SciPy

Fundamental algorithms

SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems.

Broadly applicable

The algorithms and data structures provided by SciPy are broadly applicable across domains.

Foundational

Extends NumPy providing additional tools for array computing and provides specialized data structures, such as sparse matrices and k-dimensional trees.

Performant

SciPy wraps highly-optimized implementations written in low-level languages like Fortran, C, and C++. Enjoy the flexibility of Python with the speed of compiled code.

Easy to use

SciPy’s high level syntax makes it accessible and productive for programmers from any background or experience level.