  SciPy is an open source scientific computing library for the Python
programming language. SciPy 1.0 was released in late 2017, about 16 years after
the original version 0.1 release. SciPy has become a de facto standard for
leveraging scientific algorithms in the Python programming language, with more
than 600 unique code contributors, thousands of dependent packages, over
100,000 dependent repositories, and millions of downloads per year. This
includes usage of SciPy in almost half of all machine learning projects on
GitHub, and usage by high profile projects including LIGO gravitational wave
analysis and creation of the first-ever image of a black hole (M87). The
library includes functionality spanning clustering, Fourier transforms,
integration, interpolation, file I/O, linear algebra, image processing,
orthogonal distance regression, minimization algorithms, signal processing,
sparse matrix handling, computational geometry, and statistics. In this work,
we provide an overview of the capabilities and development practices of the
SciPy library and highlight some recent technical developments.
