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Why SciPy? Fundamental algorithms. Broadly applicable. Foundational. Interoperable. Performant. Open source.
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SciPy Install Documentation Community About Us Contribute Install Documentation Community About Us Contribute SciPy Fundamental algorithms for scientific computing in Python Get started SciPy 1.11.2 released! 2023-08-17 Fundamental algorithms SciPy provides algorithms for optimization, integration, interpolation, eigenvalue problems, algebraic equations, differential equations, statistics and many other classes of problems. Broadly applicable The algorithms and data structures provided by SciPy are broadly applicable across domains. Foundational Extends NumPy providing additional tools for array computing and provides specialized data structures, such as sparse matrices and k-dimensional trees. Performant SciPy wraps highly-optimized implementations written in low-level languages like Fortran, C, and C...
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