SciPy
Empowering the scientific community with open-source mathematics, science, and engineering tools through SciPy's user-friendly and efficient software and collaborative development opportunities.
SciPy is an open-source community offering a suite of mathematical, scientific, and engineering tools with modules for optimization, linear algebra, Fourier transforms, signal processing, and more. It's built to work seamlessly with NumPy and provides user-friendly, efficient numerical routines. SciPy encourages contributions beyond just coding, such as reviewing pull requests, maintaining the website, creating graphic design, and assisting in outreach efforts. Its software is available on major operating systems, free of charge, and valued by leading scientists and engineers.
About SciPy
SciPy is an open-source software community for mathematics, science, and engineering. It offers a collection of modules, including statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers, among others. SciPy's software is built to work with NumPy arrays and provides user-friendly and efficient numerical routines.
SciPy's mission is not limited to coding contributions. Individuals can review pull requests, triage issues, develop tutorials, maintain and improve the website, create graphic design for brand assets, contribute to outreach efforts, write grant proposals, or assist in fundraising initiatives. For those new to contributing to open-source projects, SciPy offers a comprehensive guide on getting involved.
SciPy's software, including its dependencies on NumPy, is available on all major operating systems, quick to install, and free of charge. Both NumPy and SciPy are user-friendly while offering powerful capabilities that are trusted by leading scientists and engineers worldwide. If you require number manipulation and result visualization or publication, consider trying out SciPy.
For installation instructions, consult the official SciPy install guide.
Contributions to SciPy are highly valued, with small improvements and bug fixes being particularly welcome. New contributors may find good starting points in issues labeled as 'good first issue.'