NumPy (pronounced ) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications. NumPy is open-source software and has many contributors. NumPy is fiscally sponsored by NumFOCUS.
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NumPy (pronounced ) is a library for the Python programming language, adding support for large, multi-dimensional arrays and matrices, along with a large collection of high-level mathematical functions to operate on these arrays. The predecessor of NumPy, Numeric, was originally created by Jim Hugunin with contributions from several other developers. In 2005, Travis Oliphant created NumPy by incorporating features of the competing Numarray into Numeric, with extensive modifications. NumPy is open-source software and has many contributors. NumPy is fiscally sponsored by NumFOCUS.
== History == ===matrix-sig=== The Python programming language was not originally designed for numerical computing, but attracted the attention of the scientific and engineering community early on. In 1995 the special interest group (SIG) matrix-sig was founded with the aim of defining an array computing package; among its members was Python designer and maintainer Guido van Rossum, who extended Python's syntax (in particular the indexing syntax) to make array computing easier.
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NumPy requires pytest and hypothesis . Tests can then be run after installation with: NumPy is a community-driven open source project developed by a diverse group of contributors. The NumPy leadership has made a strong commitment to creating an open, inclusive, and positive community. Please read the NumPy Code of Conduct for guidance on how to interact with others in a way that makes our community thrive. Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact us through the mailing list first. Writing code isn’t the only way to contribute to NumPy. You can also: review pull requests help us stay on top of new and old issues develop tutorials, presentations, and other educational materials maintain and improve our website develop graphic design for our brand assets and promotional materials translate website content help with outreach and onboard new contributors write grant proposals and help with other fundraising efforts We also have a biweekly community call, details of which are announced on the mailing list. You are very welcome to join. If you are new to contributing to open source, this guide helps explain why, what, and how to successfully get involved.
Excerpt from the source-code README · 4,225 chars · not written by Vinony
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Discovered by embedding cosine similarity (sentence-transformers MiniLM, 384-dim).