SciPy essentially functions as a library for statistics, linear algebra, optimization, and mathematics. It is designed to interact with NumPy arrays and includes a number of user-friendly and efficient numerical functions, such as numerical integration and optimization techniques.

A multidimensional array given by the NumPy module is the basic data structure used by SciPy. NumPy has certain functions for linear algebra, Fourier transformations, and random number generation, although they don’t have the same breath as the SciPy equivalents.

Project Background

  • Project: SciPy
  • Author: Travis Oliphant, Pearu Peterson, Eric Jones
  • Initial Release: 2001
  • Type: Technical Computing
  • License: New BSD Licence
  • Contains: cluster, constant, integrate, interpolate, optimize, signal, park, etc
  • Language:  Python, Fortran, C, C++
  • GitHub: scipy/scipy with 8.7k stars and 1074 contributors
  • Runs On: Windows, Linux, MacOS
  • Twitter: None


  • Provides additional tools for array computing
  • Provides specialized data structures
  • Provides algorithm for higher order mathematics
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