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

Sep 11, 2025 · 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 …

To clarify which modules these are, we define below what the public API is for SciPy, and give some recommendations for how to import modules/functions/objects from SciPy.

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

On this base, the SciPy ecosystem includes general and specialised tools for data management and computation, productive experimentation, and high-performance computing.

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, …

Large-scale bundle adjustment in scipy demonstrates large-scale capabilities of least_squares and how to efficiently compute finite difference approximation of sparse Jacobian. Robust …