manipulation, Equation solving, Symbolic integration, Symbolic differentiation, and it shines with pros like Open source, Free to use, Large community support, Extensive documentation, Integrates well with NumPy and SciPy.

To help you make an informed decision, we've compiled a comprehensive comparison of these two products, delving into their features, pros, cons, pricing, and more. Get ready to explore the nuances that set them apart and determine which one is the perfect fit for your requirements.

Cadabra

Cadabra

Cadabra is an open-source computer algebra system designed specifically for advanced theoretical physics computations involving tensor polynomial simplifications. It has a modern codebase focused on flexibility, extensibility and understandability.

Categories:
Science & Math Physics
algebra tensor polynomial simplification physics opensource

Cadabra Features

  1. Symbolic tensor computations
  2. Component tensor computations
  3. Extensible architecture
  4. Python API
  5. TeX and LaTeX output

Pricing

  • Open Source

Pros

Specialized for tensor computations in theoretical physics

Clean and modular codebase

Active development and support

Cons

Limited user base compared to more general CAS

Less comprehensive documentation

Fewer supported operations than Mathematica or Maple

SymPy

SymPy

SymPy is an open-source Python library for symbolic mathematics. It provides computer algebra capabilities to manipulate mathematical expressions, calculate limits, solve equations, perform symbolic integration and differentiation, and more.

Categories:
Development Scientific Computing
mathematics symbolic-math computer-algebra

SymPy Features

  1. Symbolic mathematics
  2. Computer algebra system
  3. Mathematical expressions manipulation
  4. Equation solving
  5. Symbolic integration
  6. Symbolic differentiation

Pricing

  • Open Source

Pros

Open source

Free to use

Large community support

Extensive documentation

Integrates well with NumPy and SciPy

Cons

Steep learning curve

Not as fast as optimized commercial CAS

Limited plotting capabilities

Not ideal for numerical computations