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

4 days ago · Want to build from source rather than use a Python distribution or pre-built SciPy binary? This guide will describe how to set up your build environment, and how to build SciPy …

Here is a step-by-step guide to setting up a project to use SciPy, with uv, a Python package manager. Install uv following, the instructions in the uv documentation.

SciPy is a collection of mathematical algorithms and convenience functions built on NumPy . It adds significant power to Python by providing the user with high-level commands and classes …

In SciPy there are modules whose names don’t start with an underscore, but that should be considered private. To clarify which modules these are, we define below what the public API is …

Numpy and Scipy Documentation Welcome! This is the documentation for Numpy and Scipy. For contributors: Numpy developer guide Scipy developer guide Latest releases: Complete Numpy …

SciPy is a collection of mathematical algorithms and convenience functions built on the NumPy extension of Python. It adds significant power to the interactive Python session by providing …

SciPy is a set of open source (BSD licensed) scientific and numerical tools for Python. It currently supports special functions, integration, ordinary differential equation (ODE) solvers, gradient …

The SciPy library is one of the core packages that make up the SciPy stack. It provides many user-friendly and efficient numerical routines, such as routines for numerical integration, …

To try out SciPy, you don’t even need to install it! You can use SciPy in your browser at https://jupyter.org/try-jupyter/lab/ - just open a Python Notebook, then write import scipy in one …