casadi/casadi

CasADi is a symbolic framework for numeric optimization implementing automatic differentiation in forward and reverse modes on sparse matrix-valued computational graphs. It supports self-contained C-code generation and interfaces state-of-the-art codes such as SUNDIALS, IPOPT etc. It can be used from C++, Python, Matlab/Octave, Julia or Javascript

What is CasADi?

CasADi is an open‑source software library that you can install via PyPI (the Python package index) and download from GitHub. The project’s homepage (http://casadi.org) and a dedicated install guide (http://install.casadi.org) provide the full documentation and installation steps.

How popular is it?

  • The GitHub repository shows a cumulative download badge, indicating many users have fetched the source code.
  • The PyPI badge reports a high number of package downloads, suggesting active use in the Python ecosystem.

Getting started

  1. Visit the homepage – The main site (http://casadi.org) contains an overview, tutorials, and API reference.
  2. Read the install guide – Detailed installation instructions are available at http://install.casadi.org, covering all supported platforms.
  3. Install via pip – The library is published on PyPI, so you can install it with the standard command:
    pip install casadi

Who might use it?

Anyone needing a ready‑made, well‑maintained library that can be pulled into Python projects. The download statistics suggest it is used in a variety of scientific and engineering contexts.

All information above is taken directly from the repository’s README and the linked resources.

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